Cost Model and Cost Estimating Software
Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]
1997-03-28T23:59:59.000Z
This chapter discusses a formalized methodology is basically a cost model, which forms the basis for estimating software.
Updating MIT's cost estimation model for shipbuilding
Smith, Matthew B., Lieutenant, junior grade
2008-01-01T23:59:59.000Z
This thesis project will update the MIT ship cost estimation model by combining the two existing models (the Basic Military Training School (BMTS) Cost Model and the MIT Math Model) in order to develop a program that can ...
Improved diagnostic model for estimating wind energy
Endlich, R.M.; Lee, J.D.
1983-03-01T23:59:59.000Z
Because wind data are available only at scattered locations, a quantitative method is needed to estimate the wind resource at specific sites where wind energy generation may be economically feasible. This report describes a computer model that makes such estimates. The model uses standard weather reports and terrain heights in deriving wind estimates; the method of computation has been changed from what has been used previously. The performance of the current model is compared with that of the earlier version at three sites; estimates of wind energy at four new sites are also presented.
Language model parameter estimation using user transcriptions
Hsu, Bo-June
In limited data domains, many effective language modeling techniques construct models with parameters to be estimated on an in-domain development set. However, in some domains, no such data exist beyond the unlabeled test ...
Rabouille, C.; Gaillard, J.F. (Univ. Paris 7 (France) Inst. de Physique du Globe de Paris (France))
1991-09-01T23:59:59.000Z
The ultimate fate of particles in aquatic environments is their burial and transformation in surficial sediments. There is an increasing need to relate quantitatively particle fluxes in the water column to the material recycled or preserved in the sediment. For this purpose, a transport-reaction model (EDGE) that represents the early diagenetic processes occurring in surficial sediments has been designed. This model uses the incoming flux of particulate matter and the overlying water composition in order to obtain simulated concentration profiles of chemical species in the bulk sediment and interstitial waters. It consists of a set of coupled nonlinear differential equations representing the oxidation of Particulate Organic Matter (POM) by a continuous sequence of electron acceptors (i.e., O{sub 2}, NO{sub 3}{sup {minus}}, MnO{sub 2}; in its preset state). The distribution of the concentrations of six components: POM, O{sub 2}, NO{sub 3}{sup {minus}}, MnO{sub 2}, Mn{sup 2+}, and {Sigma}PO{sub 4} are currently calculated. The Monod rate law has been used for representing the mineralization of POM coupled with the consumption of oxidants, and the sequence of oxidation of organic matter is represented using an inhibition function. The distributions with depth of the concentrations of the six chemical compounds are presented for different fluxes of POM at steady-state. These calculations show that the preservation of organic carbon and the extent of the mineralization processes are very sensitive to the organic carbon rain rate. For constant fluxes of POM and MnO{sub 2} arriving at the sediment water interface, the effect of an increasing sedimentation rate, as it might be produced by an augmentation of the detrital flux, is assessed on carbon preservation.
Robust estimation procedure in panel data model
Shariff, Nurul Sima Mohamad [Faculty of Science of Technology, Universiti Sains Islam Malaysia (USIM), 71800, Nilai, Negeri Sembilan (Malaysia); Hamzah, Nor Aishah [Institute of Mathematical Sciences, Universiti Malaya, 50630, Kuala Lumpur (Malaysia)
2014-06-19T23:59:59.000Z
The panel data modeling has received a great attention in econometric research recently. This is due to the availability of data sources and the interest to study cross sections of individuals observed over time. However, the problems may arise in modeling the panel in the presence of cross sectional dependence and outliers. Even though there are few methods that take into consideration the presence of cross sectional dependence in the panel, the methods may provide inconsistent parameter estimates and inferences when outliers occur in the panel. As such, an alternative method that is robust to outliers and cross sectional dependence is introduced in this paper. The properties and construction of the confidence interval for the parameter estimates are also considered in this paper. The robustness of the procedure is investigated and comparisons are made to the existing method via simulation studies. Our results have shown that robust approach is able to produce an accurate and reliable parameter estimates under the condition considered.
PARAMETER ESTIMATION IN PETROLEUM AND GROUNDWATER MODELING
Ewing, Richard E.
PARAMETER ESTIMATION IN PETROLEUM AND GROUNDWATER MODELING R.E. Ewing, M.S. Pilant, J.G. Wade the location and subsequent remediation of contaminants in groundwater to the optimization of production on grand challenge problems. In today's petroleum industry, reservoir simulators are routinely used
On the empirical statistics of parameter estimates in parametric modeling
Zhu, Yao
1988-01-01T23:59:59.000Z
Chair of Advisory Committee: Dr. Shiping Li This thesis is a document of studying empirical statistics of the parameter estimates in parametric modeling. After reviewing some common estimation methods, some simulation results on the empirical..., a new estimation method is proposed to improve the accuracy of the estimates for ARMA models. In chapter four, a new estimation method is proposed for exponential models. This method first utilizes singular value decomposition of the signal...
Hybrid Model of Existing Buildings for Transient Thermal Performance Estimation
Xu, X.; Wang, S.
2006-01-01T23:59:59.000Z
are estimated and optimized using short-term monitored operation data. A genetic algorithm estimator is developed to optimize these parameters. The parameter optimization of the simplified model and the hybrid building model are validated in a high...
Asymptotics for the maximum likelihood estimators of diffusion models
Jeong, Minsoo
2009-05-15T23:59:59.000Z
In this paper I derive the asymptotics of the exact, Euler, and Milstein ML estimators for diffusion models, including general nonstationary diffusions. Though there have been many estimators for the diffusion model, their asymptotic properties were...
New DOE Modeling Tool Estimates Economic Benefits of Offshore...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
New DOE Modeling Tool Estimates Economic Benefits of Offshore Wind Plants New DOE Modeling Tool Estimates Economic Benefits of Offshore Wind Plants October 1, 2013 - 3:28pm Addthis...
New DOE Modeling Tool Estimates Economic Benefits of Offshore...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
Modeling Tool Estimates Economic Benefits of Offshore Wind Plants New DOE Modeling Tool Estimates Economic Benefits of Offshore Wind Plants October 1, 2013 - 3:28pm Addthis To help...
Estimating Wireless Network Properties with Spatial Statistics and Models
Paris-Sud XI, Université de
Estimating Wireless Network Properties with Spatial Statistics and Models Janne Riihij statistics and models for different estimation problems related to wireless networks. We focus specifically wireless networks. We provide a concise survey of existing techniques from the spatial statistics
Visual geo-localization of non-photographic depictions via 2D-3D alignment
and Josef Sivic Fig. 1 Our system automatically geo-localizes paintings, drawings, and historical, paintings and historical pho- tographs. This is achieved by aligning the input depiction with a 3D model of several scenes are represented by a set of discrim- inative visual elements that are automatically learnt
Dynamic Bayesian Networks model to estimate process availability.
Paris-Sud XI, Université de
Dynamic Bayesian Networks model to estimate process availability. Weber P. Centre de Recherche en reported here explores a new methodology to develop Dynamic Bayesian Network-based Availability of the system availability estimation comparing DBN model with the classical Markov chain model. Keywords
Noisy Independent Factor Analysis Model for Density Estimation and Classification
Amato, U.
2009-06-09T23:59:59.000Z
We consider the problem of multivariate density estimation when the unknown density is assumed to follow a particular form of dimensionality reduction, a noisy independent factor analysis (IFA) model. In this model the ...
ACCURATE MODELS FOR ESTIMATING AREA AND POWER OF FPGA IMPLEMENTATIONS
Kambhampati, Subbarao
-circuit power and leak- age power. Models for large parametrized IP cores have been pre- sented in [6], [7]; [6] presents area models and detailed power model for fast Hadamard transform, and [7] presents area modelsACCURATE MODELS FOR ESTIMATING AREA AND POWER OF FPGA IMPLEMENTATIONS Lanping Deng, Kanwaldeep
Estimation of Parameters in Carbon Sequestration Models from Net Ecosystem
White, Luther
Estimation of Parameters in Carbon Sequestration Models from Net Ecosystem Exchange Data Luther in the context of a deterministic com- partmental carbon sequestration system. Sensitivity and approximation usefulness in the estimation of parameters within a compartmental carbon sequestration model. Previously we
Pilot Models for Estimating Bicycle Intersection Volumes
Griswold, Julia B.; Medury, Aditya; Schneider, Robert J.
2011-01-01T23:59:59.000Z
and Table 4. Alternative Bicycle Model Specifications Model= 2-hr Intersection Bicycle Count Constant NComPropT BikeSymof Portland, OR. Portland Bicycle Counts 2008. Available
Stochastic Wireless Channel Modeling, Estimation and Identification from Measurements
Olama, Mohammed M [ORNL; Djouadi, Seddik M [ORNL; Li, Yanyan [ORNL
2008-07-01T23:59:59.000Z
This paper is concerned with stochastic modeling of wireless fading channels, parameter estimation, and system identification from measurement data. Wireless channels are represented by stochastic state-space form, whose parameters and state variables are estimated using the expectation maximization algorithm and Kalman filtering, respectively. The latter are carried out solely from received signal measurements. These algorithms estimate the channel inphase and quadrature components and identify the channel parameters recursively. The proposed algorithm is tested using measurement data, and the results are presented.
Battery Calendar Life Estimator Manual Modeling and Simulation
Jon P. Christophersen; Ira Bloom; Ed Thomas; Vince Battaglia
2012-10-01T23:59:59.000Z
The Battery Life Estimator (BLE) Manual has been prepared to assist developers in their efforts to estimate the calendar life of advanced batteries for automotive applications. Testing requirements and procedures are defined by the various manuals previously published under the United States Advanced Battery Consortium (USABC). The purpose of this manual is to describe and standardize a method for estimating calendar life based on statistical models and degradation data acquired from typical USABC battery testing.
The Art and Science of Depiction Fredo Durand
Durand, Frédo
· Computational theory of vision · Invariants #12;Picture Organization & Gestalt 3 Overview · After image theory in physics · Holistic philosophy of vision "spontaneous" organization Opposed to unconsciousThe Art and Science of Depiction Fredo Durand MIT- Lab for Computer Science Picture Organization
The Art and Science of Depiction Fredo Durand
Durand, Frédo
· Grass Greener · Sky Bluer #12;5 Color Vision 25 Plan · Color blindness · Color Opponents, Hue luminance #12;6 Color Vision 31 Blue-yellow opponent and painting · Often used to depict night · (S cones stage may reparameterize: Brightness or Luminance or Value Hue Saturation Color Vision 35 Hue
The Art and Science of Depiction Fredo Durand
Durand, Frédo
differences #12;Color Vision 24 Preferred colors · Caucasian skin More tanned · Grass Greener · Sky more than luminance #12;Color Vision 31 Blue-yellow opponent and painting · Often used to depict night-dark Blue-yellow Red-green · A later stage may reparameterize: Brightness or Luminance or Value Hue
ESTIMATING CONSUMER BEHAVIOUR IN AN ENERGY-ECONOMY POLICY MODEL
furnace emissions to 2050. Despite insufficient variation in energy prices over the historical periodESTIMATING CONSUMER BEHAVIOUR IN AN ENERGY-ECONOMY POLICY MODEL by Dale Beugin B.A.Sc., University Degree: Master of Resource Management Title of Thesis: Estimating Consumer Behaviour in an Energy
Estimating Emissions in Latin America: An Alternative to Traffic Models
Richner, Heinz
Estimating Emissions in Latin America: An Alternative to Traffic Models Margarita Ossés de Eicker; Hans Hurni, Centre for Development and Environment (CDE), University of Bern, Switzerland Emissions allow precise estimations of these emissions but are too expensive for a broad application. A simplifed
Ridge Regression Estimation Approach to Measurement Error Model
Shalabh
Ridge Regression Estimation Approach to Measurement Error Model A.K.Md. Ehsanes Saleh Carleton of the regression parameters is ill conditioned. We consider the Hoerl and Kennard type (1970) ridge regression (RR) modifications of the five quasi- empirical Bayes estimators of the regression parameters of a measurement error
Panel data models with nonadditive unobserved heterogeneity : estimation and inference
Lee, Joonhwan
2014-01-01T23:59:59.000Z
This paper considers fixed effects estimation and inference in linear and nonlinear panel data models with random coefficients and endogenous regressors. The quantities of interest - means, variances, and other moments of ...
Efficient Estimation in a Regression Model with Missing Responses
Crawford, Scott
2012-10-19T23:59:59.000Z
This article examines methods to efficiently estimate the mean response in a linear model with an unknown error distribution under the assumption that the responses are missing at random. We show how the asymptotic variance is affected...
Estimation of Random-Coefficient Demand Models: Two Empiricists' Perspective
Metaxoglou, Konstantinos
We document the numerical challenges we experienced estimating random-coefficient demand models as in Berry, Levinsohn, and Pakes (1995) using two well-known data sets and a thorough optimization design. The optimization ...
A categorical model for traffic incident likelihood estimation
Kuchangi, Shamanth
2007-04-25T23:59:59.000Z
that the model distinguished different levels of crash rate for different precursor values and hence could be a useful tool in estimating the likelihood of incidents for real-time freeway incident management systems....
Root Modeling: Estimating Storage, Live, and Dead Pool
Post, Wilfred M.
Root Modeling: Estimating Storage, Live, and Dead Pool Turnover Times; Storage Inputs to New Root to choose best-fit parameters · "Storage" simulations with in-growth cores · Live and dead pool simulations Atmosphere East Atmosphere; 1 SD East tree rings f(Average respiration and soil gas) Modeled GSD = 1.3 Range
An evaluation of risk simulation models for reserve estimates
Judah, Janeen Sue
1983-01-01T23:59:59.000Z
1983 Major Subject: Petroleum Engineering AN EVALUATION OF RISK SIMULATION MODELS FOR RESERVE ESTIMATES A Thesis by JANEEN SUE JUDAH A pproved as to style and content by: (Chairman of Committee) Richard A. tartzman (Member) eund ( mber) o 9... in estimating reserves for petroleum economic evaluations is an 1mportant everyday problem encountered by practicing petroleum engineers. This study addresses the problem of est1mating reserves for petroleum evaluations with little available data. The risk...
Combined Estimation of Hydrogeologic Conceptual Model and Parameter Uncertainty
Meyer, Philip D.; Ye, Ming; Neuman, Shlomo P.; Cantrell, Kirk J.
2004-03-01T23:59:59.000Z
The objective of the research described in this report is the development and application of a methodology for comprehensively assessing the hydrogeologic uncertainties involved in dose assessment, including uncertainties associated with conceptual models, parameters, and scenarios. This report describes and applies a statistical method to quantitatively estimate the combined uncertainty in model predictions arising from conceptual model and parameter uncertainties. The method relies on model averaging to combine the predictions of a set of alternative models. Implementation is driven by the available data. When there is minimal site-specific data the method can be carried out with prior parameter estimates based on generic data and subjective prior model probabilities. For sites with observations of system behavior (and optionally data characterizing model parameters), the method uses model calibration to update the prior parameter estimates and model probabilities based on the correspondence between model predictions and site observations. The set of model alternatives can contain both simplified and complex models, with the requirement that all models be based on the same set of data. The method was applied to the geostatistical modeling of air permeability at a fractured rock site. Seven alternative variogram models of log air permeability were considered to represent data from single-hole pneumatic injection tests in six boreholes at the site. Unbiased maximum likelihood estimates of variogram and drift parameters were obtained for each model. Standard information criteria provided an ambiguous ranking of the models, which would not justify selecting one of them and discarding all others as is commonly done in practice. Instead, some of the models were eliminated based on their negligibly small updated probabilities and the rest were used to project the measured log permeabilities by kriging onto a rock volume containing the six boreholes. These four projections, and associated kriging variances, were averaged using the posterior model probabilities as weights. Finally, cross-validation was conducted by eliminating from consideration all data from one borehole at a time, repeating the above process, and comparing the predictive capability of the model-averaged result with that of each individual model. Using two quantitative measures of comparison, the model-averaged result was superior to any individual geostatistical model of log permeability considered.
Locatelli, R.
A modelling experiment has been conceived to assess the impact of transport model errors on methane emissions estimated in an atmospheric inversion system. Synthetic methane observations, obtained from 10 different model ...
Assessment of model estimates of land-atmosphere CO2 exchange across Northern Eurasia
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
Rawlins, M. A.; McGuire, A. D.; Kimball, J. S.; Dass, P.; Lawrence, D.; Burke, E.; Chen, X.; Delire, C.; Koven, C.; MacDougall, A.; et al
2015-07-28T23:59:59.000Z
A warming climate is altering land-atmosphere exchanges of carbon, with a potential for increased vegetation productivity as well as the mobilization of permafrost soil carbon stores. Here we investigate land-atmosphere carbon dioxide (CO2) cycling through analysis of net ecosystem productivity (NEP) and its component fluxes of gross primary productivity (GPP) and ecosystem respiration (ER) and soil carbon residence time, simulated by a set of land surface models (LSMs) over a region spanning the drainage basin of Northern Eurasia. The retrospective simulations cover the period 1960–2009 at 0.5° resolution, which is a scale common among many global carbon and climate modelmore »simulations. Model performance benchmarks were drawn from comparisons against both observed CO2 fluxes derived from site-based eddy covariance measurements as well as regional-scale GPP estimates based on satellite remote-sensing data. The site-based comparisons depict a tendency for overestimates in GPP and ER for several of the models, particularly at the two sites to the south. For several models the spatial pattern in GPP explains less than half the variance in the MODIS MOD17 GPP product. Across the models NEP increases by as little as 0.01 to as much as 0.79 g C m?² yr?², equivalent to 3 to 340 % of the respective model means, over the analysis period. For the multimodel average the increase is 135 % of the mean from the first to last 10 years of record (1960–1969 vs. 2000–2009), with a weakening CO2 sink over the latter decades. Vegetation net primary productivity increased by 8 to 30 % from the first to last 10 years, contributing to soil carbon storage gains. The range in regional mean NEP among the group is twice the multimodel mean, indicative of the uncertainty in CO2 sink strength. The models simulate that inputs to the soil carbon pool exceeded losses, resulting in a net soil carbon gain amid a decrease in residence time. Our analysis points to improvements in model elements controlling vegetation productivity and soil respiration as being needed for reducing uncertainty in land-atmosphere CO2 exchange. These advances will require collection of new field data on vegetation and soil dynamics, the development of benchmarking data sets from measurements and remote-sensing observations, and investments in future model development and intercomparison studies.« less
PARAMETRIC MODELS FOR ESTIMATING WIND TURBINE FATIGUE LOADS FOR DESIGN
Sweetman, Bert
1 PARAMETRIC MODELS FOR ESTIMATING WIND TURBINE FATIGUE LOADS FOR DESIGN Lance Manuel1 Paul S-4020 ABSTRACT International standards for wind turbine certification depend on finding long-term fatigue load-bending data from a commercial turbine in complex terrain. Distributions of rainflow-counted range data
Hybrid Simulation Modeling to Estimate U.S. Energy Elasticities
-data' based on a series of simulations in which I vary energy and capital input prices over a wide range. I to calculate price- independent changes in energy-efficiency in the form of the AEEI, by comparing energyHybrid Simulation Modeling to Estimate U.S. Energy Elasticities by Adam C. Baylin-Stern B.A. & Sc
Spectral jitter modeling and estimation Miltiadis Vasilakis a,b,
Stylianou, Yannis
Spectral jitter modeling and estimation Miltiadis Vasilakis a,b, *, Yannis Stylianou a modulation is referred to as jitter. During sustained vowel phonation, both modulations can be defined amplitude and the glottal pitch period, for shimmer and jitter, respectively.1 Since an unperturbed quasi
AIAA-2001-0047 PARAMETRIC MODELS FOR ESTIMATING WIND TURBINE
Sweetman, Bert
AIAA-2001-0047 1 PARAMETRIC MODELS FOR ESTIMATING WIND TURBINE FATIGUE LOADS FOR DESIGN Lance 94305-4020 ABSTRACT International standards for wind turbine certification depend on finding long. INTRODUCTION Design constraints for wind turbine structures fall into either extreme load or fatigue categories
AIAA-2001-0047 PARAMETRIC MODELS FOR ESTIMATING WIND
AIAA-2001-0047 PARAMETRIC MODELS FOR ESTIMATING WIND TURBINE FATIGUE LOADS FOR DESIGN Lance Manuel Laboratories Wind Energy Technology Department Albuquerque, NM 87185-0708 Steven R. Winterstein Department standards for wind turbine certification depend on finding long-term fatigue load distributions
Emulating maize yields from global gridded crop models using statistical estimates
Blanc, E.
This study estimates statistical models emulating maize yield responses to changes in temperature and
Model Year 2005 Fuel Economy Guide: EPA Fuel Economy Estimates
None
2004-11-01T23:59:59.000Z
The Fuel Economy Guide is published by the U.S. Department of Energy as an aid to consumers considering the purchase of a new vehicle. The Guide lists estimates of miles per gallon (mpg) for each vehicle available for the new model year. These estimates are provided by the U.S. Environmental Protection Agency in compliance with Federal Law. By using this Guide, consumers can estimate the average yearly fuel cost for any vehicle. The Guide is intended to help consumers compare the fuel economy of similarly sized cars, light duty trucks and special purpose vehicles. The vehicles listed have been divided into three classes of cars, three classes of light duty trucks, and three classes of special purpose vehicles.
Model Reduction and Parameter Estimation in Groundwater Modeling
Siade, Adam
2012-01-01T23:59:59.000Z
Uncon?ned Groundwater Model Reduction via Proper Orthogonalvi List of Figures One-dimensional groundwater ?owQuadratic Programming 3.1 Con?ned aquifer groundwater ?ow
Test models for improving filtering with model errors through stochastic parameter estimation
Gershgorin, B. [Department of Mathematics and Center for Atmosphere and Ocean Science, Courant Institute of Mathematical Sciences, New York University, NY 10012 (United States); Harlim, J. [Department of Mathematics, North Carolina State University, NC 27695 (United States)], E-mail: jharlim@ncsu.edu; Majda, A.J. [Department of Mathematics and Center for Atmosphere and Ocean Science, Courant Institute of Mathematical Sciences, New York University, NY 10012 (United States)
2010-01-01T23:59:59.000Z
The filtering skill for turbulent signals from nature is often limited by model errors created by utilizing an imperfect model for filtering. Updating the parameters in the imperfect model through stochastic parameter estimation is one way to increase filtering skill and model performance. Here a suite of stringent test models for filtering with stochastic parameter estimation is developed based on the Stochastic Parameterization Extended Kalman Filter (SPEKF). These new SPEKF-algorithms systematically correct both multiplicative and additive biases and involve exact formulas for propagating the mean and covariance including the parameters in the test model. A comprehensive study is presented of robust parameter regimes for increasing filtering skill through stochastic parameter estimation for turbulent signals as the observation time and observation noise are varied and even when the forcing is incorrectly specified. The results here provide useful guidelines for filtering turbulent signals in more complex systems with significant model errors.
Asymptotics for the maximum likelihood estimators of diffusion models
Jeong, Minsoo
2009-05-15T23:59:59.000Z
: : : : : : 24 3 First Order Distribution and the Histogram of t(^fi2) { CEV : : : : : 25 4 First Order Distributions of t(^fi1) and t(^fi2) : : : : : : : : : : : : : : 33 1 CHAPTER I INTRODUCTION The difiusion model was originally designed and has long been used... of the estimator. Wooldridge (1994) shows that AD3 together with AD1 and AD2 implies1 AD4: S(^ ) = 0 with probability approaching to one as T !1 and ? ! 0. AD5: w?1?H(~ )?H( 0)?w?10= op(1) and w0(^ ? 0) = Op(1). Thus, with these conditions, we have w?1S(^ ) = w?1S...
Estimation of landfill emission lifespan using process oriented modeling
Ustohalova, Veronika [Institute of Waste Management, University of Duisburg-Essen, Universitaetsstrasse 15, 45141 Essen (Germany)]. E-mail: veronika.ustohalova@uni-essen.de; Ricken, Tim [Institute of Mechanics, University of Duisburg-Essen, Universitaetsstrasse 15, 45141 Essen (Germany); Widmann, Renatus [Institute of Waste Management, University of Duisburg-Essen, Universitaetsstrasse 15, 45141 Essen (Germany)
2006-07-01T23:59:59.000Z
Depending on the particular pollutants emitted, landfills may require service activities lasting from hundreds to thousands of years. Flexible tools allowing long-term predictions of emissions are of key importance to determine the nature and expected duration of maintenance and post-closure activities. A highly capable option represents predictions based on models and verified by experiments that are fast, flexible and allow for the comparison of various possible operation scenarios in order to find the most appropriate one. The intention of the presented work was to develop a experimentally verified multi-dimensional predictive model capable of quantifying and estimating processes taking place in landfill sites where coupled process description allows precise time and space resolution. This constitutive 2-dimensional model is based on the macromechanical theory of porous media (TPM) for a saturated thermo-elastic porous body. The model was used to simulate simultaneously occurring processes: organic phase transition, gas emissions, heat transport, and settlement behavior on a long time scale for municipal solid waste deposited in a landfill. The relationships between the properties (composition, pore structure) of a landfill and the conversion and multi-phase transport phenomena inside it were experimentally determined. In this paper, we present both the theoretical background of the model and the results of the simulations at one single point as well as in a vertical landfill cross section.
Adaptive Density Estimation in the Pile-up Model Involving Measurement Errors
Paris-Sud XI, Université de
Adaptive Density Estimation in the Pile-up Model Involving Measurement Errors Fabienne Comte, Tabea of nonparametric density estimation in the pile-up model. Adaptive nonparametric estimators are proposed for the pile-up model in its simple form as well as in the case of additional measurement errors. Furthermore
Lo, Min-Hui; Famiglietti, James S; Yeh, P. J.-F.; Syed, T. H
2010-01-01T23:59:59.000Z
model using GRACE water storage and estimated base flow data,model using GRACE water storage and estimated base flow datawith esti- mated base flow data in the model calibration.
Multi-rate Modeling, Model Inference, and Estimation for Statistical Classifiers
Washington at Seattle, University of
Multi-rate Modeling, Model Inference, and Estimation for Statistical Classifiers ¨Ozg¨ur C University of Washington 2004 Program Authorized to Offer Degree: Electrical Engineering #12;#12;University: Mari Ostendorf Reading Committee: Mari Ostendorf Jeffrey A. Bilmes Maya R. Gupta Date: #12;#12;In
Nonparametric estimation of varying coefficient dynamic panel models
Cai, Zongwu; Li, Qi
2008-10-01T23:59:59.000Z
#2; m2 because the number of parameters in ~6! is m2+ However, when m1 #7; m2, the model is overidentified, and there may not exist a unique a to satisfy ~6!+ To obtain a unique a satisfy- ing ~6!, we premultiply ~6! by an m2 #3; m1 matrix Sn' , where... with Qit #1; Q~Vit ! and n #1; NT, Sn #1; 1 n #6; i#1;1 N #6; t#1;1 T QitUit' Kh~Zit #5; z!+ Then solving for a we obtain [a #1; ~Sn' Sn !#5;1Sn' Tn , (7) where Tn #1; 1 n #6; i#1;1 N #6; t#1;1 T Qit Kh~Zit #5; z!Yit + The estimator [a defined in ~7...
Mass Flow Estimation with Model Bias Correction for a Turbocharged Diesel Engine
Johansen, Tor Arne
Mass Flow Estimation with Model Bias Correction for a Turbocharged Diesel Engine Tomás Polóni. Based on an augmented observable Mean Value En- gine Model (MVEM) of a turbocharged Diesel engine in the intake duct. Keywords: Diesel engine, Mass flow estimation, Bias estimation, Kalman filtering, Mean value
Sun, Jian
[1] We use a conditional averaging approach to estimate the parameters of a land surface water and energy balance model and then use the estimated parameters to partition net radiation into latent, sensible, and ground ...
Estimating market power in homogeneous product markets using a composed error model
Orea, Luis; Steinbuks, Jevgenijs
2012-04-25T23:59:59.000Z
This study contributes to the literature on estimating market power in homogenous product markets. We estimate a composed error model, where the stochastic part of the firm?s pricing equation is formed by two random variables...
On the empirical statistics of parameter estimates in parametric modeling
Zhu, Yao
1988-01-01T23:59:59.000Z
. The PARCOR parametrization has received considerable attention because of its attractive features. One of these features shows that the magnitudes of the k?'s obtained from the autocorrelation method are guaranteed to be less than one (6]. 10 2. 1. 2... are asymptotically unbiased estimates with covsriance matrix CA, because A are the maximum likelihood estimates. Similarly, the asymptotic probability density function of the PARCOR coeffi- cient estimates K = (kq, ks, ~ ~ ~, k&) is Gaussian and given by f(K...
Modeling, Estimation, and Control of Waste Heat Recovery Systems
Luong, David
2013-01-01T23:59:59.000Z
State Estimation for Open Organic Rankine Cycle (ORC)138optimization of an organic Rankine cycle waste heat powerand Simulation of an Organic Rankine Cycle (ORC) System for
Model Test Setup and Program for Experimental Estimation of Surface Loads of the SSG Kvitsy
Model Test Setup and Program for Experimental Estimation of Surface Loads of the SSG Kvitsøy Pilot Engineering No. 32 ISSN: 1603-9874 Model Test Setup and Program for Experimental Estimation of Surface Loads University October, 2005 #12;#12;Preface This report presents the preparations done prior to model tests
Chauhan, Sanjay S.
of dam failure for use in Dam Safety Risk Assessments. For the emergency preparedness applications inundation characteristics. The scale of estimated consequences associated with dam failure, and especially making up the dam, and the reservoir head and volume at the time of failure. Defining breach parameters
Gruben, David Christopher
1987-01-01T23:59:59.000Z
MODEL A Thesis by DAVID CHRISTOPHER GRUBEN Approved as to style and content by: P. Fred Dahm (Chair of Committee) Thomas E. Wehrly (Member) Roy F. Gilbert (Member) ge (Interim Head of Department) August 1987 ABSTRACT Development of a.... Small sample properties of the three estimators will be examined. Key Words: measurement error, structural model, maximum likelihood, in- strumental variable, consistent, asymptotic variance. DEDICATION To my parents, James and Theresa Gruben...
A Comparative Study of Estimation Models for Satellite Relative Motion
Desai, Uri
2013-01-31T23:59:59.000Z
The problem of relative spacecraft motion estimation is considered with application to various reference and relative orbits. Mean circular and elliptic orbits are analyzed, with relative orbits ranging in size from 1 km ...
Estimation of system reliability using a semiparametric model
Wu, Leon
An important problem in reliability engineering is to predict the failure rate, that is, the frequency with which an engineered system or component fails. This paper presents a new method of estimating failure rate using ...
Modeling, estimation, and control of robot-soil interactions
Hong, Won, 1971-
2001-01-01T23:59:59.000Z
This thesis presents the development of hardware, theory, and experimental methods to enable a robotic manipulator arm to interact with soils and estimate soil properties from interaction forces. Unlike the majority of ...
A quantitative framework For large-scale model estimation and discrimination In systems biology
Eydgahi, Hoda
2013-01-01T23:59:59.000Z
Using models to simulate and analyze biological networks requires principled approaches to parameter estimation and model discrimination. We use Bayesian and Monte Carlo methods to recover the full probability distributions ...
Online Center of Gravity Estimation in Automotive Vehicles using Multiple Models and Switching
Duffy, Ken
Online Center of Gravity Estimation in Automotive Vehicles using Multiple Models and Switching and switching for realtime estimation of center of gravity (CG) position in automotive vehicles. The method utilizes simple linear vehicle models and assumes availability of standard stock automotive sensors. We
sensitivity estimate using Bayesian fusion of instrumental observations and an Earth System model, J. Geophys System model Roman Olson,1 Ryan Sriver,1 Marlos Goes,2,3 Nathan M. Urban,4,5 H. Damon Matthews,6 MuraliA climate sensitivity estimate using Bayesian fusion of instrumental observations and an Earth
Hierarchical models for estimating state and demographic trends in U.S. death penalty public opinion
Gelman, Andrew
Hierarchical models for estimating state and demographic trends in U.S. death penalty public?" Because the death penalty is governed by state laws rather than federal laws, it is of special interest logistic regression model to estimate support for the death penalty as a function of the year, the state
Run-time Modeling and Estimation of Operating System Power Consumption
John, Lizy Kurian
Run-time Modeling and Estimation of Operating System Power Consumption Tao Li Department computing systems point to the need for power modeling and estimation for all components of a system software power evaluation, as well as power management (e.g. dynamic thermal control and equal energy
Venditti, Jeremy G.
Estimating suspended sediment concentrations in areas with limited hydrological data using a mixed-effects. In this study, we used a mixed-effects linear model to estimate an average SSCQ relation for different periods the performance of the mixed-effects model against the standard rating curve, represented by a generalized least
Data-driven Techniques to Estimate Parameters in the Homogenized Energy Model for Shape Memory. In this paper, we focus on the homogenized energy model for shape memory alloys (SMA). Specifically, we develop parameters are compared to the initial estimates. 1 Introduction Shape memory alloys (SMA) are novel
Bilinear estimation of pollution source profiles in receptor models
Washington at Seattle, University of
the pollution sources based on air pollution data. This article is concerned with estimation of the source and assess the contribution of each source based on this data. There have been two traditional approaches. Los Angeles, CA 90089-2531 + Address for correspondence: NRCSE, University of Washington, Box 351720
The Lithium-Ion Cell: Model, State Of Charge Estimation
Schenato, Luca
. Di Domenico, A. Stefanopoulou, and G. Fiengo., Reduced Order Lithium-ion Battery Electrochemical+ontestresultsIncreasingamplitudeHPPCprofiles #12;LithiumionbaEery:ExtendedKalmanFilter cs cse I V Lithium-ion battery EKF. Stefanopoulou, and G. Fiengo., Experimental Validation of a Lithium-Ion Battery State of Charge Estimation
Wavelet Based Density Estimators for Modeling Multidimensional Data Sets
Shahabi, Cyrus
the distribution of this random variable. We exhibit an estimator for the wavelet coeÃ?cients of this density and ionospheric data. After three levels of o#11;-line pre-processing, observations of temperature, water vapor agreement nr. F30602-99-1-0524, and unrestricted cash/equipment gifts from NCR, IBM, Intel and SUN. #12; 1
Plan-view Trajectory Estimation with Dense Stereo Background Models
Darrell, T.
2001-02-01T23:59:59.000Z
In a known environment, objects may be tracked in multiple views using a set of back-ground models. Stereo-based models can be illumination-invariant, but often have undefined values which inevitably lead to foreground ...
Modeling, Estimation, and Control of Waste Heat Recovery Systems
Luong, David
2013-01-01T23:59:59.000Z
presented along with a centrifugal pump model. General ModelCentrifugal pumps are comprised of hydraulic and mechanicalK is the pump constant, and ? is the pump speed. Centrifugal
Richardson, John G. (Idaho Falls, ID)
2009-11-17T23:59:59.000Z
An impedance estimation method includes measuring three or more impedances of an object having a periphery using three or more probes coupled to the periphery. The three or more impedance measurements are made at a first frequency. Three or more additional impedance measurements of the object are made using the three or more probes. The three or more additional impedance measurements are made at a second frequency different from the first frequency. An impedance of the object at a point within the periphery is estimated based on the impedance measurements and the additional impedance measurements.
Modeling, Estimation, and Control of Waste Heat Recovery Systems
Luong, David
2013-01-01T23:59:59.000Z
Steam Turbine . . . . . .and A. Ghaffari. “Steam Turbine Model. ” SimulationTurbine Blade Damage from Wet Steam (Source: PTG Advisers,
A model for estimating the potential of flexible carpool matching
Ringrose, Michael R
1992-01-01T23:59:59.000Z
Savings Destination Site Area. . . . . Idle Time per Passenger Average Detour Speed Detour Coefficient Automobile Use Factor . Participant Adjustment Factor 88 90 92 94 94 96 98 . . 100 Findings . . 102 Model Demonstration Comprehensive... response to changes in the line-haul HOV savings 18 Model response to changes in the destination site area 19 Model response to changes in the idle time per passenger 91 93 95 20 Model response to changes in the average detour speed 97 LIST...
Three Essays on Estimation and Testing of Nonparametric Models
Ma, Guangyi
2012-10-19T23:59:59.000Z
| , then the local quadratic estimator for (m0 (x) ;m1 (x) ;m2 (x)) | can be written as b (x) = b 0 (x) ; b 1 (x) ; b 2 (x) | ; 8 where for j = 0; 1; 2, b j (x) = 1 hj 1 n Xn i=1 Wji (x)Yi 1 n Xn i=1 W0i (x) ; and the corresponding weights...) Xi x h s21 s0s2 Xi x h 2 # Ki; where sj = 1 nh Xn i=1 Xi x h j Ki for j = 0; 1; 2; 3; 4: 2.2.2 EL for the Local Quadratic Estimating Equations In this subsection we construct the empirical likelihood formulation...
Estimating sandstone permeability using network models with pore size distributions
Mathews, Alan Ronald
1991-01-01T23:59:59.000Z
the effects of each parameter on the response of the network lattice. A FoR+RAv source code was written to generate and analyze the response of the network model (see Appendix G for source code description and flow chart). The controlling parameters used... in appearance to empirical data. A network model is developed to simulate the pore geometry of a clean, well-sorted sandstone. Pores were modeled as straight capillaries connected in various lattice configurations. Complex lattice configurations produce more...
Modeling, Estimation, and Control of Waste Heat Recovery Systems
Luong, David
2013-01-01T23:59:59.000Z
Steam Turbine . . . . . .and A. Ghaffari. “Steam Turbine Model. ” Simulation= m ? v (h in ? h out ) Steam Turbine As with the pump, the
General model selection estimation of a periodic regression with a Gaussian noise
Konev, Victor; 10.1007/s10463-008-0193-1
2010-01-01T23:59:59.000Z
This paper considers the problem of estimating a periodic function in a continuous time regression model with an additive stationary gaussian noise having unknown correlation function. A general model selection procedure on the basis of arbitrary projective estimates, which does not need the knowledge of the noise correlation function, is proposed. A non-asymptotic upper bound for quadratic risk (oracle inequality) has been derived under mild conditions on the noise. For the Ornstein-Uhlenbeck noise the risk upper bound is shown to be uniform in the nuisance parameter. In the case of gaussian white noise the constructed procedure has some advantages as compared with the procedure based on the least squares estimates (LSE). The asymptotic minimaxity of the estimates has been proved. The proposed model selection scheme is extended also to the estimation problem based on the discrete data applicably to the situation when high frequency sampling can not be provided.
Model selection and estimation of a component in additive regression
Paris-Sud XI, Université de
on s and is based on non-asymptotic model selection methods. Given some linear spaces collection {Sm, m M}, we proposed and, among them, a widely used is the linear regression Z = µ + k i=1 iX(i) + (2) where µ;drawback of linear regression is its lack of flexibility for modeling more complex dependencies between Z
Numerically Estimating Internal Models of Dynamic Virtual Objects
Sekuler, Robert
human subjects to manipulate a computer-animated virtual object. This virtual object (vO) was a high, human cognition, human information processing, ideal performer, internal model, virtual object, virtual, specifically how humans acquire an internal model of a dynamic virtual object. Our methodology minimizes
INVENTORY OF SOLAR RADIATION/SOLAR ENERGY SYSTEMS ESTIMATORS, MODELS, SITE-SPECIFIC DATA, and Buildings Systems Integration Center National Renewable Energy Laboratory 8 July 2009 SOLAR SYSTEM POTENTIAL/calculators/PVWATTS/version1/ http://rredc.nrel.gov/solar/calculators/PVWATTS/version2/ Estimates the electrical energy
Logistic Regression and Bayesian Model Selection in Estimation of Probability of Success
Shemyakin, Arkady
1 1 Logistic Regression and Bayesian Model Selection in Estimation of Probability of Success Arkady ABSTRACT Logistic regression and linear discriminant analysis are used to estimate probability of success X is analyzed as an explanatory variable. A comparison is made between logistic regression technique
A NEW APPROACH FOR ESTIMATING ENTRAINMENT RATE IN CUMULUS AND PARAMETERIZATION IN MODELS
A NEW APPROACH FOR ESTIMATING ENTRAINMENT RATE IN CUMULUS AND PARAMETERIZATION IN MODELS Chunsong Entrainment of dry air into clouds is essential to many cloud processes, affecting cloud microphysical for estimating fractional entrainment rate in cumulus clouds from aircraft observations. This approach is based
A Performance Model to Estimate Execution Time of Scientific Workflows on the Cloud
Sakellariou, Rizos
. In the evaluation, three real-world scientific workflows are used to compare the estimated makespan calculatedA Performance Model to Estimate Execution Time of Scientific Workflows on the Cloud Ilia Pietri.K Information Sciences Institute, University of Southern California, USA Abstract--Scientific workflows, which
Flood control of rivers with nonlinear model predictive control and moving horizon estimation
Flood control of rivers with nonlinear model predictive control and moving horizon estimation control (MPC) in combination with moving horizon estimation (MHE) can more effectively be used for flood into account, it uses the buffer capacity of the available flood basins in a more optimal way. Simulation
ON THE MODELING AND ESTIMATION OF NONLINEAR INSTANTANEOUS FREQUENCY
Paris-Sud XI, Université de
and voltage, and a thermal model, which outputs are the stator and rotor temperatures. The parameter slight variations of high fre- quency resonances in the winding of a working machine fed by an industrial
Logit Models for Estimating Urban Area Through Travel
Talbot, Eric
2011-10-21T23:59:59.000Z
the greatest data collection efforts. All three of the models performed reasonably well for external stations with high traffic volumes, but performed erratically for external stations with low traffic volumes (Chatterjee and Raja 1989). Reeder tested...
Modeling, Estimation, and Control of Waste Heat Recovery Systems
Luong, David
2013-01-01T23:59:59.000Z
Kan08] for flow through vertical and horizontal tubes. TheFlow Boiling Heat Transfer Inside Horizontal and Vertical Tubes. ”and thin horizontal tube. 2. Working fluid flow modeled as a
Statistical testing and estimation in continuous time interest rate models
Kim, Myung Suk
2006-10-30T23:59:59.000Z
The shape of drift function in continuous time interest rate models has been investigated by many authors during the past decade. The main concerns have been whether the drift function is linear or nonlinear, but no convincing conclusions have been...
Hybrid Model of Existing Buildings for Transient Thermal Performance Estimation
Xu, X.; Wang, S.
2006-01-01T23:59:59.000Z
Building level energy models are important to provide accurate prediction of energy consumption for building performance diagnosis and energy efficiency assessment of retrofitting alternatives for building performance upgrading. Simplified...
Estimations of baryon asymmetry for different neutrino mass models
Amal Kr. Sarma; Hijam Zeen Devi; N. Nimai Singh
2006-04-05T23:59:59.000Z
We present a comparison of the numerical prediction on baryon asymmetry of the Universe in different neutrino mass models. We start with a very brief review on the main formalism of baryogenesis via leptogenesis through decay of heavy right-handed Majorana neutrinos, and then calculate the baryon asymmetry of the universe for known six neutrino mass models viz., three quasi-degenerate, two inverted and one normal hierarchical models, which are derived from canonical seesaw formula. The corresponding mass matrices for the right-handed Majorana neutrino as well as the Dirac neutrino, which are fixed at the seesaw stage for generating correct light neutrino mass matrices, are again employed in the calculation of baryogenesis. This procedure removes possible ambiguity on the choices of Dirac neutrino and right-handed Majorana mass matrices, and fixes input parameters at the seesaw stage. We find that the ranges of predictions from both normal hierarchical model and degenerate model (DegT1A) are almost consistent with the observed baryon asymmetry of the universe. Combining the present result with other predictions such as light neutrino masses and mixing angles, and stability under radiative corrections in MSSM, the normal hierarchical model appears to be the most favourable choice of nature.
A Model for Estimating Demand for Irrigation Water on the Texas High Plains
Condra, G. D.; Lacewell, R. D.; Sprott, J. M.; Adams, B. M.
1975-01-01T23:59:59.000Z
and soybeans. Inputs that can be evaluated include irrigation water, natural gas, diesel, nitrogen fertilizer and herbicides. The primary focus of this work was to estimate the demand for irrigation water in the study area. The model was applied using...
Faquih, Yaquta Fakhruddin
2010-10-12T23:59:59.000Z
Facility managers use various cost models and techniques to estimate the cost of renovating a building and to secure the required funds needed for building renovation. A literature search indicates that these techniques offer both advantages...
Weijo, R. O.; and Brown, D. R.
1988-01-01T23:59:59.000Z
This study estimated the market penetration for residential cool storage technology using economic cost modeling. Residential cool storage units produce and store chill during off-peak periods of the day to be used during times of peak electric...
Tabares Velasco, P. C.
2011-04-01T23:59:59.000Z
This presentation discusses estimating heat and mass transfer processes in green roof systems: current modeling capabilities and limitations. Green roofs are 'specialized roofing systems that support vegetation growth on rooftops.'
Impact of aerothermal modeling on the estimation of turbine blade life
Collin, Jean E., 1978-
2004-01-01T23:59:59.000Z
The impact of aerothermal modeling on estimates of turbine blade heat transfer and life was assessed for three high pressure turbine blades. The work was conducted as part of a project aimed at the evaluation of the effect ...
Griffith, Daniel Todd
2005-02-17T23:59:59.000Z
The main objective of this work is to demonstrate some new computational methods for estimation, optimization and modeling of dynamical systems that use automatic differentiation. Particular focus will be upon dynamical ...
Linear and NonLinear Estimation Methods Applied to the Hemodynamic model
Schaal, Stefan
Linear and NonLinear Estimation Methods Applied to the Hemodynamic model Evangelos A. Theodorou s that controls the blood inflow. The total balloon model can be defined by the 4 differential equations the hemodynamic process of the balloon model. These equations consist of a set of deterministic highly non
Estimating home energy decision parameters for a hybrid energyYeconomy policy model
Estimating home energy decision parameters for a hybrid energyYeconomy policy model Mark Jaccard, Canada E-mail: jaccard@sfu.ca Hybrid energyYeconomy models combine the advantages of a technologically parameters translate into the behavioral parameters of a hybrid model. We then simulate household energy
Bakhtiary, Esmaeel
2013-01-15T23:59:59.000Z
PROBABILISTIC SEISMIC DEMAND MODEL AND FRAGILITY ESTIMATES FOR SYMMETRIC RIGID BLOCKS SUBJECT TO ROCKING MOTIONS A Thesis by ESMAEEL BAKHTIARY Submitted to the Office of Graduate Studies of Texas A&M University in partial... Motion ........ 17 4. CONSTRUCTION OF THE PROBABILISTIC DEMAND MODEL ........................ 18 4.1 Virtual Experiments Using Computer Modeling ................................................... 18 4.2 Earthquake Selection...
Load estimation and control using learned dynamics models Georgios Petkos and Sethu Vijayakumar
Vijayakumar, Sethu
Load estimation and control using learned dynamics models Georgios Petkos and Sethu Vijayakumar with their robustness in light of imperfect, intermediate dynamic models. I. INTRODUCTION Adaptive control the learned dynamics for control. In Section IV, we see how from a set of learned models with known inertial
A model for pricing data bundles based on minimax risks for estimation of a location parameter
Robertson, Edward L.
A model for pricing data bundles based on minimax risks for estimation of a location parameter of progress on the fundamental conceptual issues of the mathematical modeling of data, increasingly attention to this line of work; in particular, we propose and analyze a model for the pricing of data when the value
Parameter Estimation and Capacity Fade Analysis of Lithium-Ion Batteries Using Reformulated Models
Parameter Estimation and Capacity Fade Analysis of Lithium-Ion Batteries Using Reformulated Models and characterize capacity fade in lithium-ion batteries. As a comple- ment to approaches to mathematically model been made in developing lithium-ion battery models that incor- porate transport phenomena
Abstract--Using a bioenergetics model, we estimated daily ration and
332 Abstract--Using a bioenergetics model, we estimated daily ration and seasonal prey consumption sandbar sharks (Carcharhinus plumbeus) in Chesapeake Bay, Virginia, using a bioenergetics model* W. Wesley used in error analyses of the sandbar shark (Carcharhinus plumbeus) bioenergetics model. See text
On the estimation of galaxy structural parameters: the Sersic Model
Ignacio Trujillo; Alister W. Graham; Nicola Caon
2001-02-22T23:59:59.000Z
This paper addresses some questions which have arisen from the use of the S\\'ersic r^{1/n} law in modelling the luminosity profiles of early type galaxies. The first issue deals with the trend between the half-light radius and the structural parameter n. We show that the correlation between these two parameters is not only real, but is a natural consequence from the previous relations found to exist between the model-independent parameters: total luminosity, effective radius and effective surface brightness. We also define a new galaxy concentration index which is largely independent of the image exposure depth, and monotonically related with n. The second question concerns the curious coincidence between the form of the Fundamental Plane and the coupling between _e and r_e when modelling a light profile. We explain, through a mathematical analysis of the S\\'ersic law, why the quantity r_e_e^{0.7} appears almost constant for an individual galaxy, regardless of the value of n (over a large range) adopted in the fit to the light profile. Consequently, Fundamental Planes of the form r_e_e^{0.7} propto sigma_0^x (for any x, and where sigma_0 is the central galaxy velocity dispersion) are insensitive to galaxy structure. Finally, we address the problematic issue of the use of model-dependent galaxy light profile parameters versus model-independent quantities for the half-light radii, mean surface brightness and total galaxy magnitude. The former implicitly assume that the light profile model can be extrapolated to infinity, while the latter quantities, in general, are derived from a signal-to-noise truncated profile. We quantify (mathematically) how these parameters change as one reduces the outer radius of an r^{1/n} profile, and reveal how these can vary substantially when n>4.
An analysis of tomb reliefs depicting boat construction from the Old Kingdom period in Egypt
Rogers, Edward Morgan
1996-01-01T23:59:59.000Z
Among the aspects of daily life represented on the walls of private tombs during the Old Kingdom in Egypt are reliefs depicting the construction of boat hulls. Examination of the twenty known reliefs and relief fragments which date to this period...
State Estimation for Force-Controlled Humanoid Balance using Simple Models in the Presence-based control frameworks, such as model predictive control (MPC), use the expected dynamics to generate that requires active balance control in the presence of modeling error. Primus humanoid shown in Figure 1
Modeling of PM Synchronous Motors for Control and Estimation Tasks
Stankoviæ, Aleksandar
- soidal stator winding and rotor magnet distribution and rotor saliency. Modeling is based on linear of the nonsinusoidal stator winding and rotor magnet distribution. Finally, Rabc = diagf Rs; Rs; Rsg and Labc are the stator resistance and inductance matrices. In the case of the most common stator winding distri- bution
Markov models and the ensemble Kalman filter for estimation of sorption rates.
Vugrin, Eric D.; McKenna, Sean Andrew (Sandia National Laboratories, Albuquerque, NM); Vugrin, Kay White
2007-09-01T23:59:59.000Z
Non-equilibrium sorption of contaminants in ground water systems is examined from the perspective of sorption rate estimation. A previously developed Markov transition probability model for solute transport is used in conjunction with a new conditional probability-based model of the sorption and desorption rates based on breakthrough curve data. Two models for prediction of spatially varying sorption and desorption rates along a one-dimensional streamline are developed. These models are a Markov model that utilizes conditional probabilities to determine the rates and an ensemble Kalman filter (EnKF) applied to the conditional probability method. Both approaches rely on a previously developed Markov-model of mass transfer, and both models assimilate the observed concentration data into the rate estimation at each observation time. Initial values of the rates are perturbed from the true values to form ensembles of rates and the ability of both estimation approaches to recover the true rates is examined over three different sets of perturbations. The models accurately estimate the rates when the mean of the perturbations are zero, the unbiased case. For the cases containing some bias, addition of the ensemble Kalman filter is shown to improve accuracy of the rate estimation by as much as an order of magnitude.
Experimental Validation of Stochastic Wireless Urban Channel Model: Estimation and Prediction
Kuruganti, Phani Teja [ORNL] [ORNL; Ma, Xiao [ORNL] [ORNL; Djouadi, Seddik M [ORNL] [ORNL
2012-01-01T23:59:59.000Z
Stochastic differential equations (SDE) can be used to describe the time-varying nature of wireless channels. This paper validates a long-term fading channel model for estimation and prediction from solely using measured received signal strength measurements. Such channel models can be used for optimizing wireless networks deployed for industrial automation, public access, and communication. This paper uses two different sets of received signal measurement data to estimate an predict the signal strength based on past measurements. The realworld performance of the estimation and prediction algorithm is demonstrated.
Evaluation of Clear Sky Models for Satellite-Based Irradiance Estimates
Sengupta, M.; Gotseff, P.
2013-12-01T23:59:59.000Z
This report describes an intercomparison of three popular broadband clear sky solar irradiance model results with measured data, as well as satellite-based model clear sky results compared to measured clear sky data. The authors conclude that one of the popular clear sky models (the Bird clear sky model developed by Richard Bird and Roland Hulstrom) could serve as a more accurate replacement for current satellite-model clear sky estimations. Additionally, the analysis of the model results with respect to model input parameters indicates that rather than climatological, annual, or monthly mean input data, higher-time-resolution input parameters improve the general clear sky model performance.
Coupling remote sensing with computational fluid dynamics modelling to estimate lake chlorophyll form 17 October 2000; accepted 1 June 2001 Abstract A remotely sensed image of Loch Leven, a shallow in the remotely sensed image. It is proposed that CFD modelling benefits the interpretation of remotely sensed
High and Low Temperature Series Estimates for the Critical Temperature of the 3D Ising Model
Adler, Joan
High and Low Temperature Series Estimates for the Critical Temperature of the 3D Ising Model Zaher Abstract We have analysed low and high temperature series expansions for the threedimensional Ising model on the simple cubic lattice. Our analysis of Butera and Comi's new 32 term high temperature series yields K c
On the Parameter Estimation of Linear Models of Aggregate Power System Loads
Cañizares, Claudio A.
1 On the Parameter Estimation of Linear Models of Aggregate Power System Loads Valery Knyazkin-- This paper addressed some theoretical and practical issues relevant to the problem of power system load, and the corresponding results are used to validate a commonly used linear model of aggre- gate power system load
ACCEPTED TO IEEE TRANSACTIONS ON POWER SYSTEMS 1 On the Parameter Estimation and Modeling of
Cañizares, Claudio A.
ACCEPTED TO IEEE TRANSACTIONS ON POWER SYSTEMS 1 On the Parameter Estimation and Modeling of Aggregate Power System Loads Valery Knyazkin, Student Member, IEEE, Claudio Ca~nizares, Senior Member, IEEE relevant to the problem of power system load modeling and identification. Two identification techniques
Statistical Simulation to Estimate Uncertain Behavioral Parameters of Hybrid Energy-Economy Models
functions. Policies that change energy prices, such as a tax on GHG emissions, can be simulated for their effect on output, energy demand, and, as a result, emissions. The model responses to these price changesStatistical Simulation to Estimate Uncertain Behavioral Parameters of Hybrid Energy-Economy Models
Comparison of model estimates of the effects of aviation emissions on atmospheric ozone and methane
Jacobson, Mark
Comparison of model estimates of the effects of aviation emissions on atmospheric ozone and methane is the effects of aviation emissions on ozone and atmospheric chemistry. In this study the effects of aviation emissions on atmospheric ozone for 2006 and two projections for 2050 are compared among seven models
Distributed state estimation and model predictive control of linear interconnected system
Boyer, Edmond
requirements, modern control systems are becoming more and more complex. For these processes, different controlDistributed state estimation and model predictive control of linear interconnected system: In this paper, a distributed and networked control system architecture based on independent Model Predictive
Modeling and Bayesian parameter estimation for shape memory alloy bending actuators
Modeling and Bayesian parameter estimation for shape memory alloy bending actuators John H. Crewsa energy model (HEM) for shape memory alloy (SMA) bending actuators. Additionally, we utilize a Bayesian. Keywords: shape memory alloys, uncertainty quantificiation, markov chain monte carlo 1. INTRODUCTION Shape
Mittelmann, Hans D.
is shown by applying it to a case study involving composition control of a binary distillation column. I is demonstrated in a binary high-purity distillation column case study by Weischedel and McAvoy [7], a demandingOptimization-based Design of Plant-Friendly Input Signals for Model-on-Demand Estimation and Model
Chen, X.; Liu, X.; Gales, M. J. F.; Woodland, P. C.
2015-04-22T23:59:59.000Z
, recurrent neural network, GPU, noise contrastive estimation, speech recognition 1. INTRODUCTION Statistical language models (LMs) are crucial components in many speech and language processing systems designed for tasks such as speech recognition, spoken... as follows. In section 2, recur- rent neural network LMs are reviewed. Noise contrastive estimation is presented in section 3. The detailed implement of NCE training is presented in section 4. Experiment results on a large vocabulary conversational telephone...
Maximum likelihood parameter estimation in time series models using sequential Monte Carlo
Yildirim, Sinan
2013-06-11T23:59:59.000Z
, respectively. This approach is useful to handle the case where the columns of Y are generated sequentially in time, such as in audio signal processing. Usually very large number of columns in Y leads to the necessity of online algorithms to learn the model... .6 (dashed lines). For illustrative purposes, every 1000th estimate is shown . . . . . . . . . . . . . . . . . . . . . . . 130 6.1 Histograms of Monte Carlo estimates of gradients of log p?,?,?? (Y ?,?,?) w.r.t. the parameters of the ?-stable distribution...
A Monte Carlo study of the distribution of parameter estimators in a dual exponential decay model
Garcia, Raul
1969-01-01T23:59:59.000Z
of an estimate of the reliability of the parameter estimates calculated. In 1965, Bell and Garcia [2] developed a computer program which permits a solution of the parameters without the time-consuming effort of manual calcu- lations. The same year, Rossing [3...A MONTE CARLO STUDY OF THE DISTRIBUTION OF PARAMETER ESTIMATORS IN A DUAL EXPONENTIAL DECAY MODEL A Thesis by SAUL GARCIA Submitted to the Graduate College of Texas A&M University in partial fulfillment of the requirements for the degree...
Mukhopadhyay, S.; Tsang, Y.; Finsterle, S.
2009-01-15T23:59:59.000Z
A simple conceptual model has been recently developed for analyzing pressure and temperature data from flowing fluid temperature logging (FFTL) in unsaturated fractured rock. Using this conceptual model, we developed an analytical solution for FFTL pressure response, and a semianalytical solution for FFTL temperature response. We also proposed a method for estimating fracture permeability from FFTL temperature data. The conceptual model was based on some simplifying assumptions, particularly that a single-phase airflow model was used. In this paper, we develop a more comprehensive numerical model of multiphase flow and heat transfer associated with FFTL. Using this numerical model, we perform a number of forward simulations to determine the parameters that have the strongest influence on the pressure and temperature response from FFTL. We then use the iTOUGH2 optimization code to estimate these most sensitive parameters through inverse modeling and to quantify the uncertainties associated with these estimated parameters. We conclude that FFTL can be utilized to determine permeability, porosity, and thermal conductivity of the fracture rock. Two other parameters, which are not properties of the fractured rock, have strong influence on FFTL response. These are pressure and temperature in the borehole that were at equilibrium with the fractured rock formation at the beginning of FFTL. We illustrate how these parameters can also be estimated from FFTL data.
Ajo-Franklin, Jonathan
models on estimates of reservoir parameters from joint inversion of seismic AVA and CSEM data. The reser framework and Markov Chain Monte Carlo methods, we obtain estimates of reservoir parameters as well as of the uncertainty in the estimates. Synthetic case studies show that uncertainties in both rock-physics models
Tadi?, Vladislav B
2009-01-01T23:59:59.000Z
This paper considers the asymptotic properties of the recursive maximum likelihood estimation in hidden Markov models. The paper is focused on the asymptotic behavior of the log-likelihood function and on the point-convergence and convergence rate of the recursive maximum likelihood estimator. Using the principle of analytical continuation, the analyticity of the asymptotic log-likelihood function is shown for analytically parameterized hidden Markov models. Relying on this fact and some results from differential geometry (Lojasiewicz inequality), the almost sure point-convergence of the recursive maximum likelihood algorithm is demonstrated, and relatively tight bounds on the convergence rate are derived. As opposed to the existing result on the asymptotic behavior of maximum likelihood estimation in hidden Markov models, the results of this paper are obtained without assuming that the log-likelihood function has an isolated maximum at which the Hessian is strictly negative definite.
A Neural Network Model for Construction Projects Site Overhead Cost Estimating in Egypt
ElSawy, Ismaail; Razek, Mohammed Abdel
2011-01-01T23:59:59.000Z
Estimating of the overhead costs of building construction projects is an important task in the management of these projects. The quality of construction management depends heavily on their accurate cost estimation. Construction costs prediction is a very difficult and sophisticated task especially when using manual calculation methods. This paper uses Artificial Neural Network (ANN) approach to develop a parametric cost-estimating model for site overhead cost in Egypt. Fifty-two actual real-life cases of building projects constructed in Egypt during the seven year period 2002-2009 were used as training materials. The neural network architecture is presented for the estimation of the site overhead costs as a percentage from the total project price.
Chen, H.W. (Los Alamos National Lab., NM (United States). Biophysics Group M715)
1995-01-01T23:59:59.000Z
Structural classification and parameter estimation (SCPE) methods are used for studying single-input single-output (SISO) parallel linear-nonlinear-linear (LNL), linear-nonlinear (LN), and nonlinear-linear (NL) system models from input-output (I-O) measurements. The uniqueness of the I-O mappings (see the definition of the I-O mapping in Section 3-A) of some model structures is discussed. The uniqueness of the I-O mappings (see the definition of the I-O mapping in Section 3-A) of some model structures is discussed. The uniqueness of I-O mappings of different models tells them in what conditions different model structures can be differentiated from one another. Parameter uniqueness of the I-O mapping of a given structural model is also discussed, which tells the authors in what conditions a given model's parameters can be uniquely estimated from I-O measurements. These methods are then generalized so that they can be used to study single-input multi-output (SIMO), multi-input single-output (MISO), as well as multi-input multi-output (MIMO) nonlinear system models. Parameter estimation of the two-input single-output nonlinear system model (denoted as the 2f-structure in 2 cited references), which was left unsolved previously, can now be obtained using the newly derived algorithms. Applications of SCPE methods for modeling visual cortical neurons, system fault detection, modeling and identification of communication networks, biological systems, and natural and artificial neural networks are also discussed. The feasibility of these methods is demonstrated using simulated examples. SCPE methods presented in this paper can be further developed to study more complicated block-structures models, and will therefore have future potential for modeling and identifying highly complex multi-input multi-output nonlinear systems.
Araujo, Marcelo Guimaraes, E-mail: marcel_g@uol.com.br [Federal University of Rio de Janeiro, COPPE, Energy Planning Department (Brazil); Magrini, Alessandra [Federal University of Rio de Janeiro, COPPE, Energy Planning Department (Brazil); Mahler, Claudio Fernando [Federal University of Rio de Janeiro, COPPE, GETRES (Brazil); Bilitewski, Bernd [Technical University of Dresden, Institute of Waste Management and Contaminated Site Treatment (IAA) (Germany)
2012-02-15T23:59:59.000Z
Highlights: Black-Right-Pointing-Pointer Literature of WEEE generation in developing countries is reviewed. Black-Right-Pointing-Pointer We analyse existing estimates of WEEE generation for Brazil. Black-Right-Pointing-Pointer We present a model for WEEE generation estimate. Black-Right-Pointing-Pointer WEEE generation of 3.77 kg/capita year for 2008 is estimated. Black-Right-Pointing-Pointer Use of constant lifetime should be avoided for non-mature market products. - Abstract: Sales of electrical and electronic equipment are increasing dramatically in developing countries. Usually, there are no reliable data about quantities of the waste generated. A new law for solid waste management was enacted in Brazil in 2010, and the infrastructure to treat this waste must be planned, considering the volumes of the different types of electrical and electronic equipment generated. This paper reviews the literature regarding estimation of waste electrical and electronic equipment (WEEE), focusing on developing countries, particularly in Latin America. It briefly describes the current WEEE system in Brazil and presents an updated estimate of generation of WEEE. Considering the limited available data in Brazil, a model for WEEE generation estimation is proposed in which different methods are used for mature and non-mature market products. The results showed that the most important variable is the equipment lifetime, which requires a thorough understanding of consumer behavior to estimate. Since Brazil is a rapidly expanding market, the 'boom' in waste generation is still to come. In the near future, better data will provide more reliable estimation of waste generation and a clearer interpretation of the lifetime variable throughout the years.
Development of Property-Transfer Models for Estimating the Hydraulic Properties of Deep
Development of Property-Transfer Models for Estimating the Hydraulic Properties of Deep Sediments at the Idaho National Engineering and Environmental Laboratory, Idaho Scientific Investigations Report 2005 Survey DOE/ID-22196 #12;Cover: Graph showing example of water-retention (q(y)) curve showing components
Everingham, Mark
Appearance Models for Human Pose Estimation Sam Johnson s.a.johnson04@leeds.ac.uk Mark Everingham m.everingham@leeds.ac.uk School of Computing University of Leeds Leeds, UK Abstract We investigate the task of 2D articulated parts e.g. labeling the position and orientation of the head, torso, arms and legs in an image
Edinburgh Research Explorer Comparison of models for estimation of long-term exposure to
Millar, Andrew J.
-term exposure to air pollution in cohort studies' Atmospheric Environment, vol 62, pp. 530-539., 10.1016/j to Air Pollution in Cohort Studies Beverland, I.J.* Department of Civil Engineering, University.L. and Agius, R.M. (2012) Comparison of models for estimation of long-term exposure to air pollution in cohort
Parameter Estimation and Life Modeling of Lithium-Ion Cells Shriram Santhanagopalan,*,a
Parameter Estimation and Life Modeling of Lithium-Ion Cells Shriram Santhanagopalan,*,a Qi Zhang Carolina, Columbia, South Carolina 29208, USA Lithium-ion pouch cells were cycled at five different. The lithium-ion cell is among the most popular candidates con- sidered actively as a replacement for nickel
SO2 emissions and lifetimes: Estimates from inverse modeling using in situ and global, spacebased
Martin, Randall
SO2 emissions and lifetimes: Estimates from inverse modeling using in situ and global, spacebased 18 March 2011. [1] Topdown constraints on global sulfur dioxide (SO2) emissions are inferred through of GEOSChem for inversion of SO2 columns to emissions. The seasonal mean SO2 lifetime calculated with the GEOS
ASSESSMENT OF THE MODELS FOR THE ESTIMATION OF THE CO2 RELEASES TOXIC EFFECTS
Boyer, Edmond
the global warming due to high concentration of CO2 in the atmosphere. However, in case of massive accidental to specific properties regarding its triple point. Then, this CO2 flakes creation may be followed1 ASSESSMENT OF THE MODELS FOR THE ESTIMATION OF THE CO2 RELEASES TOXIC EFFECTS Frédéric Antoine
Estimating Water Quality Pollution Impacts Based on Economic Loss Models in Urbanization Process
Yu, Qian
Estimating Water Quality Pollution Impacts Based on Economic Loss Models in Urbanization Process Abstract: The study investigates water quality pollution impacts on urbanization by analyzing temporal the greatest contributors of surface water quality pollution from 1996 to 2003. High values existed
Robust Estimation and Outlier Detection for Overdispersed Multinomial Models of Count Data
Sekhon, Jasjeet S.
Robust Estimation and Outlier Detection for Overdispersed Multinomial Models of Count Data Walter R research on labor rela- tions (Card 1990), the relationship between patents and R&D (Hausman, Hall counts in political science includes studies of child care services (Bratton and Ray 2002), gender
Estimating Litter Decomposition Rate in Single-Pool Models Using Nonlinear Beta Regression
Thomas, David D.
Estimating Litter Decomposition Rate in Single-Pool Models Using Nonlinear Beta Regression Etienne the performance of nonlinear regression using the beta distribution, which is well-suited to bounded data and this type of heteroscedasticity, to standard nonlinear regression (normal errors) on simulated and real
A Model for Human Interruptability: Experimental Evaluation and Automatic Estimation from Wearable Sensors Nicky Kern, Stavros Antifakos, Bernt Schiele Perceptual Computing and Computer Vision ETH Zurich sensors. It is scalable for a large number of sensors, contexts, and situations and allows for online
An iterative stochastic ensemble method for parameter estimation of subsurface flow models
Elsheikh, Ahmed H., E-mail: aelsheikh@ices.utexas.edu [Center for Subsurface Modeling (CSM), Institute for Computational Engineering and Sciences (ICES), University of Texas at Austin, TX (United States); Dept. of Earth Sciences and Engineering, King Abdullah University of Science and Technology (KAUST), Thuwal (Saudi Arabia); Dept. of Applied Mathematics and Computational Sciences, King Abdullah University of Science and Technology (KAUST), Thuwal (Saudi Arabia); Wheeler, Mary F. [Center for Subsurface Modeling (CSM), Institute for Computational Engineering and Sciences (ICES), University of Texas at Austin, TX (United States)] [Center for Subsurface Modeling (CSM), Institute for Computational Engineering and Sciences (ICES), University of Texas at Austin, TX (United States); Hoteit, Ibrahim [Dept. of Earth Sciences and Engineering, King Abdullah University of Science and Technology (KAUST), Thuwal (Saudi Arabia) [Dept. of Earth Sciences and Engineering, King Abdullah University of Science and Technology (KAUST), Thuwal (Saudi Arabia); Dept. of Applied Mathematics and Computational Sciences, King Abdullah University of Science and Technology (KAUST), Thuwal (Saudi Arabia)
2013-06-01T23:59:59.000Z
Parameter estimation for subsurface flow models is an essential step for maximizing the value of numerical simulations for future prediction and the development of effective control strategies. We propose the iterative stochastic ensemble method (ISEM) as a general method for parameter estimation based on stochastic estimation of gradients using an ensemble of directional derivatives. ISEM eliminates the need for adjoint coding and deals with the numerical simulator as a blackbox. The proposed method employs directional derivatives within a Gauss–Newton iteration. The update equation in ISEM resembles the update step in ensemble Kalman filter, however the inverse of the output covariance matrix in ISEM is regularized using standard truncated singular value decomposition or Tikhonov regularization. We also investigate the performance of a set of shrinkage based covariance estimators within ISEM. The proposed method is successfully applied on several nonlinear parameter estimation problems for subsurface flow models. The efficiency of the proposed algorithm is demonstrated by the small size of utilized ensembles and in terms of error convergence rates.
Estimation of a supply and demand model for the hired farm labor market in Texas
Turley, Keith Pool
1977-01-01T23:59:59.000Z
ESTIMATION OF A SUPPLY AND DEMAND MODEL FOR THE HIRED FARM LABOR MARKET IN TEXAS A Thesis by KEITH POOL TURLEY Submitted to the Craduate College of Texas ARM University in partial fulfillment of the requirement for the degree of MASTER... Or SCIENCI. December 1977 Major Subject: Agricultural Economics ESTIMATION OF A SUPPLY AND DEMAND NODEL FOR THE HIRED FARM LABOR MARKET IN TEXAS A Thesis by KEITH POOL TURLEY Approved as to style and content by: Ch rman of Comm' tee) Member Mem r...
Comparison of Fourier and model-based estimators in single mode multiaxial interferometry
E. Tatulli; J. -B. LeBouquin
2006-02-15T23:59:59.000Z
There are several solutions to code the signal arising from optical long baseline multi-aperture interferometers. In this paper,we focus on the {\\bf non homothetic spatial coding scheme} (multiaxial) with the fringe pattern coded along one dimension on one detector(all-in-one). After describing the physical principles governing single mode interferometers using that sort of recombination scheme, we analyze two different existing methods that measure the source visibility. The first technique, so-called Fourier estimator, consists in integrating the high frequency peak of the power spectral density of the interferogram. The second method, so-called model-based estimator, has been specifically developed for the AMBER instrument of the VLTI and deals with directly modelling the interferogram recorded on the detector. Performances of both estimators are computed in terms of Signal to Noise Ratio (SNR) of the visibility, assuming that the interferograms are perturbed by photon and detector noises. Theoretical expressions of the visibility SNR are provided, validated through numerical computations and then compared. We show that the model-based estimator offers up to 5 times better performances than the Fourier one.
A Bayesian Approach for Parameter Estimation and Prediction using a Computationally Intensive Model
Dave Higdon; Jordan D. McDonnell; Nicolas Schunck; Jason Sarich; Stefan M. Wild
2014-09-17T23:59:59.000Z
Bayesian methods have been very successful in quantifying uncertainty in physics-based problems in parameter estimation and prediction. In these cases, physical measurements y are modeled as the best fit of a physics-based model $\\eta(\\theta)$ where $\\theta$ denotes the uncertain, best input setting. Hence the statistical model is of the form $y = \\eta(\\theta) + \\epsilon$, where $\\epsilon$ accounts for measurement, and possibly other error sources. When non-linearity is present in $\\eta(\\cdot)$, the resulting posterior distribution for the unknown parameters in the Bayesian formulation is typically complex and non-standard, requiring computationally demanding computational approaches such as Markov chain Monte Carlo (MCMC) to produce multivariate draws from the posterior. While quite generally applicable, MCMC requires thousands, or even millions of evaluations of the physics model $\\eta(\\cdot)$. This is problematic if the model takes hours or days to evaluate. To overcome this computational bottleneck, we present an approach adapted from Bayesian model calibration. This approach combines output from an ensemble of computational model runs with physical measurements, within a statistical formulation, to carry out inference. A key component of this approach is a statistical response surface, or emulator, estimated from the ensemble of model runs. We demonstrate this approach with a case study in estimating parameters for a density functional theory (DFT) model, using experimental mass/binding energy measurements from a collection of atomic nuclei. We also demonstrate how this approach produces uncertainties in predictions for recent mass measurements obtained at Argonne National Laboratory (ANL).
Coastal DEMs integrate seafloor bathymetry and land topography to depict Earth's solid surface Sheet What is a coastal DEM? A coastal DEM depicts Earth's land surface and ocean bottom. It is made
Estimating a model discrepancy term for the Community Land Model using latent heat and
Ray, Jaideep
system models; coupled to an atmosphere & ocean model · Can be used in global (gridded) mode or locally calibration = O(104) #12;What is CLM? · A model for biogeochemical & hydrological processes · Used in Earth
Miller, C.; Little, C.A.
1982-08-01T23:59:59.000Z
The purpose is to summarize estimates based on currently available data of the uncertainty associated with radiological assessment models. The models being examined herein are those recommended previously for use in breeder reactor assessments. Uncertainty estimates are presented for models of atmospheric and hydrologic transport, terrestrial and aquatic food-chain bioaccumulation, and internal and external dosimetry. Both long-term and short-term release conditions are discussed. The uncertainty estimates presented in this report indicate that, for many sites, generic models and representative parameter values may be used to calculate doses from annual average radionuclide releases when these calculated doses are on the order of one-tenth or less of a relevant dose limit. For short-term, accidental releases, especially those from breeder reactors located in sites dominated by complex terrain and/or coastal meteorology, the uncertainty in the dose calculations may be much larger than an order of magnitude. As a result, it may be necessary to incorporate site-specific information into the dose calculation under these circumstances to reduce this uncertainty. However, even using site-specific information, natural variability and the uncertainties in the dose conversion factor will likely result in an overall uncertainty of greater than an order of magnitude for predictions of dose or concentration in environmental media following shortterm releases.
Estimating Loss-of-Coolant Accident Frequencies for the Standardized Plant Analysis Risk Models
S. A. Eide; D. M. Rasmuson; C. L. Atwood
2008-09-01T23:59:59.000Z
The U.S. Nuclear Regulatory Commission maintains a set of risk models covering the U.S. commercial nuclear power plants. These standardized plant analysis risk (SPAR) models include several loss-of-coolant accident (LOCA) initiating events such as small (SLOCA), medium (MLOCA), and large (LLOCA). All of these events involve a loss of coolant inventory from the reactor coolant system. In order to maintain a level of consistency across these models, initiating event frequencies generally are based on plant-type average performance, where the plant types are boiling water reactors and pressurized water reactors. For certain risk analyses, these plant-type initiating event frequencies may be replaced by plant-specific estimates. Frequencies for SPAR LOCA initiating events previously were based on results presented in NUREG/CR-5750, but the newest models use results documented in NUREG/CR-6928. The estimates in NUREG/CR-6928 are based on historical data from the initiating events database for pressurized water reactor SLOCA or an interpretation of results presented in the draft version of NUREG-1829. The information in NUREG-1829 can be used several ways, resulting in different estimates for the various LOCA frequencies. Various ways NUREG-1829 information can be used to estimate LOCA frequencies were investigated and this paper presents two methods for the SPAR model standard inputs, which differ from the method used in NUREG/CR-6928. In addition, results obtained from NUREG-1829 are compared with actual operating experience as contained in the initiating events database.
Harlim, John, E-mail: jharlim@psu.edu [Department of Mathematics and Department of Meteorology, the Pennsylvania State University, University Park, PA 16802, Unites States (United States)] [Department of Mathematics and Department of Meteorology, the Pennsylvania State University, University Park, PA 16802, Unites States (United States); Mahdi, Adam, E-mail: amahdi@ncsu.edu [Department of Mathematics, North Carolina State University, Raleigh, NC 27695 (United States)] [Department of Mathematics, North Carolina State University, Raleigh, NC 27695 (United States); Majda, Andrew J., E-mail: jonjon@cims.nyu.edu [Department of Mathematics and Center for Atmosphere and Ocean Science, Courant Institute of Mathematical Sciences, New York University, New York, NY 10012 (United States)
2014-01-15T23:59:59.000Z
A central issue in contemporary science is the development of nonlinear data driven statistical–dynamical models for time series of noisy partial observations from nature or a complex model. It has been established recently that ad-hoc quadratic multi-level regression models can have finite-time blow-up of statistical solutions and/or pathological behavior of their invariant measure. Recently, a new class of physics constrained nonlinear regression models were developed to ameliorate this pathological behavior. Here a new finite ensemble Kalman filtering algorithm is developed for estimating the state, the linear and nonlinear model coefficients, the model and the observation noise covariances from available partial noisy observations of the state. Several stringent tests and applications of the method are developed here. In the most complex application, the perfect model has 57 degrees of freedom involving a zonal (east–west) jet, two topographic Rossby waves, and 54 nonlinearly interacting Rossby waves; the perfect model has significant non-Gaussian statistics in the zonal jet with blocked and unblocked regimes and a non-Gaussian skewed distribution due to interaction with the other 56 modes. We only observe the zonal jet contaminated by noise and apply the ensemble filter algorithm for estimation. Numerically, we find that a three dimensional nonlinear stochastic model with one level of memory mimics the statistical effect of the other 56 modes on the zonal jet in an accurate fashion, including the skew non-Gaussian distribution and autocorrelation decay. On the other hand, a similar stochastic model with zero memory levels fails to capture the crucial non-Gaussian behavior of the zonal jet from the perfect 57-mode model.
Glass Property Data and Models for Estimating High-Level Waste Glass Volume
Vienna, John D.; Fluegel, Alexander; Kim, Dong-Sang; Hrma, Pavel R.
2009-10-05T23:59:59.000Z
This report describes recent efforts to develop glass property models that can be used to help estimate the volume of high-level waste (HLW) glass that will result from vitrification of Hanford tank waste. The compositions of acceptable and processable HLW glasses need to be optimized to minimize the waste-form volume and, hence, to save cost. A database of properties and associated compositions for simulated waste glasses was collected for developing property-composition models. This database, although not comprehensive, represents a large fraction of data on waste-glass compositions and properties that were available at the time of this report. Glass property-composition models were fit to subsets of the database for several key glass properties. These models apply to a significantly broader composition space than those previously publised. These models should be considered for interim use in calculating properties of Hanford waste glasses.
Modeling, Real-Time Estimation, and Identification of UWB Indoor Wireless Channels
Olama, Mohammed M [ORNL] [ORNL; Djouadi, Seddik M [ORNL] [ORNL; Li, Yanyan [ORNL] [ORNL; Fathy, Aly [University of Tennessee (UT)] [University of Tennessee (UT)
2013-01-01T23:59:59.000Z
In this paper, stochastic differential equations (SDEs) are used to model ultrawideband (UWB) indoor wireless channels. We show that the impulse responses for time-varying indoor wireless channels can be approximated in a mean square sense as close as desired by impulse responses that can be realized by SDEs. The state variables represent the inphase and quadrature components of the UWB channel. The expected maximization and extended Kalman filter are employed to recursively identify and estimate the channel parameters and states, respectively, from online received signal strength measured data. Both resolvable and non-resolvable multipath received signals are considered and represented as small-scaled Nakagami fading. The proposed models together with the estimation algorithm are tested using UWB indoor measurement data demonstrating the method s viability and the results are presented.
Li, Ke
2012-02-14T23:59:59.000Z
of the requirements for the degree of DOCTOR OF PHILOSOPHY December 2010 Major Subject: Agricultural Economics Essays on Regression Spline Structural Nonparametric Stochastic Production Frontier Estimation and Ine ciency Analysis Models Copyright 2010 Ke Li... of the requirements for the degree of DOCTOR OF PHILOSOPHY Approved by: Chair of Committee, Ximing Wu Committee Members, David Bessler H. Alan Love Qi Li Head of Department, John P. Nichols December 2010 Major Subject: Agricultural Economics iii ABSTRACT...
Griffith, Daniel Todd
2005-02-17T23:59:59.000Z
computation and evaluation of partial derivatives with minimal user coding. The key results in this dissertation details the use of OCEA through a number of computational studies in estimation and dynamical modeling. Several prototype problems are studied... Embedding Method), has been recently developed which shows promise for efficient computation and evaluation of partial derivatives. For a rather arbitrary sequentially substituted set of functions, coded in FORTRAN 90, OCEA invokes operator overloading...
Modeling and estimation in Gaussian graphical models : maximum-entropy methods and walk-sum analysis
Chandrasekaran, Venkat
2007-01-01T23:59:59.000Z
Graphical models provide a powerful formalism for statistical signal processing. Due to their sophisticated modeling capabilities, they have found applications in a variety of fields such as computer vision, image processing, ...
ESTIMATING THE PROPERTIES OF HARD X-RAY SOLAR FLARES BY CONSTRAINING MODEL PARAMETERS
Ireland, J. [ADNET Systems, Inc. at NASA Goddard Space Flight Center, Greenbelt, MD 20771 (United States); Tolbert, A. K.; Schwartz, R. A. [Catholic University of America at NASA Goddard Space Flight Center, Greenbelt, MD 20771 (United States); Holman, G. D.; Dennis, B. R. [NASA Goddard Space Flight Center, Code 671, Greenbelt, MD 20771 (United States)
2013-06-01T23:59:59.000Z
We wish to better constrain the properties of solar flares by exploring how parameterized models of solar flares interact with uncertainty estimation methods. We compare four different methods of calculating uncertainty estimates in fitting parameterized models to Ramaty High Energy Solar Spectroscopic Imager X-ray spectra, considering only statistical sources of error. Three of the four methods are based on estimating the scale-size of the minimum in a hypersurface formed by the weighted sum of the squares of the differences between the model fit and the data as a function of the fit parameters, and are implemented as commonly practiced. The fourth method is also based on the difference between the data and the model, but instead uses Bayesian data analysis and Markov chain Monte Carlo (MCMC) techniques to calculate an uncertainty estimate. Two flare spectra are modeled: one from the Geostationary Operational Environmental Satellite X1.3 class flare of 2005 January 19, and the other from the X4.8 flare of 2002 July 23. We find that the four methods give approximately the same uncertainty estimates for the 2005 January 19 spectral fit parameters, but lead to very different uncertainty estimates for the 2002 July 23 spectral fit. This is because each method implements different analyses of the hypersurface, yielding method-dependent results that can differ greatly depending on the shape of the hypersurface. The hypersurface arising from the 2005 January 19 analysis is consistent with a normal distribution; therefore, the assumptions behind the three non-Bayesian uncertainty estimation methods are satisfied and similar estimates are found. The 2002 July 23 analysis shows that the hypersurface is not consistent with a normal distribution, indicating that the assumptions behind the three non-Bayesian uncertainty estimation methods are not satisfied, leading to differing estimates of the uncertainty. We find that the shape of the hypersurface is crucial in understanding the output from each uncertainty estimation technique, and that a crucial factor determining the shape of hypersurface is the location of the low-energy cutoff relative to energies where the thermal emission dominates. The Bayesian/MCMC approach also allows us to provide detailed information on probable values of the low-energy cutoff, E{sub c} , a crucial parameter in defining the energy content of the flare-accelerated electrons. We show that for the 2002 July 23 flare data, there is a 95% probability that E{sub c} lies below approximately 40 keV, and a 68% probability that it lies in the range 7-36 keV. Further, the low-energy cutoff is more likely to be in the range 25-35 keV than in any other 10 keV wide energy range. The low-energy cutoff for the 2005 January 19 flare is more tightly constrained to 107 {+-} 4 keV with 68% probability. Using the Bayesian/MCMC approach, we also estimate for the first time probability density functions for the total number of flare-accelerated electrons and the energy they carry for each flare studied. For the 2002 July 23 event, these probability density functions are asymmetric with long tails orders of magnitude higher than the most probable value, caused by the poorly constrained value of the low-energy cutoff. The most probable electron power is estimated at 10{sup 28.1} erg s{sup -1}, with a 68% credible interval estimated at 10{sup 28.1}-10{sup 29.0} erg s{sup -1}, and a 95% credible interval estimated at 10{sup 28.0}-10{sup 30.2} erg s{sup -1}. For the 2005 January 19 flare spectrum, the probability density functions for the total number of flare-accelerated electrons and their energy are much more symmetric and narrow: the most probable electron power is estimated at 10{sup 27.66{+-}0.01} erg s{sup -1} (68% credible intervals). However, in this case the uncertainty due to systematic sources of error is estimated to dominate the uncertainty due to statistical sources of error.
Olama, Mohammed M [ORNL; Djouadi, Seddik M [ORNL; Charalambous, Prof. Charalambos [University of Cyprus
2009-01-01T23:59:59.000Z
Mobile-to-mobile networks are characterized by node mobility that makes the propagation environment time varying and subject to fading. As a consequence, the statistical characteristics of the received signal vary continuously, giving rise to a Doppler power spectral density (DPSD) which varies from one observation instant to the next. The current models do not capture and track the time varying characteristics. This paper is concerned with dynamical modelling of mobile-to-mobile channels, parameter estimation and identification from received signal measurements. The evolution of the propagation environment is described by stochastic differential equations. In particular, it is shown that the parameters of the models can be determined by approximating the band-limited DPSD using the Gauss-Newton method. However, since the DPSD is not available online, we propose to use a filter-based expectation maximization algorithm and Kalman filter to estimate the channel parameters and states, respectively. The scheme results in a finite dimensional filter which only uses the first and second order statistics. The algorithm is recursive allowing the inphase and quadrature components and parameters to be estimated online from received signal measurements. The algorithms are tested using experimental data collected from moving sensor nodes in indoor and outdoor environments demonstrating the method s viability.
Gershgorin, B. [Department of Mathematics and Center for Atmosphere and Ocean Science, Courant Institute of Mathematical Sciences, New York University, NY 10012 (United States); Harlim, J. [Department of Mathematics, North Carolina State University, NC 27695 (United States)], E-mail: jharlim@ncsu.edu; Majda, A.J. [Department of Mathematics and Center for Atmosphere and Ocean Science, Courant Institute of Mathematical Sciences, New York University, NY 10012 (United States)
2010-01-01T23:59:59.000Z
The filtering and predictive skill for turbulent signals is often limited by the lack of information about the true dynamics of the system and by our inability to resolve the assumed dynamics with sufficiently high resolution using the current computing power. The standard approach is to use a simple yet rich family of constant parameters to account for model errors through parameterization. This approach can have significant skill by fitting the parameters to some statistical feature of the true signal; however in the context of real-time prediction, such a strategy performs poorly when intermittent transitions to instability occur. Alternatively, we need a set of dynamic parameters. One strategy for estimating parameters on the fly is a stochastic parameter estimation through partial observations of the true signal. In this paper, we extend our newly developed stochastic parameter estimation strategy, the Stochastic Parameterization Extended Kalman Filter (SPEKF), to filtering sparsely observed spatially extended turbulent systems which exhibit abrupt stability transition from time to time despite a stable average behavior. For our primary numerical example, we consider a turbulent system of externally forced barotropic Rossby waves with instability introduced through intermittent negative damping. We find high filtering skill of SPEKF applied to this toy model even in the case of very sparse observations (with only 15 out of the 105 grid points observed) and with unspecified external forcing and damping. Additive and multiplicative bias corrections are used to learn the unknown features of the true dynamics from observations. We also present a comprehensive study of predictive skill in the one-mode context including the robustness toward variation of stochastic parameters, imperfect initial conditions and finite ensemble effect. Furthermore, the proposed stochastic parameter estimation scheme applied to the same spatially extended Rossby wave system demonstrates high predictive skill, comparable with the skill of the perfect model for a duration of many eddy turnover times especially in the unstable regime.
RADTRAD: A simplified model for RADionuclide Transport and Removal And Dose estimation
Humphreys, S.L.; Miller, L.A.; Monroe, D.K. [Sandia National Labs., Albuquerque, NM (United States); Heames, T.J. [ITSC, Albuquerque, NM (United States)
1998-04-01T23:59:59.000Z
This report documents the RADTRAD computer code developed for the U.S. Nuclear Regulatory Commission (NRC) Office of Nuclear Reactor Regulation (NRR) to estimate transport and removal of radionuclides and dose at selected receptors. The document includes a users` guide to the code, a description of the technical basis for the code, the quality assurance and code acceptance testing documentation, and a programmers` guide. The RADTRAD code can be used to estimate the containment release using either the NRC TID-14844 or NUREG-1465 source terms and assumptions, or a user-specified table. In addition, the code can account for a reduction in the quantity of radioactive material due to containment sprays, natural deposition, filters, and other natural and engineered safety features. The RADTRAD code uses a combination of tables and/or numerical models of source term reduction phenomena to determine the time-dependent dose at user-specified locations for a given accident scenario. The code system also provides the inventory, decay chain, and dose conversion factor tables needed for the dose calculation. The RADTRAD code can be used to assess occupational radiation exposures, typically in the control room; to estimate site boundary doses; and to estimate dose attenuation due to modification of a facility or accident sequence.
Modeling Estimated Personnel Needs for a Potential Foot and Mouth Disease Outbreak
Simmons, K; Hullinger, P
2008-01-29T23:59:59.000Z
Foot and Mouth disease (FMD) is a highly infectious and contagious viral disease affecting cloven-hoofed livestock that was last detected in the United States (US) in 1929. The prevalence of FMD in other countries, as well as the current potential for this virus to be used as a form of agroterrorism, has made preparations for a potential FMD outbreak a national priority. To assist in the evaluation of national preparedness, all 50 states were surveyed via e-mail, telephone and web search to obtain emergency response plans for FMD or for foreign animal diseases in general. Information from 33 states was obtained and analyzed for estimates of personnel resources needed to respond to an outbreak. These estimates were consolidated and enhanced to create a tool that could be used by individual states to better understand the personnel that would be needed to complete various tasks over time during an outbreak response. The estimates were then coupled, post-processing, to the output from FMD outbreaks simulated in California using the Multiscale Epidemiological/Economic Simulation and Analysis (MESA) model at Lawrence Livermore National Laboratory to estimate the personnel resource demands, by task, over the course of an outbreak response.
A Biomass-based Model to Estimate the Plausibility of Exoplanet Biosignature Gases
Seager, S; Hu, R
2013-01-01T23:59:59.000Z
Biosignature gas detection is one of the ultimate future goals for exoplanet atmosphere studies. We have created a framework for linking biosignature gas detectability to biomass estimates, including atmospheric photochemistry and biological thermodynamics. The new framework is intended to liberate predictive atmosphere models from requiring fixed, Earth-like biosignature gas source fluxes. New biosignature gases can be considered with a check that the biomass estimate is physically plausible. We have validated the models on terrestrial production of NO, H2S, CH4, CH3Cl, and DMS. We have applied the models to propose NH3 as a biosignature gas on a "cold Haber World," a planet with a N2-H2 atmosphere, and to demonstrate why gases such as CH3Cl must have too large of a biomass to be a plausible biosignature gas on planets with Earth or early-Earth-like atmospheres orbiting a Sun-like star. To construct the biomass models, we developed a functional classification of biosignature gases, and found that gases (such...
Oostrom, Martinus; Truex, Michael J.; Rice, Amy K.; Johnson, Christian D.; Carroll, Kenneth C.; Becker, Dave; Simon, Michelle A.
2014-04-28T23:59:59.000Z
Soil vapor extraction (SVE) is a prevalent remediation approach for volatile contaminants in the vadose zone. To support selection of an appropriate endpoint for the SVE remedy, an evaluation is needed to determine whether vadose zone contamination has been diminished sufficiently to protect groundwater. When vapor-phase transport is an important component of the overall contaminant fate and transport from a vadose zone source, the contaminant concentration expected in groundwater is controlled by a limited set of parameters, including specific site dimensions, vadose zone properties, and source characteristics. An approach was developed for estimating the contaminant concentration in groundwater resulting from a contaminant source in the vadose zone based on pre-modeling contaminant transport for a matrix of parameter value combinations covering a range of potential site conditions. An interpolation and scaling process are then applied to estimate groundwater impact for site-specific conditions.
Hwang, Ho-Ling [ORNL; Davis, Stacy Cagle [ORNL
2009-12-01T23:59:59.000Z
This report is designed to document the analysis process and estimation models currently used by the Federal Highway Administration (FHWA) to estimate the off-highway gasoline consumption and public sector fuel consumption. An overview of the entire FHWA attribution process is provided along with specifics related to the latest update (2008) on the Off-Highway Gasoline Use Model and the Public Use of Gasoline Model. The Off-Highway Gasoline Use Model is made up of five individual modules, one for each of the off-highway categories: agricultural, industrial and commercial, construction, aviation, and marine. This 2008 update of the off-highway models was the second major update (the first model update was conducted during 2002-2003) after they were originally developed in mid-1990. The agricultural model methodology, specifically, underwent a significant revision because of changes in data availability since 2003. Some revision to the model was necessary due to removal of certain data elements used in the original estimation method. The revised agricultural model also made use of some newly available information, published by the data source agency in recent years. The other model methodologies were not drastically changed, though many data elements were updated to improve the accuracy of these models. Note that components in the Public Use of Gasoline Model were not updated in 2008. A major challenge in updating estimation methods applied by the public-use model is that they would have to rely on significant new data collection efforts. In addition, due to resource limitation, several components of the models (both off-highway and public-us models) that utilized regression modeling approaches were not recalibrated under the 2008 study. An investigation of the Environmental Protection Agency's NONROAD2005 model was also carried out under the 2008 model update. Results generated from the NONROAD2005 model were analyzed, examined, and compared, to the extent that is possible on the overall totals, to the current FHWA estimates. Because NONROAD2005 model was designed for emission estimation purposes (i.e., not for measuring fuel consumption), it covers different equipment populations from those the FHWA models were based on. Thus, a direct comparison generally was not possible in most sectors. As a result, NONROAD2005 data were not used in the 2008 update of the FHWA off-highway models. The quality of fuel use estimates directly affect the data quality in many tables published in the Highway Statistics. Although updates have been made to the Off-Highway Gasoline Use Model and the Public Use Gasoline Model, some challenges remain due to aging model equations and discontinuation of data sources.
Chen, Jinsong; Dickens, Thomas
2007-04-09T23:59:59.000Z
This study investigates the effects of uncertainty inrockphysics models on estimates of reservoir parameters from jointinversion of seismic AVA and CSEMdata. The reservoir parameters arerelated to electrical resistivity using Archie's law, and to seismicvelocity and density using the Xu-White model. To account for errors inthe rock-physics models, we use two methods to handle uncertainty: (1)the model outputs are random functions with modes or means given by themodel predictions, and (2) the parameters of the models are themselvesrandom variables. Using a stochastic framework and Markov Chain MonteCarlo methods, we obtain estimates of reservoir parameters as well as ofthe uncertainty in the estimates. Synthetic case studies show thatuncertainties in both rock-physics models and their associated parameterscan have significant effects on estimates of reservoir parameters. Ourmethod provides a means of quantifying how the uncertainty in theestimated reservoir parameters increases with increasing uncertainty inthe rock-physics model and in the model parameters. We find that in theexample we present, the estimation of water saturation is relatively lessaffected than is the estimation of clay content and porosity.
Evolution of Meteorological Base Models for Estimating Hourly Global Solar Radiation in Texas
Kim, H.; Baltazar, J.C.; Haberl, J.S
ESL-PA-13-11-01 Available online at www.sciencedirect.com Energy Procedia 00 (2013) 000–000 www.elsevier.com/locate/procedia 2013 ISES Solar World Congress Evaluation of Meteorological Base Models... for Estimating Hourly Global Solar Radiation in Texas Kee Han Kima,b*, Juan-Carlos Baltazarb, and Jeff S. Haberla,b aDepartment of Architecture, Texas A&M University, 3137 TAMU, College Station, TX 77843-3137, U.S.A. bEnergy Systems Laboratory, Texas A...
Long, David G.
Wind Bias from Sub-optimal Estimation Due to Geophysical Modeling Error -Wind I Paul E. Johnson (which relates the wind to the normalized radar cross section, NRCS, of the ocean surface) is uncertainty in the NRCS for given wind conditions. When the estimated variability is in- cluded in the maximum likelihood
Small-Area Estimation based on Survey Data from a Left-Censored Fay-Herriot Model
Maryland at College Park, University of
Administration's monthly crude oil report is based on a survey (EIA-813, http://www.eiaSmall-Area Estimation based on Survey Data from a Left-Censored Fay-Herriot Model Eric V. Slud, survey estimation. This paper describes research and analysis of its authors, and is released to in- form
Lautenberger, Chris; Rein, Guillermo; Fernandez-Pello, Carlos
A methodology based on an automated optimization technique that uses a genetic algorithm (GA) is developed to estimate the material properties needed for CFD-based fire growth modeling from bench-scale fire test data. ...
Mooijaart, Ab; Satorra, Albert
2011-01-01T23:59:59.000Z
of-?t summaries for the MM method degrees of freedom chi-regarding the robustness of the MM method to non-normality.MM versus ML estimates of structural equation models with
Rauhut, Holger
686 IEEE TRANSACTIONS ON MAGNETICS, VOL. 44, NO. 6, JUNE 2008 Estimating the Eddy-Current Modeling Zurich, CH-8092 ZÃ¼rich, Switzerland The eddy-current model is an approximation of the full Maxwell delivers a mathematical basis for assessing the scope of the eddy-current model. Index Terms--Eddy current
Paris-Sud XI, Université de
Information bounds and MCMC parameter estimation for the pile-up model Tabea Rebafkaa,b$, François Abstract This paper is concerned with the pile-up model defined as a nonlinear transformation of a distribution of interest. An observation of the pile-up model is the minimum of a random number of independent
A mathematical model for the estimation of flue temperature in a coke oven
Choi, K.I.; Kim, S.Y.; Suo, J.S.; Hur, N.S.; Kang, I.S.; Lee, W.J.
1997-12-31T23:59:59.000Z
The coke plants at the Kwangyang works has adopted an Automatic Battery Control (ABC) system which consists of four main parts, battery heating control, underfiring heat and waste gas oxygen control, pushing and charging schedule and Autotherm-S that measures heating wall temperature during pushing. The measured heating wall temperature is used for calculating Mean Battery Temperature (MBT) which is average temperature of flues for a battery, but the Autotherm-S system can not provide the flue temperatures of an oven. This work attempted to develop mathematical models for the estimation of the flue temperature using the measured heating wall temperature and to examine fitness of the mathematical model for the coke plant operation by analysis of raw gas temperature at the stand pipe. Through this work it is possible to reflect heating wall temperature in calculating MBT for battery heating control without the interruption caused by a maintenance break.
Estimating Reaction Rate Coefficients Within a Travel-Time Modeling Framework
Gong, R [Georgia Institute of Technology; Lu, C [Georgia Institute of Technology; Luo, Jian [Georgia Institute of Technology; Wu, Wei-min [Stanford University; Cheng, H. [Stanford University; Criddle, Craig [Stanford University; Kitanidis, Peter K. [Stanford University; Gu, Baohua [ORNL; Watson, David B [ORNL; Jardine, Philip M [ORNL; Brooks, Scott C [ORNL
2011-03-01T23:59:59.000Z
A generalized, efficient, and practical approach based on the travel-time modeling framework is developed to estimate in situ reaction rate coefficients for groundwater remediation in heterogeneous aquifers. The required information for this approach can be obtained by conducting tracer tests with injection of a mixture of conservative and reactive tracers and measurements of both breakthrough curves (BTCs). The conservative BTC is used to infer the travel-time distribution from the injection point to the observation point. For advection-dominant reactive transport with well-mixed reactive species and a constant travel-time distribution, the reactive BTC is obtained by integrating the solutions to advective-reactive transport over the entire travel-time distribution, and then is used in optimization to determine the in situ reaction rate coefficients. By directly working on the conservative and reactive BTCs, this approach avoids costly aquifer characterization and improves the estimation for transport in heterogeneous aquifers which may not be sufficiently described by traditional mechanistic transport models with constant transport parameters. Simplified schemes are proposed for reactive transport with zero-, first-, nth-order, and Michaelis-Menten reactions. The proposed approach is validated by a reactive transport case in a two-dimensional synthetic heterogeneous aquifer and a field-scale bioremediation experiment conducted at Oak Ridge, Tennessee. The field application indicates that ethanol degradation for U(VI)-bioremediation is better approximated by zero-order reaction kinetics than first-order reaction kinetics.
Zhu, Ke; 10.1214/11-AOS895
2012-01-01T23:59:59.000Z
This paper investigates the asymptotic theory of the quasi-maximum exponential likelihood estimators (QMELE) for ARMA--GARCH models. Under only a fractional moment condition, the strong consistency and the asymptotic normality of the global self-weighted QMELE are obtained. Based on this self-weighted QMELE, the local QMELE is showed to be asymptotically normal for the ARMA model with GARCH (finite variance) and IGARCH errors. A formal comparison of two estimators is given for some cases. A simulation study is carried out to assess the performance of these estimators, and a real example on the world crude oil price is given.
Lo, Min-Hui; Famiglietti, James S; Yeh, P. J.-F.; Syed, T. H
2010-01-01T23:59:59.000Z
Calibration Using GRACE Data and Base Flow Estimates [ 17 ]ESTIMATION USING GRACE DATA base flow data. In this casemeasured GRACE data and estimated base flow simultaneously
Novel Method for Incorporating Model Uncertainties into Gravitational Wave Parameter Estimates
Christopher J. Moore; Jonathan R. Gair
2014-12-11T23:59:59.000Z
Posterior distributions on parameters computed from experimental data using Bayesian techniques are only as accurate as the models used to construct them. In many applications these models are incomplete, which both reduces the prospects of detection and leads to a systematic error in the parameter estimates. In the analysis of data from gravitational wave detectors, for example, accurate waveform templates can be computed using numerical methods, but the prohibitive cost of these simulations means this can only be done for a small handful of parameters. In this work a novel method to fold model uncertainties into data analysis is proposed; the waveform uncertainty is analytically marginalised over using with a prior distribution constructed by using Gaussian process regression to interpolate the waveform difference from a small training set of accurate templates. The method is well motivated, easy to implement, and no more computationally expensive than standard techniques. The new method is shown to perform extremely well when applied to a toy problem. While we use the application to gravitational wave data analysis to motivate and illustrate the technique, it can be applied in any context where model uncertainties exist.
Efficient Semiparametric Estimators for Nonlinear Regressions and Models under Sample Selection Bias
Kim, Mi Jeong
2012-10-19T23:59:59.000Z
. Overview of Semiparametric Theory . . . . . . . . . . . . . 2 B. The Second-order Least Squares Estimator . . . . . . . . . 3 C. Sample Selection Bias . . . . . . . . . . . . . . . . . . . . . 4 II THE EFFICIENCY OF THE SECOND-ORDER NONLIN- EAR LEAST... . . . . . . . . . . . . . . . . . . . . . . . . . . . 24 1. Semiparametric Derivation . . . . . . . . . . . . . . . 24 2. Robust Estimation Family . . . . . . . . . . . . . . . 25 3. E cient Estimation . . . . . . . . . . . . . . . . . . . 29 4. Population Density Estimation...
Importance of exposure model in estimating impacts when a water distribution system is contaminated.
Davis, M. J.; Janke, R.; Environmental Science Division; USEPA
2008-09-01T23:59:59.000Z
The quantity of a contaminant ingested by individuals using tap water drawn from a water distribution system during a contamination event depends on the concentration of the contaminant in the water and the volume of water ingested. If the concentration varies with time, the actual time of exposure affects the quantity ingested. The influence of the timing of exposure and of individual variability in the volume of water ingested on estimated impacts for a contamination event has received limited attention. We examine the significance of ingestion timing and variability in the volume of water ingested by using a number of models for ingestion timing and volume. Contaminant concentrations were obtained from simulations of an actual distribution system for cases involving contaminant injections lasting from 1 to 24 h. We find that assumptions about exposure can significantly influence estimated impacts, especially when injection durations are short and impact thresholds are high. The influence of ingestion timing and volume should be considered when assessing impacts for contamination events.
Moeller, M. P.; Urbanik, II, T.; Desrosiers, A. E.
1982-03-01T23:59:59.000Z
This paper describes the methodology and application of the computer model CLEAR (Calculates Logical Evacuation And Response) which estimates the time required for a specific population density and distribution to evacuate an area using a specific transportation network. The CLEAR model simulates vehicle departure and movement on a transportation network according to the conditions and consequences of traffic flow. These include handling vehicles at intersecting road segments, calculating the velocity of travel on a road segment as a function of its vehicle density, and accounting for the delay of vehicles in traffic queues. The program also models the distribution of times required by individuals to prepare for an evacuation. In order to test its accuracy, the CLEAR model was used to estimate evacuatlon tlmes for the emergency planning zone surrounding the Beaver Valley Nuclear Power Plant. The Beaver Valley site was selected because evacuation time estimates had previously been prepared by the licensee, Duquesne Light, as well as by the Federal Emergency Management Agency and the Pennsylvania Emergency Management Agency. A lack of documentation prevented a detailed comparison of the estimates based on the CLEAR model and those obtained by Duquesne Light. However, the CLEAR model results compared favorably with the estimates prepared by the other two agencies.
Martin, Timothy
-relative-humidity-based two-source (ARTS) E model that simulates the surface energy balance, soil water balanceGlobal estimation of evapotranspiration using a leaf area index-based surface energy and water balance model H. Yan a, , S.Q. Wang b , D. Billesbach c , W. Oechel d , J.H. Zhang e , T. Meyers f , T
Chen, Jinsong
Joint inversion of seismic AVO and EM data for gas saturation estimation using a sampling- based hypothesis using a sampling-based stochastic model, based on a typical situation of gas exploration and EM data are obtained from one-dimensional (or layered) models, (2) the thickness and electrical
Post, Ellen S.; Grambsch, A.; Weaver, C. P.; Morefield, Philip; Huang, Jin; Leung, Lai-Yung R.; Nolte, Christopher G.; Adams, P. J.; Liang, Xin-Zhong; Zhu, J.; Mahoney, Hardee
2012-11-01T23:59:59.000Z
Future climate change may cause air quality degradation via climate-induced changes in meteorology, atmospheric chemistry, and emissions into the air. Few studies have explicitly modeled the potential relationships between climate change, air quality, and human health, and fewer still have investigated the sensitivity of estimates to the underlying modeling choices.
Galtchouk, Leonid
2008-01-01T23:59:59.000Z
An adaptive nonparametric estimation procedure is constructed for the estimation problem of heteroscedastic regression when the noise variance depends on the unknown regression. A non-asymptotic upper bound for a quadratic risk (an oracle inequality) is constructed.
Collins, D E; Gammon, J; Shaw, M L
1980-01-01T23:59:59.000Z
The Capital Requirements Estimating Model for the Electric Utilities (CREMOD) is a system of programs and data files used to estimate the capital requirements of the electric utility industry for each year between the current one and 1990. CREMOD disaggregates new electric plant capacity levels from the Mid-term Energy Forecasting System (MEFS) Integrating Model solution over time using actual projected commissioning dates. It computes the effect on aggregate capital requirements of dispersal of new plant and capital expenditures over relatively long construction lead times on aggregate capital requirements for each year. Finally, it incorporates the effects of real escalation in the electric utility construction industry on these requirements and computes the necessary transmission and distribution expenditures. This model was used in estimating the capital requirements of the electric utility sector. These results were used in compilation of the aggregate capital requirements for the financing of energy development as published in the 1978 Annual Report to Congress. This volume, Vol. I, explains CREMOD's methodology, functions, and applications.
Ely, Gregory
2013-01-01T23:59:59.000Z
In this paper we present a novel technique for micro-seismic localization using a group sparse penalization that is robust to the focal mechanism of the source and requires only a velocity model of the stratigraphy rather than a full Green's function model of the earth's response. In this technique we construct a set of perfect delta detector responses, one for each detector in the array, to a seismic event at a given location and impose a group sparsity across the array. This scheme is independent of the moment tensor and exploits the time compactness of the incident seismic signal. Furthermore we present a method for improving the inversion of the moment tensor and Green's function when the geometry of seismic array is limited. In particular we demonstrate that both Tikhonov regularization and truncated SVD can improve the recovery of the moment tensor and be robust to noise. We evaluate our algorithm on synthetic data and present error bounds for both estimation of the moment tensor as well as localization...
ARM Climate Modeling Best Estimate Data, A New Data Product for Climate Studies
Xie, Shaocheng [Lawrence Livermore National Laboratory (LLNL); McCoy, Renata B. [Lawrence Livermore National Laboratory (LLNL); Klein, Stephen A. [Lawrence Livermore National Laboratory (LLNL); Cederwall, Richard T. [Lawrence Livermore National Laboratory (LLNL); Wiscombe, Warren J. [Brookhaven National Laboratory (BNL); Clothiaux, Eugene E. [Pennsylvania State University, University Park, PA; Gaustad, Krista L. [Pacific Northwest National Laboratory (PNNL); Golaz, Jean-Christophe [NOAA Geophysical Fluid Dynamics Laboratory (GFDL), Princeton, NJ; Shamblin, Stefanie H [ORNL; Jensen, Michael P. [Brookhaven National Laboratory (BNL); Johnson, Karen L. [Brookhaven National Laboratory (BNL); Lin, Yanluan [NOAA Geophysical Fluid Dynamics Laboratory (GFDL), Princeton, NJ; Long, Charles N. [Pacific Northwest National Laboratory (PNNL); Mather, James H. [Pacific Northwest National Laboratory (PNNL); McCord, Raymond A [ORNL; McFarlane, Sally A. [Pacific Northwest National Laboratory (PNNL); Palanisamy, Giri [ORNL; Shi, Yan [Pacific Northwest National Laboratory (PNNL); Turner, David D. [University of Wisconsin, Madison
2010-01-01T23:59:59.000Z
The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Program (www.arm.gov) was created in 1989 to address scientific uncertainties related to global climate change, with a focus on the crucial role of clouds and their influence on the transfer of radiation in the atmosphere. A central activity is the acquisition of detailed observations of clouds and radiation, as well as related atmospheric variables for climate model evaluation and improvement. Since 1992, ARM has established six permanent ARM Climate Research Facility (ACRF) sites and deployed an ARM Mobile Facility (AMF) in diverse climate regimes around the world (Fig. 1) to perform long-term continuous field measurements. The time record of ACRF data now exceeds a decade at most ACRF fixed sites and ranges from several months to one year for AMF deployments. Billions of measurements are currently stored in millions of data files in the ACRF Data Archive. The long-term continuous ACRF data provide invaluable information to improve our understanding of the interaction between clouds and radiation, and an observational basis for model validation and improvement and climate studies. Given the huge number of data files and current diversity of archived ACRF data structures, however, it can be difficult for an outside user such as a climate modeler to quickly find the ACRF data product(s) that best meets their research needs. The required geophysical quantities may exist in multiple data streams, and over the history of ACRF operations, the measurements could be obtained by a variety of instruments, reviewed with different levels of data quality assurance, or derived using different algorithms. In addition, most ACRF data are stored in daily-based files with a temporal resolution that ranges from a few seconds to a few minutes, which is much finer than that sought by some users. Therefore, it is not as convenient for data users to perform quick comparisons over large spans of data, and this can hamper the use of ACRF data by the climate community. To make ACRF data better serve the needs of climate studies and model development, ARM has developed a data product specifically tailored for use by the climate community. The new data product, named the Climate Modeling Best Estimate (CMBE) dataset, assembles those quantities that are both well observed by ACRF over many years and are often used in model evaluation into one single dataset. The CMBE product consists of hourly averages and thus has temporal resolution comparable to a typical resolution used in climate model output. It also includes standard deviations within the averaged hour and quality control flags for the selected quantities to indicate the temporal variability and data quality. Since its initial release in February 2008, the new data product has quickly drawn the attention of the climate modeling community. It is being used for model evaluation by two major U.S. climate modeling centers, the National Center for Atmospheric Research (NCAR) and the Geophysical Fluid Dynamics Laboratory (GFDL). The purpose of this paper is to provide an overview of CMBE data and a few examples that demonstrate the potential value of CMBE data for climate modeling and in studies of cloud processes and climate variability and change.
Logue, J. M.; Turner, W. J.N.; Walker, I. S.; Singer, B. C.
2015-01-01T23:59:59.000Z
Changing the air exchange rate of a home (the sum of the infiltration and mechanical ventilation airflow rates) affects the annual thermal conditioning energy. Large-scale changes to air exchange rates of the housing stock can significantly alter the residential sector's energy consumption. However, the complexity of existing residential energy models is a barrier to the accurate quantification of the impact of policy changes on a state or national level. The Incremental Ventilation Energy (IVE) model developed in this study combines the output of simple air exchange models with a limited set of housing characteristics to estimate the associated change in energy demand of homes. The IVE model was designed specifically to enable modellers to use existing databases of housing characteristics to determine the impact of ventilation policy change on a population scale. The IVE model estimates of energy change when applied to US homes with limited parameterisation are shown to be comparable to the estimates of a well-validated, complex residential energy model.
Borchers, Brian
JOURNAL OF GEOPHYSICAL RESEARCH, VOL. ???, XXXX, DOI:10.1029/, Efficient stochastic estimation of the model resolution1 matrix diagonal and generalized crossÂvalidation for2 large geophysical inverse and Environmental Science and Geophysical Research Cen- ter, New Mexico Institute of Mining and Technology, 801
Lithium-Ion battery State of Charge estimation with a Kalman Filter based on a electrochemical model
Stefanopoulou, Anna
Lithium-Ion battery State of Charge estimation with a Kalman Filter based on a electrochemical model Domenico Di Domenico, Giovanni Fiengo and Anna Stefanopoulou Abstract-- Lithium-ion battery hybrid electric vehicles (HEV). In most cases the lithium-ion battery performance plays an important role
Boyer, Edmond
to explic- itly represent the energy fluxes of four surface components of agricultural fields including bare in north- western Mexico during the 2007-2008 agricultural season. Input data are composed of ASTERAn image-based four-source surface energy balance model to estimate crop evapotranspiration from
Hollinger, D. [USDA Forest Service; Ollinger, S. V. [University of Hew Hampshire; Richardson, A. D. [University of Hew Hampshire; Martin, M. E. [University of New Hampshire; Meyers, T. P. [NOAA ATDD; Dail, D. B. [University of Maine; Scott, N. A. [Queens University, Kingston, ON, Canada; Arkebauer, T. J. [University of Nebraska, Lincoln; Baldocchi, D. D. [University of California, Berkeley; Clark, K. L. [USDA Forest Service; Curtis, Peter [Ohio State University, The, Columbus; Davis, K. J. [Pennsylvania State University; Desai, Desai Ankur R. [University of Wisconsin, Madison; Dragoni, Danilo [Indiana University; Goulden, M. L. [University of California, Irvine; Gu, Lianhong [ORNL; Katul, G. G. [Duke University; Pallardy, Stephen G. [University of Missouri; Pawu, K. T. [University of California, Davis; Schmid, H. P. [IFU, FZK IMK, Institute of Meteorology & Climate, Garmisch Partenkirchen, Germany; Stoy, P. C. [University of Edinburgh; Suyker, A. E. [University of Nebraska, Lincoln; Verma, Shashi [University of Nebraska
2009-02-01T23:59:59.000Z
Vegetation albedo is a critical component of the Earth s climate system, yet efforts to evaluate and improve albedo parameterizations in climate models have lagged relative to other aspects of model development. Here, we calculated growing season albedos for deciduous and evergreen forests, crops, and grasslands based on over 40 site-years of data from the AmeriFlux network and compared them with estimates presently used in the land surface formulations of a variety of climate models. Generally, the albedo estimates used in land surface models agreed well with this data compilation. However, a variety of models using fixed seasonal estimates of albedo overestimated the growing season albedo of northerly evergreen trees. In contrast, climatemodels that rely on a common two-stream albedo submodel provided accurate predictions of boreal needle-leaf evergreen albedo but overestimated grassland albedos. Inverse analysis showed that parameters of the two-stream model were highly correlated. Consistent with recent observations based on remotely sensed albedo, the AmeriFlux dataset demonstrated a tight linear relationship between canopy albedo and foliage nitrogen concentration (for forest vegetation: albedo 50.0110.071%N, r250.91; forests, grassland, and maize: albedo50.0210.067%N, r250.80). However, this relationship saturated at the higher nitrogen concentrations displayed by soybean foliage. We developed similar relationships between a foliar parameter used in the two-stream albedo model and foliage nitrogen concentration. These nitrogen-based relationships can serve as the basis for a new approach to land surface albedo modeling that simplifies albedo estimation while providing a link to other important ecosystem processes.
Sahu, Sujit K
for estimating the health effects of air pollution Duncan Lee1, , Alastair Rushworth1 and Sujit K. Sahu2 . 1.Lee@glasgow.ac.uk Summary: Estimation of the long-term health effects of air pollution is a challenging task, especially effects confound the effects of air pollution, which are also globally smooth. To avoid this collinearity
Convolution particle filtering for parameter estimation in general state-space models
Paris-Sud XI, UniversitÃ© de
of these aspects [6] [4]. The second approach takes place in a classical Bayesian framework, a prior probability suited, given the context of parameter estimation. Firstly the usual non Bayesian statistical estimates results in practice but suffer from an absence of theoretical backing. The particle filters propose a good
Parameter Estimation of Dynamic Air-conditioning Component Models Using Limited Sensor Data
Hariharan, Natarajkumar
2011-08-08T23:59:59.000Z
This thesis presents an approach for identifying critical model parameters in dynamic air-conditioning systems using limited sensor information. The expansion valve model and the compressor model parameters play a crucial role in the system model...
A review of "The Public Mirror: Molière and the Social Commerce of Depiction." by Larry F. Norman
Kiki Gounaridou
2002-01-01T23:59:59.000Z
enough been addressed directly, despite the number of books and articles in recent years that have taken for granted the impor- tance of coteries and other literary communities in Early Modern England. Larry F. Norman. The Public Mirror: Moli...?re and the Social Com- merce of Depiction. Chicago and London: University of Chicago Press, 1999. vii + 226 pp. $40. Review by KIKI GOUNARIDOU, SMITH COLLEGE. In The Public Mirror, Larry Norman?s intention is to un- cover the aesthetic and social conditions...
ARM Climate Modeling Best Estimate from Nauru (ARMBE-CLDRAD TWPC2 V2.1)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate from Nauru (ARMBE-CLDRAD TWPC1)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate Lamont, OK (ARMBE-CLDRAD SGPC1)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate from Nauru (ARMBE-CLDRAD TWPC2)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate Barrow, AK (ARMBE-CLDRAD NSAC1 V2.1)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate Lamont, OK (ARMBE-CLDRAD SGPC1)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-CLDRAD [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected cloud and radiation relevant quantities from ACRF observations
ARM Climate Modeling Best Estimate from Nauru (ARMBE-CLDRAD TWPC3)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate Barrow, AK (ARMBE-CLDRAD NSAC1)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
A BIOMASS-BASED MODEL TO ESTIMATE THE PLAUSIBILITY OF EXOPLANET BIOSIGNATURE GASES
Seager, Sara
Biosignature gas detection is one of the ultimate future goals for exoplanet atmosphere studies. We have created a framework for linking biosignature gas detectability to biomass estimates, including atmospheric photochemistry ...
ARM Climate Modeling Best Estimate Barrow, AK (ARMBE-ATM NSAC1)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate From Darwin, AU (ARMBE-ATM TWPC3)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate From Manus Island, PNG (ARMBE-ATM TWPC1)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate Lamont, OK (ARMBE-ATM SGPC1)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate From Nauru (ARMBE-ATM TWPC2)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate From Darwin, AU (ARMBE-ATM TWPC2)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate Barrow, AK (ARMBE-ATM NSAC1 V4)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
Melanoma costs: A dynamic model comparing estimated overall costs of various clinical stages
Alexandrescu, Doru Traian
2009-01-01T23:59:59.000Z
AL. Trends in treatment costs for localized prostate cancer:R, Elkin EP, et al. Cumulative cost pattern comparison ofAn estimate of the annual direct cost of treating cutaneous
ARM Climate Modeling Best Estimate Barrow, AK (ARMBE-ATM NSAC1 V4)
McCoy, Renata; Xie, Shaocheng
2013-12-26T23:59:59.000Z
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate from Nauru (ARMBE-CLDRAD TWPC1)
McCoy, Renata; Xie, Shaocheng
2012-05-14T23:59:59.000Z
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate Lamont, OK (ARMBE-CLDRAD SGPC1)
McCoy, Renata; Xie, Shaocheng
2012-02-20T23:59:59.000Z
The ARM CMBE-CLDRAD [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected cloud and radiation relevant quantities from ACRF observations
ARM Climate Modeling Best Estimate From Darwin, AU (ARMBE-ATM TWPC2)
McCoy, Renata; Xie, Shaocheng
2013-12-26T23:59:59.000Z
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate From Manus Island, PNG (ARMBE-ATM TWPC1)
McCoy, Renata; Xie, Shaocheng
2012-05-14T23:59:59.000Z
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate From Darwin, AU (ARMBE-ATM TWPC3)
McCoy, Renata; Xie, Shaocheng
2013-12-26T23:59:59.000Z
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate from Nauru (ARMBE-CLDRAD TWPC3)
McCoy, Renata; Xie, Shaocheng
2012-05-14T23:59:59.000Z
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate from Nauru (ARMBE-CLDRAD TWPC2)
McCoy, Renata; Xie, Shaocheng
2012-05-14T23:59:59.000Z
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate From Darwin, AU (ARMBE-ATM TWPC3)
McCoy, Renata; Xie, Shaocheng
2013-12-27T23:59:59.000Z
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate Lamont, OK (ARMBE-ATM SGPC1)
McCoy, Renata; Xie, Shaocheng
2012-05-14T23:59:59.000Z
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate Lamont, OK (ARMBE-ATM SGPC1)
McCoy, Renata; Xie, Shaocheng
2013-12-26T23:59:59.000Z
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate Barrow, AK (ARMBE-CLDRAD NSAC1)
McCoy, Renata; Xie, Shaocheng
2012-05-14T23:59:59.000Z
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate Lamont, OK (ARMBE-ATM SGPC1)
McCoy, Renata; Xie, Shaocheng
2011-12-13T23:59:59.000Z
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate Lamont, OK (ARMBE-CLDRAD SGPC1)
McCoy, Renata; Xie, Shaocheng
2012-05-14T23:59:59.000Z
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate From Manus Island, PNG (ARMBE-ATM TWPC1)
McCoy, Renata; Xie, Shaocheng
2013-12-26T23:59:59.000Z
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
Efficient Hydraulic State Estimation Technique Using Reduced Models of Urban Water Networks
Preis, Ami
This paper describes and demonstrates an efficient method for online hydraulic state estimation in urban water networks. The proposed method employs an online predictor-corrector (PC) procedure for forecasting future water ...
Load Modeling and State Estimation Methods for Power Distribution Systems: Final Report
Tom McDermott
2010-05-07T23:59:59.000Z
The project objective was to provide robust state estimation for distribution systems, comparable to what has been available on transmission systems for decades. This project used an algorithm called Branch Current State Estimation (BCSE), which is more effective than classical methods because it decouples the three phases of a distribution system, and uses branch current instead of node voltage as a state variable, which is a better match to current measurement.
Byrd, Jimmy
2010-01-14T23:59:59.000Z
The purpose of the study was to examine multilevel regression models in the context of multilevel structural equation modeling (SEM) in terms of accuracy of parameter estimates, standard errors, and fit indices in normal ...
Fallon, Michael Brooks
2012-11-12T23:59:59.000Z
to assess the deformation demand on asymmetric offshore jacket platforms subject to wave and current loadings. The probabilistic model is constructed by adding correction terms and a model error to an existing deterministic deformation demand model...
Models for estimating saturation flow and maximum demand at closely spaced intersections
Nanduri, Sreelata
1995-01-01T23:59:59.000Z
This thesis describes models for saturation flow and maximum demand at closely spaced intersections. The effects of queue interaction between these two intersections are taken into account in both models. The saturation flow model is based...
Parameter Estimation of Dynamic Air-conditioning Component Models Using Limited Sensor Data
Hariharan, Natarajkumar
2011-08-08T23:59:59.000Z
This thesis presents an approach for identifying critical model parameters in dynamic air-conditioning systems using limited sensor information. The expansion valve model and the compressor model parameters play a crucial ...
LBNL-XXXXX | Logue et al., Evaluation of an Incremental Ventilation Energy Model for Estimating Impacts of Air Sealing and Mechanical Ventilation 1 Evaluation of an Incremental Ventilation Energy Model for Estimating Impacts of Air Sealing and Mechanical Ventilation Jennifer M. Logue, William J. N
Tang, Robert Y., E-mail: rx-tang@laurentian.ca [Biomolecular Sciences Program, Laurentian University, 935 Ramsey Lake Road, Sudbury, Ontario P3E 2C6 (Canada); Laamanen, Curtis, E-mail: cx-laamanen@laurentian.ca; McDonald, Nancy, E-mail: mcdnancye@gmail.com [Department of Physics, Laurentian University, 935 Ramsey Lake Road, Sudbury, Ontario P3E 2C6 (Canada)] [Department of Physics, Laurentian University, 935 Ramsey Lake Road, Sudbury, Ontario P3E 2C6 (Canada); LeClair, Robert J., E-mail: rleclair@laurentian.ca [Department of Physics, Laurentian University, 935 Ramsey Lake Road, Sudbury, Ontario P3E 2C6, Canada and Biomolecular Sciences Program, Laurentian University, 935 Ramsey Lake Road, Sudbury, Ontario P3E 2C6 (Canada)
2014-05-15T23:59:59.000Z
Purpose: Develop a method to subtract fat tissue contributions to wide-angle x-ray scatter (WAXS) signals of breast biopsies in order to estimate the differential linear scattering coefficients ?{sub s} of fatless tissue. Cancerous and fibroglandular tissue can then be compared independent of fat content. In this work phantom materials with known compositions were used to test the efficacy of the WAXS subtraction model. Methods: Each sample 5 mm in diameter and 5 mm thick was interrogated by a 50 kV 2.7 mm diameter beam for 3 min. A 25 mm{sup 2} by 1 mm thick CdTe detector allowed measurements of a portion of the ? = 6° scattered field. A scatter technique provided means to estimate the incident spectrum N{sub 0}(E) needed in the calculations of ?{sub s}[x(E, ?)] where x is the momentum transfer argument. Values of ?{sup ¯}{sub s} for composite phantoms consisting of three plastic layers were estimated and compared to the values obtained via the sum ?{sup ¯}{sub s}{sup ?}(x)=?{sub 1}?{sub s1}(x)+?{sub 2}?{sub s2}(x)+?{sub 3}?{sub s3}(x), where ?{sub i} is the fractional volume of the ith plastic component. Water, polystyrene, and a volume mixture of 0.6 water + 0.4 polystyrene labelled as fibphan were chosen to mimic cancer, fat, and fibroglandular tissue, respectively. A WAXS subtraction model was used to remove the polystyrene signal from tissue composite phantoms so that the ?{sub s} of water and fibphan could be estimated. Although the composite samples were layered, simulations were performed to test the models under nonlayered conditions. Results: The well known ?{sub s} signal of water was reproduced effectively between 0.5 < x < 1.6 nm{sup ?1}. The ?{sup ¯}{sub s} obtained for the heterogeneous samples agreed with ?{sup ¯}{sub s}{sup ?}. Polystyrene signals were subtracted successfully from composite phantoms. The simulations validated the usefulness of the WAXS models for nonlayered biopsies. Conclusions: The methodology to measure ?{sub s} of homogeneous samples was quantitatively accurate. Simple WAXS models predicted the probabilities for specific x-ray scattering to occur from heterogeneous biopsies. The fat subtraction model can allow ?{sub s} signals of breast cancer and fibroglandular tissue to be compared without the effects of fat provided there is an independent measurement of the fat volume fraction ?{sub f}. Future work will consist of devising a quantitative x-ray digital imaging method to estimate ?{sub f} in ex vivo breast samples.
Efficient Models for the Evaluation and Estimation of the Gravity Field
Born, George
models. Problem Cubed-Sphere Gravity Model Designed for Fast Evaluation Orbit Propagation/FORMOSAT-3 4 #12;The spherical harmonic gravity model dominates force model execution time 0 10 20 30 40 50 60 Two-Body + Overhead Precession Nutation Gravity (36x36) Lunar-Solar Drag SRP Jacobian (36x36
Richardson, Andrew D.
and earth system models, especially for long-term (multian- nual and greater) simulations. Data assimilation
High and Low Temperature Series Estimates for the Critical Temperature of the 3D Ising Model
Adler, Joan
High and Low Temperature Series Estimates for the Critical Temperature Abstract We have analysed low and high temperature series expansions for the three high temperature series yields Kc = 0.221659 +0.000002-0.000005and from the 32 term low
Huybers, Peter
Geology and Geophysics: Geomagnetism (1550); 3220 Mathematical Geophysics: Nonlinear dynamics; 4267 of ages to measurements and events recorded in marine and ice cores as well as to a variety of isolated. [3] The currently favored method for estimating Pleisto- cene age is orbital tuning [e.g., Imbrie et
Global oceanic rainfall estimation from AMSR-E data based on a radiative transfer model
Jin, Kyoung-Wook
2006-04-12T23:59:59.000Z
retrieval uncertainties. The algorithm uses six channels (dual polarizations at 36.5, 18.7 and 10.65GHz) and retrieves rain rates on a pixel-by-pixel basis. Monthly rain totals are estimated by summing average rain rates computed by merging six rain rates...
Developing a Cost Model and Methodology to Estimate Capital Costs for Thermal Energy Storage
Glatzmaier, G.
2011-12-01T23:59:59.000Z
This report provides an update on the previous cost model for thermal energy storage (TES) systems. The update allows NREL to estimate the costs of such systems that are compatible with the higher operating temperatures associated with advanced power cycles. The goal of the Department of Energy (DOE) Solar Energy Technology Program is to develop solar technologies that can make a significant contribution to the United States domestic energy supply. The recent DOE SunShot Initiative sets a very aggressive cost goal to reach a Levelized Cost of Energy (LCOE) of 6 cents/kWh by 2020 with no incentives or credits for all solar-to-electricity technologies.1 As this goal is reached, the share of utility power generation that is provided by renewable energy sources is expected to increase dramatically. Because Concentrating Solar Power (CSP) is currently the only renewable technology that is capable of integrating cost-effective energy storage, it is positioned to play a key role in providing renewable, dispatchable power to utilities as the share of power generation from renewable sources increases. Because of this role, future CSP plants will likely have as much as 15 hours of Thermal Energy Storage (TES) included in their design and operation. As such, the cost and performance of the TES system is critical to meeting the SunShot goal for solar technologies. The cost of electricity from a CSP plant depends strongly on its overall efficiency, which is a product of two components - the collection and conversion efficiencies. The collection efficiency determines the portion of incident solar energy that is captured as high-temperature thermal energy. The conversion efficiency determines the portion of thermal energy that is converted to electricity. The operating temperature at which the overall efficiency reaches its maximum depends on many factors, including material properties of the CSP plant components. Increasing the operating temperature of the power generation system leads to higher thermal-to-electric conversion efficiency. However, in a CSP system, higher operating temperature also leads to greater thermal losses. These two effects combine to give an optimal system-level operating temperature that may be less than the upper operating temperature limit of system components. The overall efficiency may be improved by developing materials, power cycles, and system-integration strategies that enable operation at elevated temperature while limiting thermal losses. This is particularly true for the TES system and its components. Meeting the SunShot cost target will require cost and performance improvements in all systems and components within a CSP plant. Solar collector field hardware will need to decrease significantly in cost with no loss in performance and possibly with performance improvements. As higher temperatures are considered for the power block, new working fluids, heat-transfer fluids (HTFs), and storage fluids will all need to be identified to meet these new operating conditions. Figure 1 shows thermodynamic conversion efficiency as a function of temperature for the ideal Carnot cycle and 75% Carnot, which is considered to be the practical efficiency attainable by current power cycles. Current conversion efficiencies for the parabolic trough steam cycle, power tower steam cycle, parabolic dish/Stirling, Ericsson, and air-Brayton/steam Rankine combined cycles are shown at their corresponding operating temperatures. Efficiencies for supercritical steam and carbon dioxide (CO{sub 2}) are also shown for their operating temperature ranges.
Eslinger, Paul W.; Friese, Judah I.; Lowrey, Justin D.; McIntyre, Justin I.; Miley, Harry S.; Schrom, Brian T.
2014-09-01T23:59:59.000Z
Abstract The International Monitoring System (IMS) of the Comprehensive-Nuclear-Test-Ban-Treaty monitors the atmosphere for radioactive xenon leaking from underground nuclear explosions. Emissions from medical isotope production represent a challenging background signal when determining whether measured radioxenon in the atmosphere is associated with a nuclear explosion prohibited by the treaty. The Australian Nuclear Science and Technology Organisation (ANSTO) operates a reactor and medical isotope production facility in Lucas Heights, Australia. This study uses two years of release data from the ANSTO medical isotope production facility and Xe-133 data from three IMS sampling locations to estimate the annual releases of Xe-133 from medical isotope production facilities in Argentina, South Africa, and Indonesia. Atmospheric dilution factors derived from a global atmospheric transport model were used in an optimization scheme to estimate annual release values by facility. The annual releases of about 6.8×1014 Bq from the ANSTO medical isotope production facility are in good agreement with the sampled concentrations at these three IMS sampling locations. Annual release estimates for the facility in South Africa vary from 1.2×1016 to 2.5×1016 Bq and estimates for the facility in Indonesia vary from 6.1×1013 to 3.6×1014 Bq. Although some releases from the facility in Argentina may reach these IMS sampling locations, the solution to the objective function is insensitive to the magnitude of those releases.
Global oceanic rainfall estimation from AMSR-E data based on a radiative transfer model
Jin, Kyoung-Wook
2006-04-12T23:59:59.000Z
An improved physically-based rainfall algorithm was developed using AMSR-E data based on a radiative transfer model. In addition, error models were designed and embedded in the algorithm to assess retrieval errors ...
Ross, D.G.; Fox, D.G.; Dietrich, D.L.; Childs, J.E.; Marlatt, W.E.
1985-07-01T23:59:59.000Z
CITPUFF, is a puff-type dispersion model that uses a wind field calculated from a complex-terrain wind model. It accommodates a variety of source types including point, area, and line sources; calculates plume rise where applicable; and outputs a graphic display of puff trajectories and concentrations. The model is compared against models currently used for assessing air quality impacts in complex topography.
Pearce, Fred
2003-01-01T23:59:59.000Z
We use a 3-D finite difference numerical model to generate synthetic seismograms from a simple fractured reservoir
Irwin, Mark E.
2005-01-01T23:59:59.000Z
reserved. Keywords: Statistical model; Spacetime models; Air pollution; Ozone; Meteorology 1. Introduction describing the spatialtemporal behavior of ambient air pollutants such as ozone (O3) and particulate matter. Statistical spacetime models are useful for illuminating relationships between different air pollutants
Parameter Estimation and Model Discrimination for a Lithium-Ion Cell
interest in the modeling of the lithium-ion battery ever since this battery was first com- mercialized.1-18 This interest has been fueled by the combination of the fast growing lithium-ion battery market and the desire of a lithium- ion battery measured over a wide range of rates. Single-Particle Model This single-particle model
Tomkins, Andrew
of Systems]: Modeling techniques General Terms Measurement, Design Keywords Power modeling, mobile phones systems. Combined, PowerBooter and PowerTutor have the goal of opening power modeling and analysis of determining the impact of software design decisions on system energy consumption, but that barrier can
Md Desa, Zairul Nor Deana
2012-08-31T23:59:59.000Z
, test linking, equating and scaling (Kolen & Brennan, 2004), item banking, computer-based testing and computerized adaptive testing (Dras- gow & Olson-Buchanan, 1999; Mills et al., 2002; Parshall et al., 2001; van der Linden & Glas, 2000; Wainer & Dorans... decisions at student and school-level decisions (Sinharay et al., 2007; Haberman, 2008; Haberman et al., 2009; Puhan et al., 2010). The application of Bayesian approach has shown improved reliability of the overall score or subscores estimates (Kolen & Tong...
Development of a mass balance model for estimating PCB export from the lower Fox River to Green Bay
Velleux, M.; Endicott, D.
1994-01-01T23:59:59.000Z
A mass balance approach was used to model contaminant cycling in the lower Fox River from the DePere Dam to Green Bay. The objectives of this research were (1) to estimate present contaminant export from the Fox River to Green Bay, and (2) to quantify contaminant transport and fate pathways in the lower river for the study period. Specifically, a model describing the transport, fate, and export of chlorides, total suspended solids, total PCBs, and six PCB congeners for the lower Fox River was developed. Field data collected as part of the U.S. Environmental Protection Agency's Green Bay Mass Balance Study were used to calibrate the model. Model results suggest that the transport of inplace pollutants significantly contributed to the cumulative export of total PCBs over this period. Estimated total PCB transport in the Fox River during 1989 increased 60% between the dam and river mouth due to the resuspension of lower river sediments. Total suspended solids and PCB predictions are most sensitive to particle transport parameters, particularly the settling and resuspension velocities. The significant components of the total PCB mass balance are import (loading over the DePere Dam), settling, resuspension, and export to Green Bay. Volatilization, porewater transport, and point source input were not significant to the mass balance. Present point source discharges to the river are not significant total PCB sources, collectively contributing less than 6 kg of PCB to the river during the mass balance period.
A Simple Model for Estimating Water Balance and Salinity of Reservoirs and Outflow
Miyamoto, S; Yuan, F; Anand, Shilpa
2010-08-23T23:59:59.000Z
to help evaluate river management options on flow and salinity of the stream and the floodplains. The first part deals with water and salt balance in reservoirs. The primary purpose of the model is to predict outflow salinity from the reservoir... storage and inflow information in advance of the actual release. A simple two-layer model is used to describe the reservoir processes. The second part addresses water and salt transport through semi-arid river channels. A routing model referred...
Nonlinear Estimation for Model Based Fault Diagnosis of Nonlinear Chemical Systems
Qu, Chunyan
2011-02-22T23:59:59.000Z
and the unknown inputs. Using mechanistic first principle models, Raja et. al [16] have proposed an observer-based methodology for diagnosing unknown sensor faults in systems with parametric uncertainties. However, the contribution of first principles model...-based fault diagnosis approaches to industrial practice has not been pervasive due to the cost and time required to develop a sufficiently accurate process model for a com- plex chemical plant [17]. Therefore, Raja et. al [18] extended their work to sensor...
Logue, Jennifer M.
2014-01-01T23:59:59.000Z
weather files for representative cities within each climatewas modeled in the representative city for each of the sevenclimate zones and representative cities were used: 2A hot/
Estimating food consumption rates of fish using a mercury mass balance model
Rasmussen, Joseph
on stomach contents. Simple models based on the mass balance of persistent contaminants such as radioactive cesium (137 Cs), poly- chlorinated bipheny
Learning shape models for monocular human pose estimation from the Microsoft Xbox Kinect
Everingham, Mark
on the popular pictorial structure model (PSM) [8]. Fig. 1 outlines our proposal: using the PSM we infer 2D human
Model error estimation in composite impact response prediction using hierarchical Bayes networks
Salas Mendez, Pablo Antonio
2010-01-01T23:59:59.000Z
in Progressive Failure Analysis . . . 4.0.2 ModelingPuck and H. Schurmann, “Failure analysis of frp laminates byComposite laminate failure analysis using multi- continuum
Chan, Kung-Sik
Kalman Filter Kwang Woo Ahn Division of Biostatistics Medical College of Wisconsin, Milwaukee, WI 53226 function computed approximately via unscented Kalman filter (UKF). We derive conditions 1 #12;under which. ---------------------------- Keywords: Nonlinear time series; State-space model; Unscented Kalman filter; SIR model. 1. INTRODUCTION
Importance Sampling Methods for Estimating Convex Risk Measures in Portfolio Credit Risk Models
Grübel, Rudolf
obligors. Owing to the complexity of realistic models, quantitative risk analysis typically requires Monte the shortcomings of the industry standard Value-at-Risk (VaR). Our analysis demonstrates that standard Monte risk analysis to realistic credit portfolio models. During the past decade an intense effort has been
Hayes, Daniel J [ORNL; Turner, David P [Oregon State University, Corvallis; Stinson, Graham [Pacific Forestry Centre, Canadian Forest Service; Mcguire, David [University of Alaska; Wei, Yaxing [ORNL; West, Tristram O. [Joint Global Change Research Institute, PNNL; Heath, Linda S. [USDA Forest Service; De Jong, Bernardus [ECOSUR; McConkey, Brian G. [Agriculture and Agri-Food Canada; Birdsey, Richard A. [U.S. Department of Agriculture Forest Service; Kurz, Werner [Canadian Forest Service; Jacobson, Andrew [NOAA ESRL and CIRES; Huntzinger, Deborah [University of Michigan; Pan, Yude [U.S. Department of Agriculture Forest Service; Post, Wilfred M [ORNL; Cook, Robert B [ORNL
2012-01-01T23:59:59.000Z
We develop an approach for estimating net ecosystem exchange (NEE) using inventory-based information over North America (NA) for a recent 7-year period (ca. 2000 2006). The approach notably retains information on the spatial distribution of NEE, or the vertical exchange between land and atmosphere of all non-fossil fuel sources and sinks of CO2, while accounting for lateral transfers of forest and crop products as well as their eventual emissions. The total NEE estimate of a 327 252 TgC yr1 sink for NA was driven primarily by CO2 uptake in the Forest Lands sector (248 TgC yr1), largely in the Northwest and Southeast regions of the US, and in the Crop Lands sector (297 TgC yr1), predominantly in the Midwest US states. These sinks are counteracted by the carbon source estimated for the Other Lands sector (+218 TgC yr1), where much of the forest and crop products are assumed to be returned to the atmosphere (through livestock and human consumption). The ecosystems of Mexico are estimated tobe a small net source (+18 TgC yr1) due to land use change between 1993 and 2002. We compare these inventorybased estimates with results from a suite of terrestrial biosphere and atmospheric inversion models, where the mean continental-scale NEE estimate for each ensemble is 511 TgC yr1 and 931 TgC yr1, respectively. In the modeling approaches, all sectors, including Other Lands, were generally estimated to be a carbon sink, driven in part by assumed CO2 fertilization and/or lack of consideration of carbon sources from disturbances and product emissions. Additional fluxes not measured by the inventories, although highly uncertain, could add an additional 239 TgC yr1 to the inventory-based NA sink estimate, thus suggesting some convergence with the modeling approaches.
Peinke, Joachim
Stochastic model for indirect estimation of instantaneous and cumulative loads in wind turbines present our recent findings for estimating instantaneous and cumulative loads in singles wind turbines at single wind turbines, driven by wind speed measurements. Through a standard fatigue analysis of data
Wang, Peijuan; Xie, Donghui; Zhou, Yuyu; E, Youhao; Zhu, Qijiang
2014-01-16T23:59:59.000Z
The ecological structure in the arid and semi-arid region of Northwest China with forest, grassland, agriculture, Gobi, and desert, is complex, vulnerable, and unstable. It is a challenging and sustaining job to keep the ecological structure and improve its ecological function. Net primary productivity (NPP) modeling can help to improve the understanding of the ecosystem, and therefore, improve ecological efficiency. The boreal ecosystem productivity simulator (BEPS) model provides the possibility of NPP modeling in terrestrial ecosystem, but it has some limitations for application in arid and semi-arid regions. In this paper we improve the BEPS model, in terms of its water cycle by adding the processes of infiltration and surface runoff, to be applicable in arid and semi-arid regions. We model the NPP of forest, grass, and crop in Gansu Province as an experimental area in Northwest China in 2003 using the improved BEPS model, parameterized with moderate resolution remote sensing imageries and meteorological data. The modeled NPP using improved BEPS agrees better with the ground measurements in Qilian Mountain than that with original BEPS, with a higher R2 of 0.746 and lower root mean square error (RMSE) of 46.53 gC/m2 compared to R2 of 0.662 and RMSE of 60.19 gC/m2 from original BEPS. The modeled NPP of three vegetation types using improved BEPS show evident differences compared to that using original BEPS, with the highest difference ratio of 9.21% in forest and the lowest value of 4.29% in crop. The difference ratios between different vegetation types lie on the dependence on natural water sources. The modeled NPP in five geographic zones using improved BEPS are higher than those with original BEPS, with higher difference ratio in dry zones and lower value in wet zones.
Masuda, H.; Claridge, D.
2012-01-01T23:59:59.000Z
, cooling and heating and weather data using multiple linear regression models based on the simplified steady-state energy balance for a whole building. Two approaches using different response variables: the energy balance load (EBL) and the building thermal...
Seismic Scattering Attributes to Estimate Reservoir Fracture Density: A Numerical Modeling Study
Pearce, Frederick Douglas
We use a 3-D finite difference numerical model to generate synthetic seismograms from a simple fractured reservoir containing evenly-spaced, discrete, vertical fracture zones. The fracture zones are represented using a ...
Efficient Bayesian estimates for discrimination among topologically different systems biology models
Hagen, David Robert
A major effort in systems biology is the development of mathematical models that describe complex biological systems at multiple scales and levels of abstraction. Determining the topology—the set of interactions—of a ...
On-line Hydraulic State Estimation in Urban Water Networks Using Reduced Models
Preis, Ami
A Predictor-Corrector (PC) approach for on-line forecasting of water usage in an urban water system is presented and demonstrated. The M5 Model-Trees algorithm is used to predict water demands and Genetic Algorithms (GAs) ...
Parameter Estimation and Capacity Fade Analysis of Lithium-Ion Batteries Using Reformulated Models
Braatz, Richard D.
Many researchers have worked to develop methods to analyze and characterize capacity fade in lithium-ion batteries. As a complement to approaches to mathematically model capacity fade that require detailed understanding ...
Masuda, H.; Claridge, D.
2012-01-01T23:59:59.000Z
, cooling and heating and weather data using multiple linear regression models based on the simplified steady-state energy balance for a whole building. Two approaches using different response variables: the energy balance load (EBL) and the building thermal...
Zamanian, S. Ahmad
2013-01-01T23:59:59.000Z
In many geophysical inverse problems, smoothness assumptions on the underlying geology are utilized to mitigate the effects of poor resolution and noise in the data and to improve the quality of the inferred model parameters. ...
Seismic scattering attributes to estimate reservoir fracture density : a numerical modeling study
Pearce, Frederick D. (Frederick Douglas), 1978-
2003-01-01T23:59:59.000Z
We use a 3-D finite difference numerical model to generate synthetic seismograms from a simple fractured reservoir containing evenly-spaced, discrete, vertical fracture zones. The fracture zones are represented using a ...
k-step Bootstrap Bias Correction for Fixed Effects Estimators in Nonlinear Panel Models
Sun, Yixiao; Kim, Min Seong
2009-01-01T23:59:59.000Z
MacKinnon, J. (1999). Bootstrap Testing in Nonlinear Models.J. (2002). Fast Double Bootstrap Tests of Nonnested LinearImproving the Reliability of Bootstrap Tests with the Fast
Evolution of Meteorological Base Models for Estimating Hourly Global Solar Radiation in Texas
Kim, H.; Baltazar, J.C.; Haberl, J.S
2013-01-01T23:59:59.000Z
such as San Antonio and Victoria, the statistical indices show similar values for either model. These findings are shown in Figure 3, where the climate zones categorized by the 2009 International Energy Conservation Code (IECC) [16] are also included... ESL-PA-13-11-01 Available online at www.sciencedirect.com Energy Procedia 00 (2013) 000–000 www.elsevier.com/locate/procedia 2013 ISES Solar World Congress Evaluation of Meteorological Base Models...
Assessing Invariance of Factor Structures and Polytomous Item Response Model Parameter Estimates
Reyes, Jennifer McGee
2012-02-14T23:59:59.000Z
.e., identical items, different people) for the homogenous graded response model (Samejima, 1969) and the partial credit model (Masters, 1982)? To evaluate measurement invariance using IRT methods, the item discrimination and item difficulty parameters... obtained from the GRM need to be equivalent across datasets. The YFCY02 and YFCY03 GRM item discrimination parameters (slope) correlation was 0.828. The YFCY02 and YFCY03 GRM item difficulty parameters (location) correlation was 0...
A comparative study of analytical models to estimate the LNAPL mound formation
Ahmed, Ashfaq
1994-01-01T23:59:59.000Z
developed. Even though these models are based on various as- sumptions, they are useful as tools in evaluating the spreading of the free oil phase during sn oil spill. The spreading depends on many factors, such as leak volume, type of petroleum product..., hydrogeological conditions, and hydraulic properties of the medium as well as the oil. Among the various modeling approaches to predict spill migration, the sharp interface approach has been widely examined due to its simplicity for homogeneous media...
Thompson, R. L.
This study examines N[subscript 2]O emission estimates from five different atmospheric inversion frameworks based on chemistry transport models (CTMs). The five frameworks differ in the choice of CTM, meteorological data, ...
Stukey, Jared D.
2011-02-22T23:59:59.000Z
The overall goal of this study was to develop a framework for using airborne lidar to derive inputs for the SPB infestation growth model TAMBEETLE. The specific objectives were (1) to estimate individual tree characteristics of XY location...
Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]
1997-03-28T23:59:59.000Z
Based on the project's scope, the purpose of the estimate, and the availability of estimating resources, the estimator can choose one or a combination of techniques when estimating an activity or project. Estimating methods, estimating indirect and direct costs, and other estimating considerations are discussed in this chapter.
Control of Airborne Wind Energy Systems Based on Nonlinear Model Predictive Control & Moving arising in the Airborne Wind Energy paradigm, an essential one is the control of the tethered airfoil], [3], the Airborne Wind Energy (AWE) paradigm shift proposes to get rid of the structural elements
Maximum Likelihood Estimation for Probit-Linear Mixed Models with Correlated Random Effects
Du, Jie
Jennifer S. K. Chan and Anthony Y. C. Kuk Department of Statistics, University of New South Wales, Sydney 2052, Australia The probit-normal model for binary data (McCulloch, 1994, Journal of the American function, one has to integrate out the random effects, which, except for a few special cases, cannot
Computational Methods for Estimation in the Modeling of Nonlinear Elastomers \\Lambda
vibration suppression devices. Materials such as elastomers, rubberlike composites typically filled and springs. One could imagine using active fillers, such as piezoelectric, magnetic, or conductive particles [12, 16, 19, 20]). Some of these models are based on the statistical molecular theory of polymers
Measuring and Modeling Fault Density for Plume-Fault Encounter Probability Estimation
Jordan, P.D.; Oldenburg, C.M.; Nicot, J.-P.
2011-05-15T23:59:59.000Z
Emission of carbon dioxide from fossil-fueled power generation stations contributes to global climate change. Storage of this carbon dioxide within the pores of geologic strata (geologic carbon storage) is one approach to mitigating the climate change that would otherwise occur. The large storage volume needed for this mitigation requires injection into brine-filled pore space in reservoir strata overlain by cap rocks. One of the main concerns of storage in such rocks is leakage via faults. In the early stages of site selection, site-specific fault coverages are often not available. This necessitates a method for using available fault data to develop an estimate of the likelihood of injected carbon dioxide encountering and migrating up a fault, primarily due to buoyancy. Fault population statistics provide one of the main inputs to calculate the encounter probability. Previous fault population statistics work is shown to be applicable to areal fault density statistics. This result is applied to a case study in the southern portion of the San Joaquin Basin with the result that the probability of a carbon dioxide plume from a previously planned injection had a 3% chance of encountering a fully seal offsetting fault.
Deng, Zhiqun; Carlson, Thomas J.; Ploskey, Gene R.; Richmond, Marshall C.
2005-11-30T23:59:59.000Z
BioIndex testing of hydro-turbines is sought as an analog to the hydraulic index testing conducted on hydro-turbines to optimize their power production efficiency. In BioIndex testing the goal is to identify those operations within the range identified by Index testing where the survival of fish passing through the turbine is maximized. BioIndex testing includes the immediate tailrace region as well as the turbine environment between a turbine's intake trashracks and the exit of its draft tube. The US Army Corps of Engineers and the Department of Energy have been evaluating a variety of means, such as numerical and physical turbine models, to investigate the quality of flow through a hydro-turbine and other aspects of the turbine environment that determine its safety for fish. The goal is to use these tools to develop hypotheses identifying turbine operations and predictions of their biological performance that can be tested at prototype scales. Acceptance of hypotheses would be the means for validation of new operating rules for the turbine tested that would be in place when fish were passing through the turbines. The overall goal of this project is to evaluate the performance of numerical blade strike models as a tool to aid development of testable hypotheses for bioIndexing. Evaluation of the performance of numerical blade strike models is accomplished by comparing predictions of fish mortality resulting from strike by turbine runner blades with observations made using live test fish at mainstem Columbia River Dams and with other predictions of blade strike made using observations of beads passing through a 1:25 scale physical turbine model.
Quantitative Modeling and Estimation in Systems Biology using Fluorescent Reporter Systems
Bansal, Loveleena
2013-12-10T23:59:59.000Z
problem is given by (2.11) The regularization parameter can be chosen with the help of the L-Curve (Hansen, 1992) which is a plot of the norm of the residual versus the regularization term for various values of the parameter... Sampling MSE Mean Squared Error nM Nano Molar O.D. Optical Density ODE Ordinary Differential Equation PBE Population Balance Equation PBM Population Balance Model RE Relative Error S.D. Standard Deviation STAT3 Signal transducer...
Aagaard, B; Brocher, T; Dreger, D; Frankel, A; Graves, R; Harmsen, S; Hartzell, S; Larsen, S; McCandless, K; Nilsson, S; Petersson, N A; Rodgers, A; Sjogreen, B; Tkalcic, H; Zoback, M L
2007-02-09T23:59:59.000Z
We estimate the ground motions produced by the 1906 San Francisco earthquake making use of the recently developed Song et al. (2008) source model that combines the available geodetic and seismic observations and recently constructed 3D geologic and seismic velocity models. Our estimates of the ground motions for the 1906 earthquake are consistent across five ground-motion modeling groups employing different wave propagation codes and simulation domains. The simulations successfully reproduce the main features of the Boatwright and Bundock (2005) ShakeMap, but tend to over predict the intensity of shaking by 0.1-0.5 modified Mercalli intensity (MMI) units. Velocity waveforms at sites throughout the San Francisco Bay Area exhibit characteristics consistent with rupture directivity, local geologic conditions (e.g., sedimentary basins), and the large size of the event (e.g., durations of strong shaking lasting tens of seconds). We also compute ground motions for seven hypothetical scenarios rupturing the same extent of the northern San Andreas fault, considering three additional hypocenters and an additional, random distribution of slip. Rupture directivity exerts the strongest influence on the variations in shaking, although sedimentary basins do consistently contribute to the response in some locations, such as Santa Rosa, Livermore, and San Jose. These scenarios suggest that future large earthquakes on the northern San Andreas fault may subject the current San Francisco Bay urban area to stronger shaking than a repeat of the 1906 earthquake. Ruptures propagating southward towards San Francisco appear to expose more of the urban area to a given intensity level than do ruptures propagating northward.
Fisher, Kathleen
ELITE Enterprise Lead Input and Tracking Environment This tool solves the problem of tracking sales leads in a closed loop fashion, as depicted in the figure below, in a simple and novel fashion, in a web handles a variety of tasks, such as lead evaluation, lead scoring, lead distribution, alerting, reporting
Efficient Semiparametric Estimators for Nonlinear Regressions and Models under Sample Selection Bias
Kim, Mi Jeong
2012-10-19T23:59:59.000Z
(X; ) + ; where Y 2 R is the response variable, X 2 Rk is the predictor variable, 2 Rp is the unknown regression parameter and is the random error satisfying E( jX) = 0 and E( 2jX) = 2. Y and are assumed to have nite fourth moments. The parameter vector...-dimensional parameter and the model error satis es the usual mean zero assumption E( jX) = 0. In addition, they also assumed that has a constant yet unknown variance 2, that is, E( 2jX) = 2. The observa- tions are denoted (X1; Y1); : : : ; (Xn; Yn), each satis...
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
Medeiros, Stephen; Hagen, Scott; Weishampel, John; Angelo, James
2015-03-25T23:59:59.000Z
Digital elevation models (DEMs) derived from airborne lidar are traditionally unreliable in coastal salt marshes due to the inability of the laser to penetrate the dense grasses and reach the underlying soil. To that end, we present a novel processing methodology that uses ASTER Band 2 (visible red), an interferometric SAR (IfSAR) digital surface model, and lidar-derived canopy height to classify biomass density using both a three-class scheme (high, medium and low) and a two-class scheme (high and low). Elevation adjustments associated with these classes using both median and quartile approaches were applied to adjust lidar-derived elevation values closer tomore »true bare earth elevation. The performance of the method was tested on 229 elevation points in the lower Apalachicola River Marsh. The two-class quartile-based adjusted DEM produced the best results, reducing the RMS error in elevation from 0.65 m to 0.40 m, a 38% improvement. The raw mean errors for the lidar DEM and the adjusted DEM were 0.61 ± 0.24 m and 0.32 ± 0.24 m, respectively, thereby reducing the high bias by approximately 49%.« less
Greenblatt, Jeffery B.
2013-10-10T23:59:59.000Z
A California Greenhouse Gas Inventory Spreadsheet (GHGIS) model was developed to explore the impact of combinations of state policies on state greenhouse gas (GHG) and regional criteria pollutant emissions. The model included representations of all GHG- emitting sectors of the California economy (including those outside the energy sector, such as high global warming potential gases, waste treatment, agriculture and forestry) in varying degrees of detail, and was carefully calibrated using available data and projections from multiple state agencies and other sources. Starting from basic drivers such as population, numbers of households, gross state product, numbers of vehicles, etc., the model calculated energy demands by type (various types of liquid and gaseous hydrocarbon fuels, electricity and hydrogen), and finally calculated emissions of GHGs and three criteria pollutants: reactive organic gases (ROG), nitrogen oxides (NOx), and fine (2.5 ?m) particulate matter (PM2.5). Calculations were generally statewide, but in some sectors, criteria pollutants were also calculated for two regional air basins: the South Coast Air Basin (SCAB) and the San Joaquin Valley (SJV). Three scenarios were developed that attempt to model: (1) all committed policies, (2) additional, uncommitted policy targets and (3) potential technology and market futures. Each scenario received extensive input from state energy planning agencies, in particular the California Air Resources Board. Results indicate that all three scenarios are able to meet the 2020 statewide GHG targets, and by 2030, statewide GHG emissions range from between 208 and 396 MtCO2/yr. However, none of the scenarios are able to meet the 2050 GHG target of 85 MtCO2/yr, with emissions ranging from 188 to 444 MtCO2/yr, so additional policies will need to be developed for California to meet this stringent future target. A full sensitivity study of major scenario assumptions was also performed. In terms of criteria pollutants, targets were less well-defined, but while all three scenarios were able to make significant reductions in ROG, NOx and PM2.5 both statewide and in the two regional air basins, they may nonetheless fall short of what will be required by future federal standards. Specifically, in Scenario 1, regional NOx emissions are approximately three times the estimated targets for both 2023 and 2032, and in Scenarios 2 and 3, NOx emissions are approximately twice the estimated targets. Further work is required in this area, including detailed regional air quality modeling, in order to determine likely pathways for attaining these stringent targets.
Discretized maximum likelihood estimates for adaptive control of ergodic Markov models
Duncan, Tyrone E.; Pasik-Duncan, B.; Stettner, L.
1998-03-01T23:59:59.000Z
processes, almost optimal adaptive control AMS subject classi#12;cations. 93E35, 93C40, 60J05, 62M05 PII. S0363012996298369 1. Introduction. In many control problems the models are not completely de- scribed and there are perturbations or unmodeled dynamics....s., so by (64), (93) I1((v^n; n 2 N)) #20; lim sup n!1 1 n n?1 X i=0 Z E c(z; uiN (z))#25; #11;0 uiN (dz) + " a.s. For ! 2 ? n N it follows from (93) that (94) I1((v^n; n 2 N)) #20; lim sup n!1 1 n n?1 X i=0 1F (#22;#14;)(#11;^iN ) Z E c(z; uiN (z))#25...
Meyer, Philip D.; Ye, Ming; Rockhold, Mark L.; Neuman, Shlomo P.; Cantrell, Kirk J.
2007-07-30T23:59:59.000Z
This report to the Nuclear Regulatory Commission (NRC) describes the development and application of a methodology to systematically and quantitatively assess predictive uncertainty in groundwater flow and transport modeling that considers the combined impact of hydrogeologic uncertainties associated with the conceptual-mathematical basis of a model, model parameters, and the scenario to which the model is applied. The methodology is based on a n extension of a Maximum Likelihood implementation of Bayesian Model Averaging. Model uncertainty is represented by postulating a discrete set of alternative conceptual models for a site with associated prior model probabilities that reflect a belief about the relative plausibility of each model based on its apparent consistency with available knowledge and data. Posterior model probabilities are computed and parameter uncertainty is estimated by calibrating each model to observed system behavior; prior parameter estimates are optionally included. Scenario uncertainty is represented as a discrete set of alternative future conditions affecting boundary conditions, source/sink terms, or other aspects of the models, with associated prior scenario probabilities. A joint assessment of uncertainty results from combining model predictions computed under each scenario using as weight the posterior model and prior scenario probabilities. The uncertainty methodology was applied to modeling of groundwater flow and uranium transport at the Hanford Site 300 Area. Eight alternative models representing uncertainty in the hydrogeologic and geochemical properties as well as the temporal variability were considered. Two scenarios represent alternative future behavior of the Columbia River adjacent to the site were considered. The scenario alternatives were implemented in the models through the boundary conditions. Results demonstrate the feasibility of applying a comprehensive uncertainty assessment to large-scale, detailed groundwater flow and transport modeling and illustrate the benefits of the methodology I providing better estimates of predictive uncertiay8, quantitative results for use in assessing risk, and an improved understanding of the system behavior and the limitations of the models.
Cohen, N. [New York Univ. Medical Center, Tuxedo, NY (United States). Dept. of Environmental Medicine
1989-03-15T23:59:59.000Z
A Polonium metabolic model was derived and incorporated into a Fortran algorithm which estimates the systemic radiation dose from {sup 210}Po when applied to occupational urine bioassay data. The significance of the doses estimated are examined by defining the degree of uncertainty attached to them through comprehensive statistical testing procedures. Many parameters necessary for dosimetry calculations (such as organ partition coefficients and excretion fractions), were evaluated from metabolic studies of {sup 210}Po in non-human primates. Two tamarins and six baboons were injected intravenously with {sup 210}Po citrate. Excreta and blood samples were collected. Five of the baboons were sacrificed at times ranging from 1 day to 3 months post exposure. Complete necropsies were performed and all excreta and the majority of all skeletal and tissue samples were analyzed radiochemically for their {sup 210}Po content. The {sup 210}Po excretion rate in the baboon was more rapid than in the tamarin. The biological half-time of {sup 210}Po excretion in the baboon was approximately 15 days while in the tamarin, the {sup 210}Po excretion rate was in close agreement with the 50 day biological half-time predicted by ICRP 30. Excretion fractions of {sup 210}Po in the non-human primates were found to be markedly different from data reported elsewhere in other species, including man. A thorough review of the Po urinalysis procedure showed that significant recovery losses resulted when metabolized {sup 210}Po was deposited out of raw urine. Polonium-210 was found throughout the soft tissues of the baboon but not with the partition coefficients for liver, kidneys, and spleen that are predicted by the ICRP 30 metabolic model. A fractional distribution of 0.29 for liver, 0.07 for kidneys, and 0.006 for spleen was determined. Retention times for {sup 210}Po in tissues are described by single exponential functions with biological half-times ranging from 15 to 50 days.
Estimates of frequency-dependent compressibility from a quasistatic double-porosity model
Berryman, J. G.; Wang, H. F.
1998-09-16T23:59:59.000Z
Gassmann's relationship between the drained and undrained bulk modulus of a porous medium is often used to relate the dry bulk modulus to the saturated bulk modulus for elastic waves, because the compressibility of air is considered so high that the dry rock behaves in a drained fashion and the frequency of elastic waves is considered so high that the saturated rock behaves in an undrained fashion. The bulk modulus calculated from ultrasonic velocities, however, often does not match the Gassmann prediction. Mavko and Jizba examined how local flow effects and unequilibrated pore pressures can lead to greater stiffnesses. Their conceptual model consists of a distribution of porosities obtained from the strain-versus-confining-pressure behavior. Stiff pores that close at higher confining pressures are considered to remain undrained (unrelaxed) while soft pores drain even for high-frequency stress changes. If the pore shape distribution is bimodal, then the rock approximately satisfies the assumptions of a double-porosity, poroelastic material. Berryman and Wang [1995] established linear constitutive equations and identified four different time scales of ow behavior: (1) totally drained, (2) soft pores are drained but stiff pores are undrained, (3) soft and stiff pores are locally equilibrated, but undrained beyond the grain scale, and (4) both soft and stiff pores are undrained. The relative magnitudes of the four associated bulk moduli will be examined for all four moduli and illustrated for several sandstones.
{\\sc CosmoNet}: fast cosmological parameter estimation in non-flat models using neural networks
T. Auld; M. Bridges; M. P. Hobson
2007-03-16T23:59:59.000Z
We present a further development of a method for accelerating the calculation of CMB power spectra, matter power spectra and likelihood functions for use in cosmological Bayesian inference. The algorithm, called {\\sc CosmoNet}, is based on training a multilayer perceptron neural network. We compute CMB power spectra (up to $\\ell=2000$) and matter transfer functions over a hypercube in parameter space encompassing the $4\\sigma$ confidence region of a selection of CMB (WMAP + high resolution experiments) and large scale structure surveys (2dF and SDSS). We work in the framework of a generic 7 parameter non-flat cosmology. Additionally we use {\\sc CosmoNet} to compute the WMAP 3-year, 2dF and SDSS likelihoods over the same region. We find that the average error in the power spectra is typically well below cosmic variance for spectra, and experimental likelihoods calculated to within a fraction of a log unit. We demonstrate that marginalised posteriors generated with {\\sc CosmoNet} spectra agree to within a few percent of those generated by {\\sc CAMB} parallelised over 4 CPUs, but are obtained 2-3 times faster on just a \\emph{single} processor. Furthermore posteriors generated directly via {\\sc CosmoNet} likelihoods can be obtained in less than 30 minutes on a single processor, corresponding to a speed up of a factor of $\\sim 32$. We also demonstrate the capabilities of {\\sc CosmoNet} by extending the CMB power spectra and matter transfer function training to a more generic 10 parameter cosmological model, including tensor modes, a varying equation of state of dark energy and massive neutrinos. {\\sc CosmoNet} and interfaces to both {\\sc CosmoMC} and {\\sc Bayesys} are publically available at {\\tt www.mrao.cam.ac.uk/software/cosmonet}.
Kao, Jim [Los Alamos National Laboratory, Applied Physics Division, P.O. Box 1663, MS T086, Los Alamos, NM 87545 (United States)]. E-mail: kao@lanl.gov; Flicker, Dawn [Los Alamos National Laboratory, Applied Physics Division, P.O. Box 1663, MS T086, Los Alamos, NM 87545 (United States); Ide, Kayo [University of California at Los Angeles (United States); Ghil, Michael [University of California at Los Angeles (United States)
2006-05-20T23:59:59.000Z
This paper builds upon our recent data assimilation work with the extended Kalman filter (EKF) method [J. Kao, D. Flicker, R. Henninger, S. Frey, M. Ghil, K. Ide, Data assimilation with an extended Kalman filter for an impact-produced shock-wave study, J. Comp. Phys. 196 (2004) 705-723.]. The purpose is to test the capability of EKF in optimizing a model's physical parameters. The problem is to simulate the evolution of a shock produced through a high-speed flyer plate. In the earlier work, we have showed that the EKF allows one to estimate the evolving state of the shock wave from a single pressure measurement, assuming that all model parameters are known. In the present paper, we show that imperfectly known model parameters can also be estimated accordingly, along with the evolving model state, from the same single measurement. The model parameter optimization using the EKF can be achieved through a simple modification of the original EKF formalism by including the model parameters into an augmented state variable vector. While the regular state variables are governed by both deterministic and stochastic forcing mechanisms, the parameters are only subject to the latter. The optimally estimated model parameters are thus obtained through a unified assimilation operation. We show that improving the accuracy of the model parameters also improves the state estimate. The time variation of the optimized model parameters results from blending the data and the corresponding values generated from the model and lies within a small range, of less than 2%, from the parameter values of the original model. The solution computed with the optimized parameters performs considerably better and has a smaller total variance than its counterpart using the original time-constant parameters. These results indicate that the model parameters play a dominant role in the performance of the shock-wave hydrodynamic code at hand.
Estimated United States Transportation Energy Use 2005
Smith, C A; Simon, A J; Belles, R D
2011-11-09T23:59:59.000Z
A flow chart depicting energy flow in the transportation sector of the United States economy in 2005 has been constructed from publicly available data and estimates of national energy use patterns. Approximately 31,000 trillion British Thermal Units (trBTUs) of energy were used throughout the United States in transportation activities. Vehicles used in these activities include automobiles, motorcycles, trucks, buses, airplanes, rail, and ships. The transportation sector is powered primarily by petroleum-derived fuels (gasoline, diesel and jet fuel). Biomass-derived fuels, electricity and natural gas-derived fuels are also used. The flow patterns represent a comprehensive systems view of energy used within the transportation sector.
Eslinger, Paul W. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); Biegalski, S. [Univ. of Texas at Austin, TX (United States); Bowyer, Ted W. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); Cooper, Matthew W. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); Haas, Derek A. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); Hayes, James C. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); Hoffman, Ian [Radiation Protection Bureau, Health Canada, Ottawa, ON (Canada); Korpach, E. [Radiation Protection Bureau, Health Canada, Ottawa, ON (Canada); Yi, Jing [Radiation Protection Bureau, Health Canada, Ottawa, ON (Canada); Miley, Harry S. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); Rishel, Jeremy P. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States); Ungar, R. Kurt [Radiation Protection Bureau, Health Canada, Ottawa, ON (Canada); White, Brian [Radiation Protection Bureau, Health Canada, Ottawa, ON (Canada); Woods, Vincent T. [Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
2014-01-01T23:59:59.000Z
Systems designed to monitor airborne radionuclides released from underground nuclear explosions detected radioactive fallout from the Fukushima Daiichi nuclear accident in March 2011. Atmospheric transport modeling (ATM) of plumes of noble gases and particulates were performed soon after the accident to determine plausible detection locations of any radioactive releases to the atmosphere. We combine sampling data from multiple International Modeling System (IMS) locations in a new way to estimate the magnitude and time sequence of the releases. Dilution factors from the modeled plume at five different detection locations were combined with 57 atmospheric concentration measurements of 133-Xe taken from March 18 to March 23 to estimate the source term. This approach estimates that 59% of the 1.24×1019 Bq of 133-Xe present in the reactors at the time of the earthquake was released to the atmosphere over a three day period. Source term estimates from combinations of detection sites have lower spread than estimates based on measurements at single detection sites. Sensitivity cases based on data from four or more detection locations bound the source term between 35% and 255% of available xenon inventory.
Zhang, Xuesong; Sahajpal, Ritvik; Manowitz, D.; Zhao, Kaiguang; LeDuc, Stephen D.; Xu, Min; Xiong, Wei; Zhang, Aiping; Izaurralde, Roberto C.; Thomson, Allison M.; West, Tristram O.; Post, W. M.
2014-05-01T23:59:59.000Z
The development of effective measures to stabilize atmospheric CO2 concentration and mitigate negative impacts of climate change requires accurate quantification of the spatial variation and magnitude of the terrestrial carbon (C) flux. However, the spatial pattern and strength of terrestrial C sinks and sources remain uncertain. In this study, we designed a spatially-explicit agroecosystem modeling system by integrating the Environmental Policy Integrated Climate (EPIC) model with multiple sources of geospatial and surveyed datasets (including crop type map, elevation, climate forcing, fertilizer application, tillage type and distribution, and crop planting and harvesting date), and applied it to examine the sensitivity of cropland C flux simulations to two widely used soil databases (i.e. State Soil Geographic-STATSGO of a scale of 1:250,000 and Soil Survey Geographic-SSURGO of a scale of 1:24,000) in Iowa, USA. To efficiently execute numerous EPIC runs resulting from the use of high resolution spatial data (56m), we developed a parallelized version of EPIC. Both STATSGO and SSURGO led to similar simulations of crop yields and Net Ecosystem Production (NEP) estimates at the State level. However, substantial differences were observed at the county and sub-county (grid) levels. In general, the fine resolution SSURGO data outperformed the coarse resolution STATSGO data for county-scale crop-yield simulation, and within STATSGO, the area-weighted approach provided more accurate results. Further analysis showed that spatial distribution and magnitude of simulated NEP were more sensitive to the resolution difference between SSURGO and STATSGO at the county or grid scale. For over 60% of the cropland areas in Iowa, the deviations between STATSGO- and SSURGO-derived NEP were larger than 1MgCha(-1)yr(-1), or about half of the average cropland NEP, highlighting the significant uncertainty in spatial distribution and magnitude of simulated C fluxes resulting from differences in soil data resolution.
Wang, Mo; Xu, B.; Cao, J.; Tie, X.; Wang, Hailong; Zhang, Rudong; Qian, Yun; Rasch, Philip J.; Zhao, Shuyu; Wu, Guangjian; Zhao, Huabiao; Joswiak, Daniel R.; Li, Jiule; Xie, Ying
2015-01-01T23:59:59.000Z
High temporal resolution measurements of black carbon (BC) and organic carbon (OC) covering the time period of 1956-2006 in an ice core over the southeastern Tibetan Plateau show a distinct seasonal dependence of OC/BC ratio with higher values in the non-monsoon season than during the summer monsoon. We use a global aerosol-climate model, in which BC emitted from different source regions can be explicitly tracked, to quantify BC source-receptor relationships between four Asian source regions and the southern Tibetan Plateau as a receptor. The model results show that South Asia is a primary contributor during the non-monsoon season (October to May) (81%) and on an annual basis (74%), followed by East Asia (14% and 21%, respectively). The ice-core record also indicates stable and relatively low BC and OC deposition fluxes from late 1950s to 1980, followed by an overall increase to recent years. This trend is consistent with the BC and OC emission inventories and the fuel consumption of South Asia as the primary contributor. Moreover, the increasing trend of OC/BC ratio since the early 1990s indicates a growing contribution of coal combustion and biomass burning to the emissions. The estimated radiative forcing induced by BC/OC impurities in snow has increased since 1980, suggesting an increasing influence of carbonaceous aerosols on the Tibetan glacier melting, influencing the availability of water resources in the surrounding regions. Our study indicates that the role of OC deserves more attention because of its non-negligible light absorption and the more rapid increase than BC
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
Wang, Mo; Xu, B.; Cao, J.; Tie, X.; Wang, Hailong; Zhang, Rudong; Qian, Yun; Rasch, Philip J.; Zhao, Shuyu; Wu, Guangjian; et al
2015-01-01T23:59:59.000Z
High temporal resolution measurements of black carbon (BC) and organic carbon (OC) covering the time period of 1956–2006 in an ice core over the southeastern Tibetan Plateau show a distinct seasonal dependence of BC and OC with higher respective concentrations but a lower OC / BC ratio in the non-monsoon season than during the summer monsoon. We use a global aerosol-climate model, in which BC emitted from different source regions can be explicitly tracked, to quantify BC source–receptor relationships between four Asian source regions and the southeastern Tibetan Plateau as a receptor. The model results show that South Asia hasmore »the largest contribution to the present-day (1996–2005) mean BC deposition at the ice-core drilling site during the non-monsoon season (October to May) (81%) and all year round (74%), followed by East Asia (14% to the non-monsoon mean and 21% to the annual mean). The ice-core record also indicates stable and relatively low BC and OC deposition fluxes from the late 1950s to 1980, followed by an overall increase to recent years. This trend is consistent with the BC and OC emission inventories and the fuel consumption of South Asia (as the primary contributor to annual mean BC deposition). Moreover, the increasing trend of the OC / BC ratio since the early 1990s indicates a growing contribution of coal combustion and/or biomass burning to the emissions. The estimated radiative forcing induced by BC and OC impurities in snow has increased since 1980, suggesting an increasing potential influence of carbonaceous aerosols on the Tibetan glacier melting and the availability of water resources in the surrounding regions. Our study indicates that more attention to OC is merited because of its non-negligible light absorption and the recent rapid increases evident in the ice-core record.« less
Chen, Sheng
output is a linear combination of non- linear basis functions. Provided that there is a separate and linear algebra are directly applicable. Moreover by applying linear regression statistical techniques-estimator and D-optimality Model Construction using Orthogonal Forward Regression Xia Hong, Senior Member, IEEE
Berlin,Technische Universität
DEWEK Wind Energy Conference 2012 Category: 4. Simulation models 1 BACKWARD EXTRAPOLATION OF SHORT-TIME MEASUREMENT DATA FOR A REMAINING SERVICE LIFE ESTIMATION OF WIND TURBINES Dipl.-Ing. René Kamieth, Prof. Dr, Germany, Tel.: +49-(0)30-314-23603, Fax: +49-(0)30-314-26131 Summary Wind turbines built in the last
Peng, Huei
A Unified Open-Circuit-Voltage Model of Lithium-ion Batteries for State-of-Charge Estimation. Keywords: Electric vehicles, Lithium-ion batteries, Open-Circuit-Voltage, State-of-Charge, State is widely used for characterizing battery properties under different conditions. It contains important
Chen, Jinsong
Joint inversion of 2D or 3D seismic and EM data for reservoir parameter estimation is computationallyEstimating reservoir parameters from seismic and electromagnetic data using stochastic rock, and pore pressure in reservoirs using seismic and electromagnetic (EM) data. Within the Bayesian framework
Chamroukhi, Faicel
of fuel cell life time Raïssa Onanena(1) , Faicel Chamroukhi(1) , Latifa Oukhellou(1)(2) , Denis Candusso to estimate fuel cell duration time from electrochemical impedance spectroscopy measurements. It consists for the estimation of fuel cell time duration. The performances of the proposed approach are evaluated
Chamroukhi, Faicel
of Fuel Cell lifetime Raïssa Onanena(1), Faicel Chamroukhi(1), Latifa Oukhellou(1), Denis Candusso(1 A probabilistic approach Parameter estimation 3 Fuel Cell lifetime estimation 4 Conclusion Faicel Chamroukhi maintenance of the Fuel Cells (FCs) Fuel Cells (FCs) are widely used in many domains including transport
Dominici, Francesca
Abstract In air pollution epidemiology, improvements in statistical analysis tools can translate for confounding. In studies of air pollution and health, the focus should ideally be on estimating health effects estimate the association between prenatal and lifetime exposures to air pollutants and pulmonary function
Donovan, E. M.; James, H.; Bonora, M.; Yarnold, J. R.; Evans, P. M. [Joint Department of Physics, Royal Marsden NHS Foundation Trust and Institute of Cancer Research, Sutton SM2 5PT (United Kingdom); Physics Department, Ipswich Hospital NHS Foundation Trust, Ipswich IP4 5PD (United Kingdom); Department of Academic Radiotherapy, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Sutton SM2 5PT, United Kingdom and School of Radiotherapy, University of Milan, Milan 20122 (Italy); Department of Academic Radiotherapy, Institute of Cancer Research and Royal Marsden NHS Foundation Trust, Sutton SM2 5PT (United Kingdom); Centre for Vision Speech and Signal Processing, University of Surrey, Guildford GU2 7XH (United Kingdom)
2012-10-15T23:59:59.000Z
Purpose: To compare organ specific cancer incidence risks for standard and complex external beam radiotherapy (including cone beam CT verification) following breast conservation surgery for early breast cancer.Method: Doses from breast radiotherapy and kilovoltage cone beam CT (CBCT) exposures were obtained from thermoluminescent dosimeter measurements in an anthropomorphic phantom in which the positions of radiosensitive organs were delineated. Five treatment deliveries were investigated: (i) conventional tangential field whole breast radiotherapy (WBRT), (ii) noncoplanar conformal delivery applicable to accelerated partial beast irradiation (APBI), (iii) two-volume simultaneous integrated boost (SIB) treatment, (iv) forward planned three-volume SIB, and (v) inverse-planned three volume SIB. Conformal and intensity modulated radiotherapy methods were used to plan the complex treatments. Techniques spanned the range from simple methods appropriate for patient cohorts with a low cancer recurrence risk to complex plans relevant to cohorts with high recurrence risk. Delineated organs at risk included brain, salivary glands, thyroid, contralateral breast, left and right lung, esophagus, stomach, liver, colon, and bladder. Biological Effects of Ionizing Radiation (BEIR) VII cancer incidence models were applied to the measured mean organ doses to determine lifetime attributable risk (LAR) for ages at exposure from 35 to 80 yr according to radiotherapy techniques, and included dose from the CBCT imaging. Results: All LAR decreased with age at exposure and were lowest for brain, thyroid, liver, and bladder (<0.1%). There was little dependence of LAR on radiotherapy technique for these organs and for colon and stomach. LAR values for the lungs for the three SIB techniques were two to three times those from WBRT and APBI. Uncertainties in the LAR models outweigh any differences in lung LAR between the SIB methods. Constraints in the planning of the SIB methods ensured that contralateral breast doses and LAR were comparable to WBRT, despite their added complexity. The smaller irradiated volume of the ABPI plan contributed to a halving of LAR for contralateral breast compared with the other plan types. Daily image guided radiotherapy (IGRT) for a left breast protocol using kilovoltage CBCT contributed <10% to LAR for the majority of organs, and did not exceed 22% of total organ dose. Conclusions: Phantom measurements and calculations of LAR from the BEIR VII models predict that complex breast radiotherapy techniques do not increase the theoretical risk of second cancer incidence for organs distant from the treated breast, or the contralateral breast where appropriate plan constraints are applied. Complex SIB treatments are predicted to increase the risk of second cancer incidence in the lungs compared to standard whole breast radiotherapy; this is outweighed by the threefold reduction in 5 yr local recurrence risk for patients of high risk of recurrence, and young age, from the use of radiotherapy. APBI may have a favorable impact on risk of second cancer in the contralateral breast and lung for older patients at low risk of recurrence. Intensive use of IGRTincreased the estimated values of LAR but these are dominated by the effect of the dose from the radiotherapy, and any increase in LAR from IGRT is much lower than the models' uncertainties.
ARM Climate Modeling Best Estimate from Manus Island, PNG (ARMBE-CLDRAD TWPC1 V2.1)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
ARM Climate Modeling Best Estimate from Darwin, AU (ARMBE-CLDRAD TWPC3 V2.1)
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
Chen, Yu-Han, 1973-
2004-01-01T23:59:59.000Z
Methane (CH?) and carbon dioxide (CO?) are the two most radiatively important greenhouse gases attributable to human activity. Large uncertainties in their source and sink magnitudes currently exist. We estimate global ...
COMPARISON OF MOBILE5A, MOBILE6, VT-MICRO, AND CMEM MODELS FOR ESTIMATING HOT-STABILIZED LIGHT-
Rakha, Hesham A.
, MOBILE6, Fuel Consumption Models, Emission Models. #12;3 INTRODUCTION Numerous energy and emission models) and Environmental Protection Agency (EPA) laboratory fuel consumption and emission databases are utilized for model are consistent in trends with laboratory measurements. Furthermore, the VT-Micro and MOBILE6 models accurately
Wang, Ruofan; Wang, Jiang; Deng, Bin, E-mail: dengbin@tju.edu.cn; Liu, Chen; Wei, Xile [Department of Electrical and Automation Engineering, Tianjin University, Tianjin (China)] [Department of Electrical and Automation Engineering, Tianjin University, Tianjin (China); Tsang, K. M.; Chan, W. L. [Department of Electrical Engineering, The Hong Kong Polytechnic University, Kowloon (Hong Kong)] [Department of Electrical Engineering, The Hong Kong Polytechnic University, Kowloon (Hong Kong)
2014-03-15T23:59:59.000Z
A combined method composing of the unscented Kalman filter (UKF) and the synchronization-based method is proposed for estimating electrophysiological variables and parameters of a thalamocortical (TC) neuron model, which is commonly used for studying Parkinson's disease for its relay role of connecting the basal ganglia and the cortex. In this work, we take into account the condition when only the time series of action potential with heavy noise are available. Numerical results demonstrate that not only this method can estimate model parameters from the extracted time series of action potential successfully but also the effect of its estimation is much better than the only use of the UKF or synchronization-based method, with a higher accuracy and a better robustness against noise, especially under the severe noise conditions. Considering the rather important role of TC neuron in the normal and pathological brain functions, the exploration of the method to estimate the critical parameters could have important implications for the study of its nonlinear dynamics and further treatment of Parkinson's disease.
Subramanian, Venkat
concentration, electrolyte potential, solid-state potential, and solid-state concentration in the porous with cycling. Reformulated Model First-principles-based battery models typically solve electrolyte electrodes and electrolyte concentration and electrolyte potential in the separator. These models
Natesan, Prathiba
2009-05-15T23:59:59.000Z
IRT models. However, models such as 2-PL MLIRT models have not been studied yet. This dissertation consists of two studies, a simulation and a substantiation for an urban school district dataset. The simulation study tested the performance...
Kooperman, G. J.; Pritchard, M. S.; Ghan, Steven J.; Wang, Minghuai; Somerville, Richard C.; Russell, Lynn
2012-12-11T23:59:59.000Z
Natural modes of variability on many timescales influence aerosol particle distributions and cloud properties such that isolating statistically significant differences in cloud radiative forcing due to anthropogenic aerosol perturbations (indirect effects) typically requires integrating over long simulations. For state-of-the-art global climate models (GCM), especially those in which embedded cloud-resolving models replace conventional statistical parameterizations (i.e. multi-scale modeling framework, MMF), the required long integrations can be prohibitively expensive. Here an alternative approach is explored, which implements Newtonian relaxation (nudging) to constrain simulations with both pre-industrial and present-day aerosol emissions toward identical meteorological conditions, thus reducing differences in natural variability and dampening feedback responses in order to isolate radiative forcing. Ten-year GCM simulations with nudging provide a more stable estimate of the global-annual mean aerosol indirect radiative forcing than do conventional free-running simulations. The estimates have mean values and 95% confidence intervals of -1.54 ± 0.02 W/m2 and -1.63 ± 0.17 W/m2 for nudged and free-running simulations, respectively. Nudging also substantially increases the fraction of the world’s area in which a statistically significant aerosol indirect effect can be detected (68% and 25% of the Earth's surface for nudged and free-running simulations, respectively). One-year MMF simulations with and without nudging provide global-annual mean aerosol indirect radiative forcing estimates of -0.80 W/m2 and -0.56 W/m2, respectively. The one-year nudged results compare well with previous estimates from three-year free-running simulations (-0.77 W/m2), which showed the aerosol-cloud relationship to be in better agreement with observations and high-resolution models than in the results obtained with conventional parameterizations.
Reiser, I; Lu, Z [University of Chicago, Chicago, IL (United States)
2014-06-01T23:59:59.000Z
Purpose: Recently, task-based assessment of diagnostic CT systems has attracted much attention. Detection task performance can be estimated using human observers, or mathematical observer models. While most models are well established, considerable bias can be introduced when performance is estimated from a limited number of image samples. Thus, the purpose of this work was to assess the effect of sample size on bias and uncertainty of two channelized Hotelling observers and a template-matching observer. Methods: The image data used for this study consisted of 100 signal-present and 100 signal-absent regions-of-interest, which were extracted from CT slices. The experimental conditions included two signal sizes and five different x-ray beam current settings (mAs). Human observer performance for these images was determined in 2-alternative forced choice experiments. These data were provided by the Mayo clinic in Rochester, MN. Detection performance was estimated from three observer models, including channelized Hotelling observers (CHO) with Gabor or Laguerre-Gauss (LG) channels, and a template-matching observer (TM). Different sample sizes were generated by randomly selecting a subset of image pairs, (N=20,40,60,80). Observer performance was quantified as proportion of correct responses (PC). Bias was quantified as the relative difference of PC for 20 and 80 image pairs. Results: For n=100, all observer models predicted human performance across mAs and signal sizes. Bias was 23% for CHO (Gabor), 7% for CHO (LG), and 3% for TM. The relative standard deviation, ?(PC)/PC at N=20 was highest for the TM observer (11%) and lowest for the CHO (Gabor) observer (5%). Conclusion: In order to make image quality assessment feasible in the clinical practice, a statistically efficient observer model, that can predict performance from few samples, is needed. Our results identified two observer models that may be suited for this task.
Busby, R.L.; Ward, K.B.
1989-01-01T23:59:59.000Z
A model was devised to estimate the harvest value of unthinned loblolly and slash pine (pinus taeda L. and P. elliottii var. elliottii Englm.) plantations in the west gulf region. The model, MERCHOP, can be used to forecast product volumes and values; the output provided is partitioned into 1-inch tree d.b.h. classes. Using a dynamic programming algorithm, MERCHOP can be used to convert stand tables predicted by USLYCOWG's three-parameter Weibull function into a listing of seven products that maximizes the selling value of the stand, assuming the assumptions used in the analysis are correct.
Washington at Seattle, University of
-based vehicle classification data are critical inputs for traffic operations,10 pavement design and maintenance classification data are important inputs for traffic operations, pavement2 design and maintenance the estimation results become statistically stable and converge. This method is20 straightforward
-Based Electrochemical Estimation and Constraint Management for Pulse Operation of Lithium Ion Batteries Kandler A. Smith Technologies, Graduate Automotive Technology Education Pro- gram. This work was performed at the Pennsylvania-mail: kandlers@hotmail.com; kandler_smith@nrel.gov). C. D. Rahn and C.-Y. Wang are with the Department
Kumar, Vipin
ecosystem (tundra and boreal) sinks for atmospheric CO2. Key Words: carbon dioxide, ecosystems, remote "missing sink" for carbon dioxide emissions. Measured atmospheric CO2, 13 C, and O2/N2 distributionsContinental Scale Comparisons of Terrestrial Carbon Sinks Estimated from Satellite Data
Madas, Balázs G
2013-01-01T23:59:59.000Z
There is a considerable debate between research groups applying the two stage clonal expansion model for lung cancer risk estimation, whether radon exposure affects initiation and transformation or promotion. The objective of the present study is to quantify the effects of radon progeny on these stages with biophysical models. For this purpose, numerical models of mutation induction and clonal growth were applied in order to estimate how initiation, transformation and promotion rates depend on tissue dose rate. It was found that rates of initiation and transformation increase monotonically with dose rate, while effective promotion rate decreases with time, but increases in a supralinear fashion with dose rate. Despite the uncertainty of the results due to the lack of experimental data, present study suggests that effects of radon exposure on both mutational events and clonal growth are significant, and should be considered in epidemiological analyses applying mathematical models of carcinogenesis.
Dowd, William Wesley; Brill, R W; Bushnell, P G; Musick, J A
2006-01-01T23:59:59.000Z
error analy- sis of fish bioenergetics models. Can J. Fish.importance of activity in bioenergetics models applied toA. C. Cockcroft. 1990. Bioenergetics of fishes in a high-
Scranton, Katherine
2012-01-01T23:59:59.000Z
cois, 2008. Non-linear regression models for approximateparameters. They use non-linear regression of parameters on
Barik, Muhammad Ghulam
2014-01-01T23:59:59.000Z
evapotranspiration equations and their relevance to stream flow modeling in semi-arid environments.evapotranspiration equations and their relevance to stream flow modeling in semi-arid environments.evapotranspiration equations and their relevance to stream flow modeling in semi-arid environments.
Gregory L. Eyink
1996-02-19T23:59:59.000Z
We establish and discuss {\\em a priori} estimates on subgrid stress and subgrid flux for filtering schemes used in the turbulence modelling method of Large-Eddy Simulation (LES). Our estimates are derived as rigorous consequences of the exact subgrid stress formulae from Navier-Stokes equations under realistic conditions for inertial-range velocity fields, those conjectured in the Parisi-Frisch ``multifractal model.'' The estimates are shown to be an expression of ``local energy cascade,'' i.e. the dominance of local wavevector triads in the energy transfer. We prove that for nearly any reasonable filter function the LES method defines an energy flux in which local triads dominate in individual realizations, due to cancellation of distant triadic contributions by detailed conservation. A somewhat similar observation of Leslie and Quarini on graded filters in the EDQNM closure is shown to be unrelated to the cancellation we establish in Navier-Stokes solutions. The sharp Fourier cutoff filter is one example which does not satisfy the modest conditions of our proof and, in fact, we show that with that filter the energy transfer in individual realizations at arbitrarily high Reynolds number will be dominated by nonlocal, convective sweeping.
Situ, S.; Wang, Xuemei; Guenther, Alex B.; Zhang, Yanli; Wang, Xinming; Huang, Minjuan; Fan, Qi; Xiong, Zhe
2014-12-01T23:59:59.000Z
Using local observed emission factor, meteorological data, vegetation 5 information and dynamic MODIS LAI, MEGANv2.1 was constrained to predict the isoprene emission from Dinghushan forest in the Pearl River Delta region during a field campaign in November 2008, and the uncertainties in isoprene emission estimates were quantified by the Monte Carlo approach. The results indicate that MEGAN can predict the isoprene emission reasonably during the campaign, and the mean value of isoprene emission is 2.35 mg m-2 h-1 in daytime. There are high uncertainties associated with the MEGAN inputs and calculated parameters, and the relative error can be as high as -89 to 111% for a 95% confidence interval. The emission factor of broadleaf trees and the activity factor accounting for light and temperature dependence are the most important contributors to the uncertainties in isoprene emission estimated for the Dinghushan forest during the campaign. The results also emphasize the importance of accurate observed PAR and temperature to reduce the uncertainties in isoprene emission estimated by model, because the MEGAN model activity factor accounting for light and temperature dependence is highly sensitive to PAR and temperature.
Estimating Fuel Cycle Externalities: Analytical Methods and Issues, Report 2
Barnthouse, L.W.; Cada, G.F.; Cheng, M.-D.; Easterly, C.E.; Kroodsma, R.L.; Lee, R.; Shriner, D.S.; Tolbert, V.R.; Turner, R.S.
1994-07-01T23:59:59.000Z
The activities that produce electric power typically range from extracting and transporting a fuel, to its conversion into electric power, and finally to the disposition of residual by-products. This chain of activities is called a fuel cycle. A fuel cycle has emissions and other effects that result in unintended consequences. When these consequences affect third parties (i.e., those other than the producers and consumers of the fuel-cycle activity) in a way that is not reflected in the price of electricity, they are termed ''hidden'' social costs or externalities. They are the economic value of environmental, health and any other impacts, that the price of electricity does not reflect. How do you estimate the externalities of fuel cycles? Our previous report describes a methodological framework for doing so--called the damage function approach. This approach consists of five steps: (1) characterize the most important fuel cycle activities and their discharges, where importance is based on the expected magnitude of their externalities, (2) estimate the changes in pollutant concentrations or other effects of those activities, by modeling the dispersion and transformation of each pollutant, (3) calculate the impacts on ecosystems, human health, and any other resources of value (such as man-made structures), (4) translate the estimates of impacts into economic terms to estimate damages and benefits, and (5) assess the extent to which these damages and benefits are externalities, not reflected in the price of electricity. Each step requires a different set of equations, models and analysis. Analysts generally believe this to be the best approach for estimating externalities, but it has hardly been used! The reason is that it requires considerable analysis and calculation, and to this point in time, the necessary equations and models have not been assembled. Equally important, the process of identifying and estimating externalities leads to a number of complex issues that also have not been fully addressed. This document contains two types of papers that seek to fill part of this void. Some of the papers describe analytical methods that can be applied to one of the five steps of the damage function approach. The other papers discuss some of the complex issues that arise in trying to estimate externalities. This report, the second in a series of eight reports, is part of a joint study by the U.S. Department of Energy (DOE) and the Commission of the European Communities (EC)* on the externalities of fuel cycles. Most of the papers in this report were originally written as working papers during the initial phases of this study. The papers provide descriptions of the (non-radiological) atmospheric dispersion modeling that the study uses; reviews much of the relevant literature on ecological and health effects, and on the economic valuation of those impacts; contains several papers on some of the more complex and contentious issues in estimating externalities; and describes a method for depicting the quality of scientific information that a study uses. The analytical methods and issues that this report discusses generally pertain to more than one of the fuel cycles, though not necessarily to all of them. The report is divided into six parts, each one focusing on a different subject area.
Operational Evaluation of Air Quality Models Paul D. Sampson Peter Guttorp
Washington at Seattle, University of
predictions, (2) graphical depiction and comparison of spatio-temporal correlation structures determined from Standards (NAAQS) (CFR 40, Part 50). These models--or modeling systems, comprised of emissions, atmospheric
Technical report: Multivariate generalized S-estimators
Van Aelst, Stefan
Technical report: Multivariate generalized S-estimators Roelant E. a, Van Aelst S. a Croux C. b a-estimators for the multivariate regression model. This class of estimators combines high robustness and high efficiency of residuals. In the special case of a multivariate location model, the generalized S-estimator has
Stoffel, Markus
and Environmental Engineering, Universidad de Los Andes, Bogotá, Colombia d Laboratory of Dendrogeomorphology the Navaluenga flow gauge (Avila Province) as well as a 1D/2D coupled numerical hydraulic model. A total of 49 hydraulic modelling, we cannot find a statistically sig- nificant difference between water depths registered
Paris-Sud XI, Université de
SimHydro 2012: Hydraulic modeling and uncertainty, 12-14 September 2012, Sophia Antipolis N. Jean-Baptiste, C. Dorée, P-O. Malaterre, J. Sau - Data assimilation for hydraulic state estimation of a development project Data assimilation for hydraulic state estimation of a development project Assimilation de données
Wang, M.Q.
1996-03-01T23:59:59.000Z
This report documents the development and use of the Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation (GREET) model. The model, developed in a spreadsheet format, estimates the full fuel- cycle emissions and energy use associated with various transportation fuels for light-duty vehicles. The model calculates fuel-cycle emissions of five criteria pollutants (volatile organic compounds, carbon monoxide, nitrogen oxides, sulfur oxides, and particulate matter measuring 10 microns or less) and three greenhouse gases (carbon dioxide, methane, and nitrous oxide). The model also calculates the total fuel-cycle energy consumption, fossil fuel consumption, and petroleum consumption using various transportation fuels. The GREET model includes 17 fuel cycles: petroleum to conventional gasoline, reformulated gasoline, clean diesel, liquefied petroleum gas, and electricity via residual oil; natural gas to compressed natural gas, liquefied petroleum gas, methanol, hydrogen, and electricity; coal to electricity; uranium to electricity; renewable energy (hydrogen, solar energy, and wind) to electricity; corn, woody biomass, and herbaceous biomass to ethanol; and landfill gases to methanol. This report presents fuel-cycle energy use and emissions for a 2000 model-year car powered by each of the fuels that are produced from the primary energy sources considered in the study.
Paris-Sud XI, Université de
of precipitation depths. Indeed, meteorological radar provides spatially distributed rainfall depths information (radars, hourly and daily rain gauges, satellite data, model freezing level heights, etc with rain gauge network. First, a methodology for automated identification and treatment of radar
Blair, N.; Mehos, M.; Short, W.; Heimiller, D.
2006-04-01T23:59:59.000Z
This paper presents the Concentrating Solar Deployment System Model (CSDS). CSDS is a multiregional, multitime-period, Geographic Information System (GIS), and linear programming model of capacity expansion in the electric sector of the United States. CSDS is designed to address the principal market and policy issues related to the penetration of concentrating solar power (CSP) electric-sector technologies. This paper discusses the current structure, capabilities, and assumptions of the model. Additionally, results are presented for the impact of continued research and development (R&D) spending, an extension to the investment tax credit (ITC), and use of a production tax credit (PTC). CSDS is an extension of the Wind Deployment System (WinDS) model created at the National Renewable Energy Laboratory (NREL). While WinDS examines issues related to wind, CSDS is an extension to analyze similar issues for CSP applications. Specifically, a detailed representation of parabolic trough systems with thermal storage has been developed within the existing structure.
Kandelous, Maziar M.; Šim?nek, Ji?í
2010-01-01T23:59:59.000Z
and clay (33.5%), and water contents for pressures of -33times, antecedent water contents, and emitter locations, andthe saturated soil water content as one of the model
McCollum, David L; Ogden, Joan M
2006-01-01T23:59:59.000Z
as reported in the Oil & Gas Journal. From this data, theycost data from the Oil & Gas Journal. The Ecofys Models Theas reported in the Oil & Gas Journal. From this data, they
Moon, Jordan R.; Hull, Holly R.; Tobkin, Sarah E.; Teramoto, Masaru; Karabulut, Murat; Roberts, Michael D.; Ryan, Eric D.; Kim, So Jung; Dalbo, Vincent J.; Herda, Ashley A.
2007-11-07T23:59:59.000Z
-free mass and fat mass can be used to identify minimal nutri- tion requirements and resting energy expenditure [2,3]. Additionally, sports nutrition experts can utilize body composition values to develop specific dietary interven- tions. Validated laboratory... is not in total agreement when comparing HW to the multiple-compartment model in adult women [4,8]. Ultimately, both multiple- compartment models and HW entail greater facility requirements and are more costly compared to more con- venient field methods...
Vijayaraghavan, K.; Zhang, Y.; Seigneur, C.; Karamchandani, P.; Snell, H.E.
2009-02-15T23:59:59.000Z
The export of reactive nitrogen (nitrogen oxides and their oxidation products, collectively referred to as NOy) from coal-fired power plants in the U.S. to the rest of the world could have a significant global contribution to ozone. Traditional Eulerian gridded air quality models cannot characterize accurately the chemistry and transport of plumes from elevated point sources such as power plant stacks. A state-of-the-science plume-in-grid (PinG) air quality model, a reactive plume model embedded in an Eulerian gridded model, is used to estimate the export of NOy from 25 large coal-fired power plants in the U. S. (in terms of NOx and SO{sub 2} emissions) in July 2001 to the global atmosphere. The PinG model used is the Community Multiscale Air Quality Model with Advanced Plume Treatment (CMAQ-APT). A benchmark simulation with only the gridded model, CMAQ, is also conducted for comparison purposes. The simulations with and without advanced plume treatment show differences in the calculated export of NOy from the 25 plants considered reflecting the effect of using a detailed and explicit treatment of plume transport and chemistry. The advanced plume treatment results in 31% greater simulated export of NOy compared to the purely grid-based modeling approach. The export efficiency of NOy (the fraction of NOy emitted that is exported) is predicted to be 21% without APT and 27% with APT. When considering only export through the eastern boundary across the Atlantic, CMAQ-APT predicts that the export efficiency is 24% and that 2% of NOy is exported as NOx, 49% as inorganic nitrate, and 25% as PAN. These results are in reasonably good agreement with an analysis reported in the literature of aircraft measurements over the North Atlantic.
Wu, Huan; Adler, Robert F.; Tian, Yudong; Huffman, George; Li, Hongyi; Wang, Jianjian
2014-04-09T23:59:59.000Z
A community land surface model, the Variable Infiltration Capacity (VIC) model, is coupled with a newly developed hierarchical dominant river tracing-based runoff-routing model to form the Dominant river tracing-Routing Integrated with VIC Environment (DRIVE) model system, which serves as the new core of the real-time Global Flood Monitoring System (GFMS). The GFMS uses real-time satellite-based precipitation to derive flood-monitoring parameters for the latitude-band 50{degree sign}N-50{degree sign}S at relatively high spatial (~12km) and temporal (3-hourly) resolution. Examples of model results for recent flood events are computed using the real-time GFMS (http://flood.umd.edu). To evaluate the accuracy of the new GFMS, the DRIVE model is run retrospectively for 15 years using both research-quality and real-time satellite precipitation products. Statistical results are slightly better for the research-quality input and significantly better for longer duration events (three-day events vs. one-day events). Basins with fewer dams tend to provide lower false alarm ratios. For events longer than three days in areas with few dams, the probability of detection is ~0.9 and the false alarm ratio is ~0.6. In general, these statistical results are better than those of the previous system. Streamflow was evaluated at 1,121 river gauges across the quasi-global domain. Validation using real-time precipitation across the tropics (30ºS-30ºN) gives positive daily Nash-Sutcliffe Coef?cients for 107 out of 375 (28%) stations with a mean of 0.19 and 51% of the same gauges at monthly scale with a mean of 0.33. There were poorer results in higher latitudes, probably due to larger errors in the satellite precipitation input.
Bunkóczi, Gábor; Wallner, Björn; Read, Randy J.
2015-01-22T23:59:59.000Z
calculated with MUSCLE (Edgar, 2004). ts, homology models were created using ini et al., 2014), based on the template ed as MR models. This step was required iction, since the actual sequence has to be cture and side chains have to be present. selected... , 2014 Published: January 22, 2015 REFERENCES Adams, P.D., Afonine, P.V., Bunko´czi, G., Chen, V.B., Davis, I.W., Echols, N., Headd, J.J., Hung, L.W., Kapral, G.J., Grosse-Kunstleve, R.W., et al. (2010).Nature 473, 540–543. Edgar, R.C. (2004). MUSCLE...
Shapiro, Benjamin
are presented and the effect of motor dynamics on the overall dynamics are investigated. Flowfield velocity the helicopter aerodynamics onboard and modulates the motor torque, rather than the collective pitch, during take- niques often require a system model with empirically fit aero- dynamic coefficients that are unique
Casey, James Elmer
1973-01-01T23:59:59.000Z
. Hypothetical Factor-Pactor Model indicating profit maximizing conditions with limited capital and with a variab1e input limitation 24 P2 units, then other inputs would be added until their marginal value poduct was equal to their price. This would...
Batzel, Jerry
flow dynamics. This model is an approach to assess the lymph flow by measurements of the substance chain of alternating units of glucuronic acid and Nacetylglucosamine that is linked glycosidically via, it takes part in the regulation of tissue hydration and is an important determinant for hydraulic
Li, Xiang; Zhou, Bei; He, Hao-Ning; Fan, Yi-Zhong; Wei, Da-Ming, E-mail: yzfan@pmo.ac.cn [Key Laboratory of Dark Matter and Space Astronomy, Purple Mountain Observatory, Chinese Academy of Science, Nanjing 210008 (China)
2014-12-10T23:59:59.000Z
The existence of fast radio bursts (FRBs), a new type of extragalatic transient, has recently been established, and quite a few models have been proposed. In this work, we discuss the possible connection between the FRB sources and ultra high energy (>10{sup 18} eV) cosmic rays. We show that in the blitzar model and the model of merging binary neutron stars, which includes the huge energy release of each FRB central engine together with the rather high rate of FRBs, the accelerated EeV cosmic rays may contribute significantly to the observed ones. In other FRB models, including, for example, the merger of double white dwarfs and the energetic magnetar radio flares, no significant EeV cosmic ray is expected. We also suggest that the mergers of double neutron stars, even if they are irrelevant to FRBs, may play a nonignorable role in producing EeV cosmic ray protons if supramassive neutron stars are formed in a sufficient fraction of mergers and the merger rate is ? 10{sup 3} yr{sup –1} Gpc{sup –3}. Such a possibility will be unambiguously tested in the era of gravitational wave astronomy.
Jiajuan Liang; Peter Bentler
2011-01-01T23:59:59.000Z
The model can be expressed as ( Vgi 9i v v w i t h the basicis given by 5 V = cov I \\Vgi I , J S I , w and the between-value v . g g YgO q+(N Vgi N g Under the basic assumptions B
Thornton, Mitchell
required resources.. The accuracy of the model is measured by validation using parallelism profiles under functions is presented. By using a data dependence graph, or alternatively, an available parallelism profile to a finite number of processing elements. 1 Introduction Parallelism profiles have been used in the past
Estimated Water Flows in 2005: United States
Smith, C A; Belles, R D; Simon, A J
2011-03-16T23:59:59.000Z
Flow charts depicting water use in the United States have been constructed from publicly available data and estimates of water use patterns. Approximately 410,500 million gallons per day of water are managed throughout the United States for use in farming, power production, residential, commercial, and industrial applications. Water is obtained from four major resource classes: fresh surface-water, saline (ocean) surface-water, fresh groundwater and saline (brackish) groundwater. Water that is not consumed or evaporated during its use is returned to surface bodies of water. The flow patterns are represented in a compact 'visual atlas' of 52 state-level (all 50 states in addition to Puerto Rico and the Virgin Islands) and one national water flow chart representing a comprehensive systems view of national water resources, use, and disposition.
Wichmann, Felix
-based and model-based segmentation. Figure 1 depicts the algorithm flow chart. The hybrid segmentation can speaker models. First, silence segments in the input audio recording are detected by the simple energy
Cost Estimating, Analysis, and Standardization
Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]
1984-11-02T23:59:59.000Z
To establish policy and responsibilities for: (a) developing and reviewing project cost estimates; (b) preparing independent cost estimates and analysis; (c) standardizing cost estimating procedures; and (d) improving overall cost estimating and analytical techniques, cost data bases, cost and economic escalation models, and cost estimating systems. Cancels DOE O 5700.2B, dated 8-5-1983; DOE O 5700.8, dated 5-27-1981; and HQ 1130.1A, dated 12-30-1981. Canceled by DOE O 5700.2D, dated 6-12-1992
Model Description 3.1 Introduction
Ford, David N.
this process by depicting the model from three relatively context-free vantage points. First the model itself in subsequent chapters. A signal processing model of a portion of the Product Development Project Model-development operations Resource Quantity Intra-phase process constraints Error Generation & Discovery Iteration & Rework
Brioude, J.; Kim, S. W.; Angevine, Wayne M.; Frost, G. J.; Lee, S. H.; McKeen, S. A.; Trainer, Michael; Fehsenfeld, Fred C.; Holloway, J. S.; Ryerson, T. B.; Williams, E. J.; Petron, Gabrielle; Fast, Jerome D.
2011-10-31T23:59:59.000Z
The 2000 and 2006 Texas Air Quality Study (TexAQS 2000 and 2006) field campaigns took place in eastern Texas in August-October of 2000 and 2006. Several flights of the National Oceanic and Atmospheric Administration (NOAA) and National Center for Atmospheric Research (NCAR) research aircraft were dedicated to characterizing anthropogenic emissions over Houston. Houston is known for having serious problems with non-attainment of air quality standards. We present a method that uses three models and aircraft observations to assess and improve existing emission inventories using an inverse modeling technique. We used 3-dimensional and 4-dimensional variational (3D-VAR and 4D-VAR) inverse modeling techniques based on a least-squares method to improve the spatial and temporal distribution of CO, NOy (sum of all reactive nitrogen compounds), and SO2 emissions predicted by the 4-km-resolution U.S. Environmental Protection Agency (EPA) National Emission Inventory (NEI) for 2005. Differences between the prior and posterior inventories are discussed in detail. We found that in 2006 the prior daytime emissions in the urban area of Houston have to be reduced by 40% {+-} 12% for CO and 7% {+-} 13% for NOy. Over the Houston Ship Channel, where industrial emissions are predominant, the prior emissions have to be reduced by 41% {+-} 15% for CO and 51% {+-} 9% for NOy. Major ports around Houston have their NOy emissions reduced as well, probably due to uncertainties in near-shore ship emissions in the EPA NEI inventory. Using the measurements from the two field campaigns, we assessed the interannual emission variability between 2000 and 2006. Daytime CO emissions from the Houston urban area have been reduced by 8% {+-} 20%, while the NOy emissions have increased by 20% {+-} 12% from 2000 to 2006. In the Houston Ship Channel, the daytime NOy emissions have increased by 13% {+-} 17%. Our results show qualitative consistencies with known changes in Houston emissions sources.
Perry, Richard Jay
1985-01-01T23:59:59.000Z
4. 5 percentage units less fat (21. 64% vs 26, 1% carcass fat) than non-implanted steers of the same carcass weight and rate of gain (350 kg and ADG of 1. 0 kg/d). Fat as a percentage of gain averaged 67. 85, 52. 05 and 39. 59 for non... model which can be used for projecting changes in yield grade and quality grade with performance of cattle in the feedlot over time. The primary objectives of this research were: 1) To determine the "shelf life" of a steer in the feedlot. 2...
Best Linear Unbiased Estimate Motivation for BLUE
Fowler, Mark
1 Chapter 6 Best Linear Unbiased Estimate (BLUE) #12;2 Motivation for BLUE Except for Linear Model to a sub-optimal estimate BLUE is one such sub-optimal estimate Idea for BLUE: 1. Restrict estimate) Advantage of BLUE:Needs only 1st and 2nd moments of PDF Mean & Covariance Disadvantages of BLUE: 1. Sub
Brian A. Ebel; John R. Nimmo
2009-09-11T23:59:59.000Z
Traveltimes for contaminant transport by water from a point in the unsaturated zone to the saturated zone are a concern at Rainier Mesa and Shoshone Mountain in the Nevada Test Site, Nevada. Where nuclear tests were conducted in the unsaturated zone, contaminants must traverse hundreds of meters of variably saturated rock before they enter the saturated zone in the carbonate rock, where the regional groundwater system has the potential to carry them substantial distances to a location of concern. The unsaturated-zone portion of the contaminant transport path may cause a significant delay, in addition to the time required to travel within the saturated zone, and thus may be important in the overall evaluation of the potential hazard from contamination. Downward contaminant transport through the unsaturated zone occurs through various processes and pathways; this can lead to a broad distribution of contaminant traveltimes, including exceedingly slow and unexpectedly fast extremes. Though the bulk of mobile contaminant arrives between the time-scale end members, the fastest contaminant transport speed, in other words the speed determined by the combination of possible processes and pathways that would bring a measureable quantity of contaminant to the aquifer in the shortest time, carries particular regulatory significance because of its relevance in formulating the most conservative hazard-prevention scenarios. Unsaturated-zone flow is usually modeled as a diffusive process responding to gravity and pressure gradients as mediated by the unsaturated hydraulic properties of the materials traversed. The mathematical formulation of the diffuse-flow concept is known as Richards' equation, which when coupled to a solute transport equation, such as the advection-dispersion equation, provides a framework to simulate contaminant migration in the unsaturated zone. In recent decades awareness has increased that much fluid flow and contaminant transport within the unsaturated zone takes place as preferential flow, faster than would be predicted by the coupled Richards' and advection-dispersion equations with hydraulic properties estimated by traditional means. At present the hydrologic community has not achieved consensus as to whether a modification of Richards' equation, or a fundamentally different formulation, would best quantify preferential flow. Where the fastest contaminant transport speed is what needs to be estimated, there is the possibility of simplification of the evaluation process. One way of doing so is by a two-step process in which the first step is to evaluate whether significant preferential flow and solute transport is possible for the media and conditions of concern. The second step is to carry out (a) a basic Richards' and advection-dispersion equation analysis if it is concluded that preferential flow is not possible or (b) an analysis that considers only the fastest possible preferential-flow processes, if preferential flow is possible. For the preferential-flow situation, a recently published model describable as a Source-Responsive Preferential-Flow (SRPF) model is an easily applied option. This report documents the application of this two-step process to flow through the thick unsaturated zones of Rainier Mesa and Shoshone Mountain in the Nevada Test Site. Application of the SRPF model involves distinguishing between continuous and intermittent water supply to preferential flow paths. At Rainier Mesa and Shoshone Mountain this issue is complicated by the fact that contaminant travel begins at a location deep in the subsurface, where there may be perched water that may or may not act like a continuous supply, depending on such features as the connectedness of fractures and the nature of impeding layers. We have treated this situation by hypothesizing both continuous and intermittent scenarios for contaminant transport to the carbonate aquifer and reporting estimation of the fastest speed for both of these end members.
Harmonizing Systems and Software Cost Estimation
Wang, Gan
2009-07-19T23:59:59.000Z
The objective of this paper is to examine the gaps and overlaps between software and systems engineering cost models with intent to harmonize the estimates in engineering engineering estimation. In particular, we evaluate ...
Bayesian estimation of resistivities from seismic velocities
Werthmüller, Dieter
2014-06-30T23:59:59.000Z
I address the problem of finding a background model for the estimation of resistivities in the earth from controlled-source electromagnetic (CSEM) data by using seismic data and well logs as constraints. Estimation of ...
Exploring chaos to model the design process
Sharkawy, Ahmed
1990-01-01T23:59:59.000Z
of design as a sequence of three rational processes (14) 10 Jansson's tsvo space model (15) 4 The different types of constraints within the design process The major processes occuring in Jansson's concept space. 19 6 Figure 6a depicts the skeleton upon... model and how it fits within March's depiction 9 Reduced two variable model and how it fits within Jansson's scheme . . 45 10 Map of case: 3=2. 0, /=50, d=0. 15 47 11 Map of case: %=2. 2, y=50, d=0. 15 48 12 Map of' case: 4=2. 6, @=50, d=0. 15 49...
Exploring chaos to model the design process
Sharkawy, Ahmed
1990-01-01T23:59:59.000Z
of design as a sequence of three rational processes (14) 10 Jansson's tsvo space model (15) 4 The different types of constraints within the design process The major processes occuring in Jansson's concept space. 19 6 Figure 6a depicts the skeleton upon... model and how it fits within March's depiction 9 Reduced two variable model and how it fits within Jansson's scheme . . 45 10 Map of case: 3=2. 0, /=50, d=0. 15 47 11 Map of case: %=2. 2, y=50, d=0. 15 48 12 Map of' case: 4=2. 6, @=50, d=0. 15 49...
Jiang, Boyang
2012-02-14T23:59:59.000Z
As the forecasting models become more sophisticated in their physics and possible depictions of the nearshore hydrodynamics, they also become increasingly sensitive to errors in the inputs. These input errors include: mis-specification of the input...
A TIME ESTIMATE FOR CONSOLIDATION AND DISINTEGRATION OF AN ASTEROID RUBBLE PILE. THE SIMPLEST model shows that an asteroid rubble pile evolves, depending on the parameter V2 d (where V rubble pile to survive for a long time, and on the other hand, even without tidal effects, it prevents
Hong, Don
AND ESTIMATION FOR LUNG CANCER PATIENTS Xingchen Yuana , Don Hongb , and Yu Shyrc,d a Fermilab, Batavia, IL 60510, Nashville, TN 37232, USA d Department of Statistics, National Cheng Kung University, Taiwan, ROC Lung cancer for a group of lung cancer patients for survival study, the covariates in the hazard function are estimated
Stukey, Jared D.
2011-02-22T23:59:59.000Z
, individual bole height (IBH), diameter at breast height (DBH), length of crown (CrHT), and age for use in TAMBEETLE; (2) to estimate individual tree age using lidar-estimated height and site index provided by the United States Department of Agriculture (USDA...
Estimating Temperature Distributions In Geothermal Areas Using...
an analytical model, showing that the errors in neuronet temperature estimates based on well log data derive from: (a) the neuronet "education level" (which depends on the amount...
Estimate product quality with ANNs
Brambilla, A. [Univ. of Pisa (Italy); Trivella, F. [Adicon Advanced Distillation Control SrL, Pisa (Italy)
1996-09-01T23:59:59.000Z
Artificial neural networks (ANNs) have been applied to predict catalytic reformer octane number (ON) and gasoline splitter product qualities. Results show that ANNs are a valuable tool to derive fast and accurate product quality measurements, and offer a low-cost alternative to online analyzers or rigorous mathematical models. The paper describes product quality measurements, artificial neural networks, ANN structure, estimating gasoline octane numbers, and estimating naphtha splitter product qualities.
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]
McCoy, Renata; Xie, Shaocheng
The ARM CMBE-ATM [Xie, McCoy, Klein et al.] data file contains a best estimate of several selected atmospheric quantities from ACRF observations and NWP analysis data.
Souradeep, Tarun
Saha,1,2,3,4, Pankaj Jain,4, and Tarun Souradeep1,x 1 IUCAA, Post Bag 4, Ganeshkhind, Pune-411007 of CMB power spectrum estimation was proposed by Saha et al. 2006. This methodology demonstrates
Kupke, Joshua Scott
2011-02-22T23:59:59.000Z
quantitative computed tomography (pQCT), mechanical testing in two different loading conditions, and estimated strength indices. Adult male Sprague-Dawley rats (6-mo) were grouped into baseline (BL), ambulatory cage control (CC) and hindlimb unloaded (HU); HU...
Interconnect Delay and Area Estimation for Multiple-Pin Nets
Pan, David Z.
,000,000 second = 3 years ! #12;Needs for Efficient Interconnect Estimation Models nn EfficiencyEfficiency nn
Estimated United States Residential Energy Use in 2005
Smith, C A; Johnson, D M; Simon, A J; Belles, R D
2011-12-12T23:59:59.000Z
A flow chart depicting energy flow in the residential sector of the United States economy in 2005 has been constructed from publicly available data and estimates of national energy use patterns. Approximately 11,000 trillion British Thermal Units (trBTUs) of electricity and fuels were used throughout the United States residential sector in lighting, electronics, air conditioning, space heating, water heating, washing appliances, cooking appliances, refrigerators, and other appliances. The residential sector is powered mainly by electricity and natural gas. Other fuels used include petroleum products (fuel oil, liquefied petroleum gas and kerosene), biomass (wood), and on-premises solar, wind, and geothermal energy. The flow patterns represent a comprehensive systems view of energy used within the residential sector.
Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]
1997-03-28T23:59:59.000Z
This chapter focuses on the components (or elements) of the cost estimation package and their documentation.
Paris-Sud XI, Université de
1 Rating curves and estimation of average water depth at the upper Negro River based on satellite for 21 ``virtual gauge stations'' located at the upper Negro River (Amazon Basin, Brazil). A virtual station can be defined as any crossing of water body surface (i.e., large rivers) by radar altimeter
Estimated Carbon Dioxide Emissions in 2008: United States
Smith, C A; Simon, A J; Belles, R D
2011-04-01T23:59:59.000Z
Flow charts depicting carbon dioxide emissions in the United States have been constructed from publicly available data and estimates of state-level energy use patterns. Approximately 5,800 million metric tons of carbon dioxide were emitted throughout the United States for use in power production, residential, commercial, industrial, and transportation applications in 2008. Carbon dioxide is emitted from the use of three major energy resources: natural gas, coal, and petroleum. The flow patterns are represented in a compact 'visual atlas' of 52 state-level (all 50 states, the District of Columbia, and one national) carbon dioxide flow charts representing a comprehensive systems view of national CO{sub 2} emissions. Lawrence Livermore National Lab (LLNL) has published flow charts (also referred to as 'Sankey Diagrams') of important national commodities since the early 1970s. The most widely recognized of these charts is the U.S. energy flow chart (http://flowcharts.llnl.gov). LLNL has also published charts depicting carbon (or carbon dioxide potential) flow and water flow at the national level as well as energy, carbon, and water flows at the international, state, municipal, and organizational (i.e. United States Air Force) level. Flow charts are valuable as single-page references that contain quantitative data about resource, commodity, and byproduct flows in a graphical form that also convey structural information about the system that manages those flows. Data on carbon dioxide emissions from the energy sector are reported on a national level. Because carbon dioxide emissions are not reported for individual states, the carbon dioxide emissions are estimated using published energy use information. Data on energy use is compiled by the U.S. Department of Energy's Energy Information Administration (U.S. EIA) in the State Energy Data System (SEDS). SEDS is updated annually and reports data from 2 years prior to the year of the update. SEDS contains data on primary resource consumption, electricity generation, and energy consumption within each economic sector. Flow charts of state-level energy usage and explanations of the calculations and assumptions utilized can be found at: http://flowcharts.llnl.gov. This information is translated into carbon dioxide emissions using ratios of carbon dioxide emissions to energy use calculated from national carbon dioxide emissions and national energy use quantities for each particular sector. These statistics are reported annually in the U.S. EIA's Annual Energy Review. Data for 2008 (US. EIA, 2010) was updated in August of 2010. This is the first presentation of a comprehensive state-level package of flow charts depicting carbon dioxide emissions for the United States.
Check Estimates and Independent Costs
Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]
1997-03-28T23:59:59.000Z
Check estimates and independent cost estimates (ICEs) are tools that can be used to validate a cost estimate. Estimate validation entails an objective review of the estimate to ensure that estimate criteria and requirements have been met and well documented, defensible estimate has been developed. This chapter describes check estimates and their procedures and various types of independent cost estimates.
Input estimation from measured structural response
Harvey, Dustin [Los Alamos National Laboratory; Cross, Elizabeth [Los Alamos National Laboratory; Silva, Ramon A [Los Alamos National Laboratory; Farrar, Charles R [Los Alamos National Laboratory; Bement, Matt [Los Alamos National Laboratory
2009-01-01T23:59:59.000Z
This report will focus on the estimation of unmeasured dynamic inputs to a structure given a numerical model of the structure and measured response acquired at discrete locations. While the estimation of inputs has not received as much attention historically as state estimation, there are many applications where an improved understanding of the immeasurable input to a structure is vital (e.g. validating temporally varying and spatially-varying load models for large structures such as buildings and ships). In this paper, the introduction contains a brief summary of previous input estimation studies. Next, an adjoint-based optimization method is used to estimate dynamic inputs to two experimental structures. The technique is evaluated in simulation and with experimental data both on a cantilever beam and on a three-story frame structure. The performance and limitations of the adjoint-based input estimation technique are discussed.
Kernel Density Based Linear Regression Estimate and Zhibiao Zhao
Zhao, Zhibiao
Kernel Density Based Linear Regression Estimate Weixin Yao and Zhibiao Zhao Abstract For linear regression models with non-normally distributed errors, the least squares estimate (LSE) will lose some words: EM algorithm, Kernel density estimate, Least squares estimate, Linear regression, Maximum
State energy data report 1994: Consumption estimates
NONE
1996-10-01T23:59:59.000Z
This document provides annual time series estimates of State-level energy consumption by major economic sector. The estimates are developed in the State Energy Data System (SEDS), operated by EIA. SEDS provides State energy consumption estimates to members of Congress, Federal and State agencies, and the general public, and provides the historical series needed for EIA`s energy models. Division is made for each energy type and end use sector. Nuclear electric power is included.
Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]
1997-03-28T23:59:59.000Z
The chapter describes the estimates required on government-managed projects for both general construction and environmental management.
and a power systems blackout model of cascading transmission line overloads. The comparisons suggest]. CASCADE contains no power sys- tem modeling, but does seem to approximately capture some of the salient and Renewable Energy, Office of Power Technologies, Transmission Reliability Program of the U.S. Department
Fernandez, Thomas
of the price of European-style options. However, the basic assumptions on the assets and market made in the B-S model are ideal. Furthermore, a lot of factors which might affect the prices of options have not been) are applied to forecast the prices of stock options by using the six basic factors in the B-S model
MODEL OF THE .MIGRATION OF ALBACORE IN THE NORTH PACIFIC OCEAN
MODEL OF THE .MIGRATION OF ALBACORE IN THE NORTH PACIFIC OCEAN .By TAMIO OTSU and RICHARD N. UCHIDA of the migration of albacore in the North Pacific Ocean has been developed. This model is consistent with the hypothesis that there is a single population of albacore in the North Pacific Ocean. . The model depicts
Koffi, Brigitte; Schultz, Michael; Breon, Francois-Marie; Griesfeller, Jan; Winker, D.; Balkanski, Y.; Bauer, Susanne E.; Berntsen, T.; Chin, Mian; Collins, William D.; Dentener, Frank; Diehl, Thomas; Easter, Richard C.; Ghan, Steven J.; Ginoux, P.; Gong, S.; Horowitz, L.; Iversen, T.; Kirkevag, A.; Koch, Dorothy; Krol, Maarten; Myhre, G.; Stier, P.; Takemura, T.
2012-05-19T23:59:59.000Z
The CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) layer product is used for a multimodel evaluation of the vertical distribution of aerosols. Annual and seasonal aerosol extinction profiles are analyzed over 13 sub-continental regions representative of industrial, dust, and biomass burning pollution, from CALIOP 2007-2009 observations and from AeroCom (Aerosol Comparisons between Observations and Models) 2000 simulations. An extinction mean height diagnostic (Z{sub a}) is defined to quantitatively assess the models performance. It is calculated over the 0-6 km and 0-10 km altitude ranges by weighting the altitude of each 100 m altitude layer by its aerosol extinction coefficient. The mean extinction profiles derived from CALIOP layer products provide consistent regional and seasonal specificities and a low inter-annual variability. While the outputs from most models are significantly correlated with the observed Z{sub a} climatologies, some do better than others, and 2 of the 12 models perform particularly well in all seasons. Over industrial and maritime regions, most models show higher Z{sub a} than observed by CALIOP, whereas over the African and Chinese dust source regions, Z{sub a} is underestimated during Northern Hemisphere Spring and Summer. The positive model bias in Z{sub a} is mainly due to an overestimate of the extinction above 6 km. Potential CALIOP and model limitations, and methodological factors that might contribute to the differences are discussed.
Fracture compliance estimation using borehole tube waves
Bakku, Sudhish Kumar
We tested two models, one for tube-wave generation and the other for tube-wave attenuation at a fracture intersecting a borehole that can be used to estimate fracture compliance, fracture aperture, and lateral extent. In ...
Broader source: Energy.gov [DOE]
This simple spreadsheet model estimates either the flow rate required to produce a specified level of power output, or the power output that can be produced from a specified flow rate.
Bisht, Gautam
2010-01-01T23:59:59.000Z
The Fourth Assessment Report of the Intergovernmental Panel on Climate Change acknowledged that the lack of relevant observations in various regions of the world is a crucial gap in understanding and modeling impacts of ...
Akbarnejad Nesheli, Babak
2012-07-16T23:59:59.000Z
stabilized production forecast than traditional DCA models and in this work it is shown that it produces unchanging EUR forecasts after only two-three years of production data are available in selected reservoirs, notably the Barnett Shale...
Guillermo A. González; J. Ibáñez; Jerson I. Reina
2011-11-16T23:59:59.000Z
A family of models of thin discs and spheroidal haloes with masses in a linear relationship is presented. The models are obtained by considering the gravitational potential as the superposition of two independent components, a potential generated by the thin galactic disc and a potential generated by the spheroidal halo. The models leads to an expression for the circular velocity that can be adjusted very accurately to the observed rotation curves of some specific galaxies, in such a way that the models are stable against radial and vertical perturbations. Two particular models for galaxies NGC4389 and UGC6969 are obtained by adjusting the circular velocity with data taken from the recent paper by Verheijen & Sancici (2001). The values of the halo mass, the disc mass and the total mass for these two galaxies are computed in such a way that we obtain a very narrow interval of values for these quantities. Furthermore, the values of masses here obtained are in perfect agreement with the expected order of magnitude and with the relative order of magnitude between the halo mass and the disc mass.
Stefanopoulou, Anna
modeling is connected with the hybrid vehicle design, scale-up, optimization and control issues of Hybrid characteristics to be widely used in the hybrid vehicles, thanks to its best energy-to-weight ratios, no memory. INTRODUCTION Lithium-ion battery is the core of new plug-in hybrid- electrical vehicles (PHEV) as well
Noé, Reinhold
current loss in interior permanent magnet machines is presented. To check the generality of the developed model, two different types of commonly employed interior permanent magnet machines are considered. 2D method, interior permanent magnet synchronous motor I. INTRODUCTION NTERIOR permanent magnet (IPM) motors
Blumenthal, Jurg M.; Thompson, Wayne
2009-06-12T23:59:59.000Z
This publication explains how to estimate the grain yield of a corn crop before harvest. An interactive grain yield calculator is included. 6 pages, 3 tables, 1 figure....
Faceted Models of Blog Feeds Department of Computer
Meng, Weiyi
Faceted Models of Blog Feeds Lifeng Jia Department of Computer Science University of Illinois@cs.binghamton.edu ABSTRACT Faceted blog distillation aims at retrieving the blogs that are not only relevant to a query blogs depict various topics related to the personal experiences of bloggers while official blogs deliver
A Configurable Reference Modelling Language1 M. Rosemanna
van der Aalst, Wil
, Configuration, Event-driven Process Chains 1 This research project is financially supported by SAP Corporate reference models "just" depict the possible system capabilities and cannot sufficiently guide the project, Eindhoven, The Netherlands, w.m.p.v.d.aalst@tm.tue.nl Abstract Enterprise Systems (ES) are comprehensive off
Distributed Road Grade Estimation
Johansson, Karl Henrik
Distributed Road Grade Estimation for Heavy Duty Vehicles PER SAH LHOLM Doctoral Thesis in Automatic Control Stockholm, Sweden 2011 #12;Distributed Road Grade Estimation for Heavy Duty Vehicles PER state-of-charge control decrease the energy consumption of vehicles and increase the safety
SPACE TECHNOLOGY Actual Estimate
technology readiness of new missions, mitigate their technological risks, improve the quality of cost estimates, and thereby contribute to better overall mission cost management..." Space Technology investmentsSPACE TECHNOLOGY TECH-1 Actual Estimate Budget Authority (in $ millions) FY 2011 FY 2012 FY 2013 FY
Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]
1997-03-28T23:59:59.000Z
Specialty costs are those nonstandard, unusual costs that are not typically estimated. Costs for research and development (R&D) projects involving new technologies, costs associated with future regulations, and specialty equipment costs are examples of specialty costs. This chapter discusses those factors that are significant contributors to project specialty costs and methods of estimating costs for specialty projects.
Tight gas reservoirs: A visual depiction
Not Available
1993-12-01T23:59:59.000Z
Future gas supplies in the US will depend on an increasing contribution from unconventional sources such as overpressured and tight gas reservoirs. Exploitation of these resources and their conversion to economically producible gas reserves represents a major challenge. Meeting this challenge will require not only the continuing development and application of new technologies, but also a detailed understanding of the complex nature of the reservoirs themselves. This report seeks to promote understanding of these reservoirs by providing examples. Examples of gas productive overpressured tight reservoirs in the Greater Green River Basin, Wyoming are presented. These examples show log data (raw and interpreted), well completion and stimulation information, and production decline curves. A sampling of wells from the Lewis and Mesaverde formations are included. Both poor and good wells have been chosen to illustrate the range of productivity that is observed. The second section of this document displays decline curves and completion details for 30 of the best wells in the Greater Green River Basin. These are included to illustrate the potential that is present when wells are fortuitously located with respect to local stratigraphy and natural fracturing, and are successfully hydraulically fractured.
Property:Depiction | Open Energy Information
AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on DeliciousPlasmaP a gHigh PlainsOttawa, Ontario:Information PropertyPropertyform ViewProperty Edit with
None
2011-06-30T23:59:59.000Z
A conceptual model was developed for the Arches Province that integrates geologic and hydrologic information on the Eau Claire and Mt. Simon formations into a geocellular model. The conceptual model describes the geologic setting, stratigraphy, geologic structures, hydrologic features, and distribution of key hydraulic parameters. The conceptual model is focused on the Mt. Simon sandstone and Eau Claire formations. The geocellular model depicts the parameters and conditions in a numerical array that may be imported into the numerical simulations of carbon dioxide (CO{sub 2}) storage. Geophysical well logs, rock samples, drilling logs, geotechnical test results, and reservoir tests were evaluated for a 500,000 km{sup 2} study area centered on the Arches Province. The geologic and hydraulic data were integrated into a three-dimensional (3D) grid of porosity and permeability, which are key parameters regarding fluid flow and pressure buildup due to CO{sub 2} injection. Permeability data were corrected in locations where reservoir tests have been performed in Mt. Simon injection wells. The final geocellular model covers an area of 600 km by 600 km centered on the Arches Province. The geocellular model includes a total of 24,500,000 cells representing estimated porosity and permeability distribution. CO{sub 2} injection scenarios were developed for on-site and regional injection fields at rates of 70 to 140 million metric tons per year.
Estimating the Wind Resource in Uttarakhand: Comparison of Dynamic...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
resource, the authors of this study employed a dynamic down scaling method with the Weather Research and Forecasting model, providing detailed estimates of winds at...
Optimization Online - Sparse/Robust Estimation and Kalman ...
Aleksandr Aravkin
2012-02-29T23:59:59.000Z
Feb 29, 2012 ... Sparse/Robust Estimation and Kalman Smoothing with Nonsmooth Log-Concave Densities: Modeling, Computation, and Theory. Aleksandr ...
Ef?cient Parameter Estimation Using Implicit Statistical Inference
Patch Occupancy Models of Metapopulation Dynamics: Ef?cient Parameter. Estimation Using Implicit Statistical Inference. Atte Moilanen. Ecology, Vol. 80, No
Radiological Source Term Estimates for the February 14, 2014...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
event. This document corresponds to Appendix D: Modeling Integrated Summary Report of the Technical Assessment Team Report. Radiological Source Term Estimates for the February 14,...
Estimating exposure of terrestrial wildlife to contaminants
Sample, B.E.; Suter, G.W. II
1994-09-01T23:59:59.000Z
This report describes generalized models for the estimation of contaminant exposure experienced by wildlife on the Oak Ridge Reservation. The primary exposure pathway considered is oral ingestion, e.g. the consumption of contaminated food, water, or soil. Exposure through dermal absorption and inhalation are special cases and are not considered hereIN. Because wildlife mobile and generally consume diverse diets and because environmental contamination is not spatial homogeneous, factors to account for variation in diet, movement, and contaminant distribution have been incorporated into the models. To facilitate the use and application of the models, life history parameters necessary to estimate exposure are summarized for 15 common wildlife species. Finally, to display the application of the models, exposure estimates were calculated for four species using data from a source operable unit on the Oak Ridge Reservation.
Cardiovascular Signal Decomposition and Estimation with the Extended Kalman Smoother
Cardiovascular Signal Decomposition and Estimation with the Extended Kalman Smoother James Mc of cardiovascular signals that can be used with the extended Kalman filter or smoother to simultaneously estimate with the extended Kalman filter and smoother to estimate and track all the model parameters of interest including
Estimation of building occupancy levels through environmental signals deconvolution
Johansson, Karl Henrik
, and ventilation actuation signals in order to identify a dynamic model. The building occupancy estimation problem Abstract We address the problem of estimating the occupancy lev- els in rooms using the information is formulated as a regularized deconvolution problem, where the estimated occupancy is the input that, when
A simple method to estimate interwell autocorrelation
Pizarro, J.O.S.; Lake, L.W. [Univ. of Texas, Austin, TX (United States)
1997-08-01T23:59:59.000Z
The estimation of autocorrelation in the lateral or interwell direction is important when performing reservoir characterization studies using stochastic modeling. This paper presents a new method to estimate the interwell autocorrelation based on parameters, such as the vertical range and the variance, that can be estimated with commonly available data. We used synthetic fields that were generated from stochastic simulations to provide data to construct the estimation charts. These charts relate the ratio of areal to vertical variance and the autocorrelation range (expressed variously) in two directions. Three different semivariogram models were considered: spherical, exponential and truncated fractal. The overall procedure is demonstrated using field data. We find that the approach gives the most self-consistent results when it is applied to previously identified facies. Moreover, the autocorrelation trends follow the depositional pattern of the reservoir, which gives confidence in the validity of the approach.
Operated device estimation framework
Rengarajan, Janarthanan
2009-05-15T23:59:59.000Z
Protective device estimation is a challenging task because there are numerous protective devices present in a typical distribution system. Among various protective devices, auto-reclosers and fuses are the main overcurrent protection on distribution...
Operated device estimation framework
Rengarajan, Janarthanan
2009-05-15T23:59:59.000Z
protective device estimation algorithm which helps in identifying which protective devices have operated to clear a short circuit condition. The algorithm uses manufacturer’s device details, power quality data measured from substation monitoring devices...
Estimation of food consumption
Callaway, J.M. Jr.
1992-04-01T23:59:59.000Z
The research reported in this document was conducted as a part of the Hanford Environmental Dose Reconstruction (HEDR) Project. The objective of the HEDR Project is to estimate the radiation doses that people could have received from operations at the Hanford Site. Information required to estimate these doses includes estimates of the amounts of potentially contaminated foods that individuals in the region consumed during the study period. In that general framework, the objective of the Food Consumption Task was to develop a capability to provide information about the parameters of the distribution(s) of daily food consumption for representative groups in the population for selected years during the study period. This report describes the methods and data used to estimate food consumption and presents the results developed for Phase I of the HEDR Project.
Estimating Power System Dynamic States Using Extended Kalman Filter
Huang, Zhenyu; Schneider, Kevin P.; Nieplocha, Jaroslaw; Zhou, Ning
2014-10-31T23:59:59.000Z
Abstract—The state estimation tools which are currently deployed in power system control rooms are based on a steady state assumption. As a result, the suite of operational tools that rely on state estimation results as inputs do not have dynamic information available and their accuracy is compromised. This paper investigates the application of Extended Kalman Filtering techniques for estimating dynamic states in the state estimation process. The new formulated “dynamic state estimation” includes true system dynamics reflected in differential equations, not like previously proposed “dynamic state estimation” which only considers the time-variant snapshots based on steady state modeling. This new dynamic state estimation using Extended Kalman Filter has been successfully tested on a multi-machine system. Sensitivity studies with respect to noise levels, sampling rates, model errors, and parameter errors are presented as well to illustrate the robust performance of the developed dynamic state estimation process.
Statistical Estimation of Quantum Tomography Protocols Quality
Yu. I. Bogdanov; G. Brida; M. Genovese; S. P. Kulik; E. V. Moreva; A. P. Shurupov
2010-02-18T23:59:59.000Z
A novel operational method for estimating the efficiency of quantum state tomography protocols is suggested. It is based on a-priori estimation of the quality of an arbitrary protocol by means of universal asymptotic fidelity distribution and condition number, which takes minimal value for better protocol. We prove the adequacy of the method both with numerical modeling and through the experimental realization of several practically important protocols of quantum state tomography.
State energy data report 1993: Consumption estimates
NONE
1995-07-01T23:59:59.000Z
The State Energy Data Report (SEDR) provides annual time series estimates of State-level energy consumption by major economic sector. The estimates are developed in the State Energy Data System (SEDS), which is maintained and operated by the Energy Information Administration (EIA). The goal in maintaining SEDS is to create historical time series of energy consumption by State that are defined as consistently as possible over time and across sectors. SEDS exists for two principal reasons: (1) to provide State energy consumption estimates to Members of Congress, Federal and State agencies, and the general public; and (2) to provide the historical series necessary for EIA`s energy models.
State energy data report 1995 - consumption estimates
NONE
1997-12-01T23:59:59.000Z
The State Energy Data Report (SEDR) provides annual time series estimates of State-level energy consumption by major economic sectors. The estimates are developed in the State Energy Data System (SEDS), which is maintained and operated by the Energy Information Administration (EIA). The goal in maintaining SEDS exists for two principal reasons: (1) to provide State energy consumption estimates to Members of Congress, Federal and State agencies, and the general public, and (2) to provide the historical series necessary for EIA`s energy models.
Hewitt, Natalie Case
2012-07-16T23:59:59.000Z
further research. 8 2. METHODS 2.1 Model Design The model is constructed of ordinary differential equations, solved using MatlabTM?s fourth-order Runge-Kutta methods(The Math Works, 2009) and uses a carbon currency to depict two phytoplankton...
Ridge Regression Estimation for Survey Samples Mingue Park
Yang, Min
Ridge Regression Estimation for Survey Samples Mingue Park and Min Yang Korea University and University of Missouri Abstract A procedure for constructing a vector of regression weights is considered. Under the re- gression superpopulation model, the ridge regression estimator that has minimum model mean
Thermodynamic estimation: Ionic materials
Glasser, Leslie, E-mail: l.glasser@curtin.edu.au
2013-10-15T23:59:59.000Z
Thermodynamics establishes equilibrium relations among thermodynamic parameters (“properties”) and delineates the effects of variation of the thermodynamic functions (typically temperature and pressure) on those parameters. However, classical thermodynamics does not provide values for the necessary thermodynamic properties, which must be established by extra-thermodynamic means such as experiment, theoretical calculation, or empirical estimation. While many values may be found in the numerous collected tables in the literature, these are necessarily incomplete because either the experimental measurements have not been made or the materials may be hypothetical. The current paper presents a number of simple and relible estimation methods for thermodynamic properties, principally for ionic materials. The results may also be used as a check for obvious errors in published values. The estimation methods described are typically based on addition of properties of individual ions, or sums of properties of neutral ion groups (such as “double” salts, in the Simple Salt Approximation), or based upon correlations such as with formula unit volumes (Volume-Based Thermodynamics). - Graphical abstract: Thermodynamic properties of ionic materials may be readily estimated by summation of the properties of individual ions, by summation of the properties of ‘double salts’, and by correlation with formula volume. Such estimates may fill gaps in the literature, and may also be used as checks of published values. This simplicity arises from exploitation of the fact that repulsive energy terms are of short range and very similar across materials, while coulombic interactions provide a very large component of the attractive energy in ionic systems. Display Omitted - Highlights: • Estimation methods for thermodynamic properties of ionic materials are introduced. • Methods are based on summation of single ions, multiple salts, and correlations. • Heat capacity, entropy, lattice energy, enthalpy, Gibbs energy values are available.
Distributed Energy Resources Market Diffusion Model
Maribu, Karl Magnus; Firestone, Ryan; Marnay, Chris; Siddiqui,Afzal S.
2006-06-16T23:59:59.000Z
Distributed generation (DG) technologies, such as gas-fired reciprocating engines and microturbines, have been found to be economically beneficial in meeting commercial-sector electrical, heating, and cooling loads. Even though the electric-only efficiency of DG is lower than that offered by traditional central stations, combined heat and power (CHP) applications using recovered heat can make the overall system energy efficiency of distributed energy resources (DER) greater. From a policy perspective, however, it would be useful to have good estimates of penetration rates of DER under various economic and regulatory scenarios. In order to examine the extent to which DER systems may be adopted at a national level, we model the diffusion of DER in the US commercial building sector under different technical research and technology outreach scenarios. In this context, technology market diffusion is assumed to depend on the system's economic attractiveness and the developer's knowledge about the technology. The latter can be spread both by word-of-mouth and by public outreach programs. To account for regional differences in energy markets and climates, as well as the economic potential for different building types, optimal DER systems are found for several building types and regions. Technology diffusion is then predicted via two scenarios: a baseline scenario and a program scenario, in which more research improves DER performance and stronger technology outreach programs increase DER knowledge. The results depict a large and diverse market where both optimal installed capacity and profitability vary significantly across regions and building types. According to the technology diffusion model, the West region will take the lead in DER installations mainly due to high electricity prices, followed by a later adoption in the Northeast and Midwest regions. Since the DER market is in an early stage, both technology research and outreach programs have the potential to increase DER adoption, and thus, shift building energy consumption to a more efficient alternative.
Park, J.K. [Inje Univ., Kimhae (Korea, Republic of). Dept. of Environmental Sciences; Allen, E.R. [Univ. of Florida, Gainesville, FL (United States). Dept. of Environmental Engineering Sciences
1997-12-31T23:59:59.000Z
The harmful effects of dry acid deposition on terrestrial ecosystems could be as significant as those from wet acid deposition. Dry deposition involves removal of air pollutants to surfaces by sedimentation, impaction, interception and diffusion. Dry deposition velocities and fluxes of air pollutants, such as SO{sub 2}(g), O{sub 3}(g), HNO{sub 3}(g), submicron particulates, NO{sub 3}{sup {minus}}(s), and SO{sub 4}{sup 2{minus}}(s), have been estimated according to local meteorological elements in the boundary layer. The model that was used for these calculations is the multiple layer resistance model developed by Hicks. It consists of multiple layered resistances including an aerodynamic resistance, a boundary layer resistance, and a surface resistance. Meteorological data were recorded on an hourly basis from July, 1990 to June, 1991 at the Austin Cary forest site, near Gainesville FL. Weekly integrated samples of ambient dry deposition species were collected at the site using triple filter packs and chemically analyzed. For the study period at this site annual average dry deposition velocities were estimated to be : 0.87--0.07 [cm/s] for SO{sub 2}(g), 0.65--0.11 [cm/s] for O{sub 3}(g), 1.20--0.14 [cm/s] for HNO{sub 3}(g), 0.0045--0.0006 [cm/s] for submicron particulates, and 0.089--0.014 [cm/s] for NO{sub 3}{sup {minus}}(s) and SO{sub 4}{sup 2{minus}}(s). Trends observed in daily mean deposition velocities are largely seasonal, indicated by larger deposition velocities for the summer season and smaller deposition velocities for the winter season. Note that the summer season at this southern US site extends from April through October (7 months) and the winter season extends from December through February. Monthly and weekly averaged values for deposition velocities do not show large differences over the year but do show a tendency for increased deposition velocities in summer and decreased values in winter.
Building unbiased estimators from non-gaussian likelihoods with application to shear estimation
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
Madhavacheril, Mathew S. [Stony Brook Univ., NY (United States); Slosar, Anze [Brookhaven National Lab. (BNL), Upton, NY (United States); McDonald, Patrick [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Sehgal, Neelima [Stony Brook Univ., NY (United States)
2015-01-01T23:59:59.000Z
We develop a general framework for generating estimators of a given quantity which are unbiased to a given order in the difference between the true value of the underlying quantity and the fiducial position in theory space around which we expand the likelihood. We apply this formalism to rederive the optimal quadratic estimator and show how the replacement of the second derivative matrix with the Fisher matrix is a generic way of creating an unbiased estimator (assuming choice of the fiducial model is independent of data). Next we apply the approach to estimation of shear lensing, closely following the work of Bernstein and Armstrong (2014). Our first order estimator reduces to their estimator in the limit of zero shear, but it also naturally allows for the case of non-constant shear and the easy calculation of correlation functions or power spectra using standard methods. Both our first-order estimator and Bernstein and Armstrong’s estimator exhibit a bias which is quadratic in true shear. Our third-order estimator is, at least in the realm of the toy problem of Bernstein and Armstrong, unbiased to 0.1% in relative shear errors ?g/g for shears up to |g| = 0.2.
Building unbiased estimators from non-gaussian likelihoods with application to shear estimation
DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)
Madhavacheril, Mathew S.; Slosar, Anze; McDonald, Patrick; Sehgal, Neelima
2015-01-01T23:59:59.000Z
We develop a general framework for generating estimators of a given quantity which are unbiased to a given order in the difference between the true value of the underlying quantity and the fiducial position in theory space around which we expand the likelihood. We apply this formalism to rederive the optimal quadratic estimator and show how the replacement of the second derivative matrix with the Fisher matrix is a generic way of creating an unbiased estimator (assuming choice of the fiducial model is independent of data). Next we apply the approach to estimation of shear lensing, closely following the workmore »of Bernstein and Armstrong (2014). Our first order estimator reduces to their estimator in the limit of zero shear, but it also naturally allows for the case of non-constant shear and the easy calculation of correlation functions or power spectra using standard methods. Both our first-order estimator and Bernstein and Armstrong’s estimator exhibit a bias which is quadratic in true shear. Our third-order estimator is, at least in the realm of the toy problem of Bernstein and Armstrong, unbiased to 0.1% in relative shear errors ?g/g for shears up to |g| = 0.2.« less
MULTIVARIATE REGRESSION S-ESTIMATORS FOR ROBUST ESTIMATION AND INFERENCE
Van Aelst, Stefan
1 MULTIVARIATE REGRESSION S-ESTIMATORS FOR ROBUST ESTIMATION AND INFERENCE Stefan Van Aelst-estimators for multivariate regression. We study the robustness of the estimators in terms of their breakdown point and in and multivariate location and scatter. Furthermore we develop a fast and robust bootstrap method
Emission estimates for air pollution transport models.
Streets, D. G.
1998-10-09T23:59:59.000Z
The results of studies of energy consumption and emission inventories in Asia are discussed. These data primarily reflect emissions from fuel combustion (both biofuels and fossil fuels) and were collected to determine emissions of acid-deposition precursors (SO{sub 2} and NO{sub x}) and greenhouse gases (CO{sub 2} CO, CH{sub 4}, and NMHC) appropriate to RAINS-Asia regions. Current work is focusing on black carbon (soot), volatile organic compounds, and ammonia.
Estimating transition times for a model of
Mitchener, W. Garrett
= mean usage rate of G2 dm dt = birth q(m) - death m 0.0 0.2 0.4 0.6 0.8 1.0 0.2 0.4 0.6 0.8 1.0 Mean at a rate k K Simplify K = 1: Each agent uses G1 (state 0) or G2 (state 1) @ Ck = number youth in state kD = death rate: each time step each adult dies with prob- ability pD = rD N , replaced by sampling from
Probabilistic models for mobile phone trajectory estimation
Thiagarajan, Arvind
2011-01-01T23:59:59.000Z
This dissertation is concerned with the problem of determining the track or trajectory of a mobile device - for example, a sequence of road segments on an outdoor map, or a sequence of rooms visited inside a building - in ...
Use of Cost Estimating Relationships
Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]
1997-03-28T23:59:59.000Z
Cost Estimating Relationships (CERs) are an important tool in an estimator's kit, and in many cases, they are the only tool. Thus, it is important to understand their limitations and characteristics. This chapter discusses considerations of which the estimator must be aware so the Cost Estimating Relationships can be properly used.
Essays on Estimation of Inflation Equation
Kim, Woong
2009-05-15T23:59:59.000Z
. . . . . . . . . . . . 11 1. Models . . . . . . . . . . . . . . . . . . . . . . . . . . 11 2. Numerical Analysis for the Theoretical Relationship . 13 3. Numerical Analysis for the Empirical Issues . . . . . . 25 C. Alternative Kurtosis... 3. Detection of Outliers . . . . . . . . . . . . . . . . . . . 71 C. Empirical Results . . . . . . . . . . . . . . . . . . . . . . . 73 D. Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 IV ESTIMATION OF HYBRID PHILLIPS CURVE...
IFE Target Fabrication, Delivery, and Cost Estimates
Foam Shell Generation Seal Coat Formation CO2 Drying High-Z Sputter CoatingDT Filling DT LayeringIFE Target Fabrication, Delivery, and Cost Estimates N. B. Alexander, L. Brown, D. Callahan, P degrees... SOMBRERO 3-D model for neutronics analysisLaser Fusion HIF - HYLIFE-II ZFE #12;An initial cost
Filtering and parameter estimation for electricity
Fournier, John J.F.
Filtering and parameter estimation for electricity markets by Alberto Molina-Escobar B to be particularly difficult for electricity, where markets are complex, and ex- hibit a number of unique features, mainly due to the problems involved in storing electricity. In this thesis we propose three models
Monotonic Local Decay Estimates
Avy Soffer
2011-10-29T23:59:59.000Z
For the Hamiltonian operator H = -{\\Delta}+V(x) of the Schr\\"odinger Equation with a repulsive potential, the problem of local decay is considered. It is analyzed by a direct method, based on a new, L^2 bounded, propagation observable. The resulting decay estimate, is in certain cases monotonic in time, with no "Quantum Corrections". This method is then applied to some examples in one and higher dimensions. In particular the case of the Wave Equation on a Schwarzschild manifold is redone: Local decay, stronger than the known ones are proved (minimal loss of angular derivatives and lower order of radial derivatives of initial data). The method developed here can be an alternative in some cases to the Morawetz type estimates, with L^2-multipliers replacing the first order operators. It provides an alternative to Mourre's method, by including thresholds and high energies.
Kampa, Aleksander Edward
1988-01-01T23:59:59.000Z
) December 1988 Extremal Index Estimation (December 1988) Aleksander Edward Kampa, Ecole Centrale de Paris, France Chairman of Advisory Comittee: Dr. Tailen Hsing If (X ) is a strictly stationary sequence satisfying certain n dependence restrictions (e.... g. D or A), then the relationship between the extremal properties of (X ) and its associated independent sequence (X ) n n can. under certain conditions, be summed up by a single constant Be[0. 1]. called the extremal index. Results of extreme...
A Flexible Method of Estimating Luminosity Functions
Brandon C. Kelly; Xiaohui Fan; Marianne Vestergaard
2008-05-19T23:59:59.000Z
We describe a Bayesian approach to estimating luminosity functions. We derive the likelihood function and posterior probability distribution for the luminosity function, given the observed data, and we compare the Bayesian approach with maximum-likelihood by simulating sources from a Schechter function. For our simulations confidence intervals derived from bootstrapping the maximum-likelihood estimate can be too narrow, while confidence intervals derived from the Bayesian approach are valid. We develop our statistical approach for a flexible model where the luminosity function is modeled as a mixture of Gaussian functions. Statistical inference is performed using Markov chain Monte Carlo (MCMC) methods, and we describe a Metropolis-Hastings algorithm to perform the MCMC. The MCMC simulates random draws from the probability distribution of the luminosity function parameters, given the data, and we use a simulated data set to show how these random draws may be used to estimate the probability distribution for the luminosity function. In addition, we show how the MCMC output may be used to estimate the probability distribution of any quantities derived from the luminosity function, such as the peak in the space density of quasars. The Bayesian method we develop has the advantage that it is able to place accurate constraints on the luminosity function even beyond the survey detection limits, and that it provides a natural way of estimating the probability distribution of any quantities derived from the luminosity function, including those that rely on information beyond the survey detection limits.
REQUESTS FOR RETIREMENT ESTIMATE
Office of Environmental Management (EM)
AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE:1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:5 TablesExports to3,1,50022,3,,0,,6,1,Separation 23 362 of Thomas P.Oil,J. B.Department ofEnergyREQUEST FOR RETIREMENT ANNUITY ESTIMATE Instructions:
Baird, Matthew David
2012-01-01T23:59:59.000Z
additively non-separable linear regression model. First,the additively non-separable linear regression model matchesThe additively non-separable linear regression model nests
Using Photogrammetry to Estimate Tank Waste Volumes from Video
Field, Jim G. [Washington River Protection Solutions, LLC, Richland, WA (United States)
2013-03-27T23:59:59.000Z
Washington River Protection Solutions (WRPS) contracted with HiLine Engineering & Fabrication, Inc. to assess the accuracy of photogrammetry tools as compared to video Camera/CAD Modeling System (CCMS) estimates. This test report documents the results of using photogrammetry to estimate the volume of waste in tank 241-C-I04 from post-retrieval videos and results using photogrammetry to estimate the volume of waste piles in the CCMS test video.
Cheng, Shinko Yuanhsien
2007-01-01T23:59:59.000Z
Driver body-pose analysis . . . . . . . . . . . . . . . . .Body Pose Estimation . . . . . . . . . . . . . . . . .Mixture Model . . 4. Learning Pose using EM . . . . . .
Kalman filter data assimilation: Targeting observations and parameter estimation
Bellsky, Thomas, E-mail: bellskyt@asu.edu; Kostelich, Eric J.; Mahalov, Alex [School of Mathematical and Statistical Sciences, Arizona State University, Tempe, Arizona 85287 (United States)] [School of Mathematical and Statistical Sciences, Arizona State University, Tempe, Arizona 85287 (United States)
2014-06-15T23:59:59.000Z
This paper studies the effect of targeted observations on state and parameter estimates determined with Kalman filter data assimilation (DA) techniques. We first provide an analytical result demonstrating that targeting observations within the Kalman filter for a linear model can significantly reduce state estimation error as opposed to fixed or randomly located observations. We next conduct observing system simulation experiments for a chaotic model of meteorological interest, where we demonstrate that the local ensemble transform Kalman filter (LETKF) with targeted observations based on largest ensemble variance is skillful in providing more accurate state estimates than the LETKF with randomly located observations. Additionally, we find that a hybrid ensemble Kalman filter parameter estimation method accurately updates model parameters within the targeted observation context to further improve state estimation.
Image-based meteorologic visibility estimation
Graves, Nathan
2011-01-01T23:59:59.000Z
the estimated luminance. . . . . . . . . . . . . . . . . .Nephelometer . . . . . . 3.4.3 Luminance Meter . . . . 4intensity and the estimated luminance. . . . . . . . . .
State energy data report 1996: Consumption estimates
NONE
1999-02-01T23:59:59.000Z
The State Energy Data Report (SEDR) provides annual time series estimates of State-level energy consumption by major economic sectors. The estimates are developed in the Combined State Energy Data System (CSEDS), which is maintained and operated by the Energy Information Administration (EIA). The goal in maintaining CSEDS is to create historical time series of energy consumption by State that are defined as consistently as possible over time and across sectors. CSEDS exists for two principal reasons: (1) to provide State energy consumption estimates to Members of Congress, Federal and State agencies, and the general public and (2) to provide the historical series necessary for EIA`s energy models. To the degree possible, energy consumption has been assigned to five sectors: residential, commercial, industrial, transportation, and electric utility sectors. Fuels covered are coal, natural gas, petroleum, nuclear electric power, hydroelectric power, biomass, and other, defined as electric power generated from geothermal, wind, photovoltaic, and solar thermal energy. 322 tabs.
Parameter Estimation for the Heat Equation on Perforated Domains
Parameter Estimation for the Heat Equation on Perforated Domains H.T. Banks1 , D. Cioranescu2 , A for simulated data for heat flow in a porous medium. We consider data simulated from a model on a perforated Words: Inverse problems, parameter estimation, perforated domains, homogeniza- tion, thermal diffusion
DAMAGE ESTIMATION USING MULTI-OBJECTIVE GENETIC ALGORITHMS Faisal Shabbir
Boyer, Edmond
DAMAGE ESTIMATION USING MULTI-OBJECTIVE GENETIC ALGORITHMS Faisal Shabbir 1 , Piotr Omenzetter 2 1.omenzetter@abdn.ac.uk ABSTRACT It is common to estimate structural damage severity by updating a structural model against experimental responses at different damage states. When experimental results from the healthy and damaged
Conditional Regression Forests for Human Pose Estimation Pushmeet Kohli
Kohli, Pushmeet
Conditional Regression Forests for Human Pose Estimation Min Sun Pushmeet Kohli Jamie Shotton estimation from depth images. The conditional regression model proposed in the paper is general and can body joint prediction as a regression problem which avoids intermediate body part classification
Javier Ortensi; Abderrafi M Ougouag
2009-07-01T23:59:59.000Z
The Doppler feedback mechanism is a major contributor to the passive safety of gas-cooled, graphite-moderated high temperature reactors that use fuel based on Tristructural-Isotropic coated particles. It follows that the correct prediction of the magnitude and time-dependence of this feedback effect is essential to the conduct of safety analyses for these reactors. We present a fuel conduction model for obtaining better estimates of the temperature feedback during moderate and fast transients. The fuel model has been incorporated in the CYNOD-THERMIX-KONVEK suite of coupled codes as a single TRISO particle within each calculation cell. The heat generation rate is scaled down from the neutronic solution and a Dirichlet boundary condition is imposed as the bulk graphite temperature from the thermal-hydraulic solution. This simplified approach yields similar results to those obtained with more complex methods, requiring multi-TRISO calculations within one control volume, but with much less computational effort. We provide an analysis of the hypothetical total control ejection event in the PBMR-400 design that clearly depicts the improvement in the predictions of the fuel temperature.
Estimating long-term world coal production with logit and probit transforms David Rutledge
Low, Steven H.
Estimating long-term world coal production with logit and probit transforms David Rutledge form 27 October 2010 Accepted 27 October 2010 Available online 4 November 2010 Keywords: Coal reserves Coal resources Coal production estimates IPCC Logistic model Cumulative normal model An estimate
Geothermal Electricity Technology Evaluation Model (GETEM) Development...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
Electricity Technology Evaluation Model (GETEM) Development Geothermal Electricity Technology Evaluation Model (GETEM) Development Project objective: Provide a tool for estimating...
Estimation of dibaryon (OO) yields at RHIC energies
Zhong-Dao Lu
2002-07-02T23:59:59.000Z
The yields of dibaryon (Omega-Omega) in relativistic heavy ion collisions, especially at RHIC energies, are estimated by statistical model. The yields of hyperon Omega- and the ratio of dibaryon to Omega are also given.
Identification and Estimation of a Discrete Game of Complete Information
Bajari, Patrick
We discuss the identification and estimation of discrete games of complete information. Following Bresnahan and Reiss (1990, 1991), a discrete game is a generalization of a standard discrete choice model where utility ...
A reconciled estimate of ice-sheet mass balance
2012-01-01T23:59:59.000Z
Estimate of Ice-Sheet Mass Balance Andrew Shepherd, 1 * Erikand models of surface mass balance and glacial isostaticThis Ice Sheet Mass Balance Exercise (IMBIE) was facilitated
Genetic parameter estimation of mohair production traits in Angora goats
Podisi, Baitsi
1998-01-01T23:59:59.000Z
analyzed included fiber diameter (FD; n = 4329), grease fleece weight (FW; n = 7073), body weight (BW; n = 4171) and fertility (FERT; n = 2118). Heritability estimates were obtained for all the traits using REML procedures with a multivariate animal model...
Kundu, Debasis
11]), in biomedical signal processing ([12,13]), modeling of biological systems ([14,15]), radio location of distant problem in digital signal processing. In this paper, we consider the problem of estimation of parameters are present in a variety of signal processing applications and time series data analysis. The review work
Estimating Energy Savings in Compressed Air Systems
Schmidt, C.; Kissock, J. K.
2004-01-01T23:59:59.000Z
are frequently overestimated because the methods used to estimate savings neglect to consider important factors such as compressor control and type, storage, and multiple compressor operation. In this paper, a methodology is presented for modeling air... compressor performance and calculating projected energy savings from easily obtainable performance data such as full-load power, no-load power, rated capacity, average fraction full-load power or average fraction rated capacity. The methodology...
AN OVERVIEW OF TOOL FOR RESPONSE ACTION COST ESTIMATING (TRACE)
FERRIES SR; KLINK KL; OSTAPKOWICZ B
2012-01-30T23:59:59.000Z
Tools and techniques that provide improved performance and reduced costs are important to government programs, particularly in current times. An opportunity for improvement was identified for preparation of cost estimates used to support the evaluation of response action alternatives. As a result, CH2M HILL Plateau Remediation Company has developed Tool for Response Action Cost Estimating (TRACE). TRACE is a multi-page Microsoft Excel{reg_sign} workbook developed to introduce efficiencies into the timely and consistent production of cost estimates for response action alternatives. This tool combines costs derived from extensive site-specific runs of commercially available remediation cost models with site-specific and estimator-researched and derived costs, providing the best estimating sources available. TRACE also provides for common quantity and key parameter links across multiple alternatives, maximizing ease of updating estimates and performing sensitivity analyses, and ensuring consistency.
Quantum-enhanced metrology for multiple phase estimation with noise
Jie-Dong Yue; Yu-Ran Zhang; Heng Fan
2014-08-10T23:59:59.000Z
We present a general framework to study the simultaneous estimation of multiple phases in the presence of noise as a discretized model for phase imaging. This approach can lead to nontrivial bounds of the precision for multiphase estimation. Our results show that simultaneous estimation (SE) of multiple phases is always better than individual estimation (IE) of each phase even in noisy environment. However with $d$ being the number of phases, the $O(d)$ advantage in the variance of the estimation, with which SE outperforms IE schemes for noiseless processes, may disappear asymptotically. When noise is low, those bounds recover the Heisenberg scale with the $O(d)$ advantage. The utility of the bound of multiple phase estimation for photon loss channels is exemplified.
IDC RP2 & 3 US Industry Standard Cost Estimate Summary.
Harris, James M.; Huelskamp, Robert M.
2015-01-01T23:59:59.000Z
Sandia National Laboratories has prepared a ROM cost estimate for budgetary planning for the IDC Reengineering Phase 2 & 3 effort, using a commercial software cost estimation tool calibrated to US industry performance parameters. This is not a cost estimate for Sandia to perform the project. This report provides the ROM cost estimate and describes the methodology, assumptions, and cost model details used to create the ROM cost estimate. ROM Cost Estimate Disclaimer Contained herein is a Rough Order of Magnitude (ROM) cost estimate that has been provided to enable initial planning for this proposed project. This ROM cost estimate is submitted to facilitate informal discussions in relation to this project and is NOT intended to commit Sandia National Laboratories (Sandia) or its resources. Furthermore, as a Federally Funded Research and Development Center (FFRDC), Sandia must be compliant with the Anti-Deficiency Act and operate on a full-cost recovery basis. Therefore, while Sandia, in conjunction with the Sponsor, will use best judgment to execute work and to address the highest risks and most important issues in order to effectively manage within cost constraints, this ROM estimate and any subsequent approved cost estimates are on a 'full-cost recovery' basis. Thus, work can neither commence nor continue unless adequate funding has been accepted and certified by DOE.
Wang, Huansha
2014-01-01T23:59:59.000Z
Financial Studies 21: 17. Caner, M. (2009) A Lasso type GMMTheory 25: 270-290. 18. Caner, M. and Fan, M. A near minimaxthe parametric case see Caner (2009), Caner and Fan (2011),
Joel Sminchak
2011-09-30T23:59:59.000Z
The Arches Province in the Midwestern U.S. has been identified as a major area for carbon dioxide (CO{sub 2}) storage applications because of the intersection of Mt. Simon sandstone reservoir thickness and permeability. To better understand large-scale CO{sub 2} storage infrastructure requirements in the Arches Province, variable density scoping level modeling was completed. Three main tasks were completed for the variable density modeling: Single-phase, variable density groundwater flow modeling; Scoping level multi-phase simulations; and Preliminary basin-scale multi-phase simulations. The variable density modeling task was successful in evaluating appropriate input data for the Arches Province numerical simulations. Data from the geocellular model developed earlier in the project were translated into preliminary numerical models. These models were calibrated to observed conditions in the Mt. Simon, suggesting a suitable geologic depiction of the system. The initial models were used to assess boundary conditions, calibrate to reservoir conditions, examine grid dimensions, evaluate upscaling items, and develop regional storage field scenarios. The task also provided practical information on items related to CO{sub 2} storage applications in the Arches Province such as pressure buildup estimates, well spacing limitations, and injection field arrangements. The Arches Simulation project is a three-year effort and part of the United States Department of Energy (U.S. DOE)/National Energy Technology Laboratory (NETL) program on innovative and advanced technologies and protocols for monitoring/verification/accounting (MVA), simulation, and risk assessment of CO{sub 2} sequestration in geologic formations. The overall objective of the project is to develop a simulation framework for regional geologic CO{sub 2} storage infrastructure along the Arches Province of the Midwestern U.S.
Examples of Cost Estimation Packages
Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]
1997-03-28T23:59:59.000Z
Estimates can be performed in a variety of ways. Some of these are for projects for an undefined scope, a conventional construction project, or where there is a level of effort required to complete the work. Examples of cost estimation packages for these types of projects are described in this appendix.
Atmospheric dispersion estimates in the vicinity of buildings
Ramsdell, J.V. Jr.; Fosmire, C.J.
1995-01-01T23:59:59.000Z
A model describing atmospheric dispersion in the vicinity of buildings was developed for the U.S. Nuclear Regulatory Commission (NRC) in the late 1980s. That model has recently undergone additional peer review. The reviewers identified four areas of concern related to the model and its application. This report describes revisions to the model in response to the reviewers concerns. Model revision involved incorporation of explicit treatment of enhanced dispersion at low wind speeds in addition to explicit treatment of enhanced dispersion at high speeds resulting from building wakes. Model parameters are evaluated from turbulence data. Experimental diffusion data from seven reactor sites are used for model evaluation. Compared with models recommended in current NRC guidance to licensees, the revised model is less biased and shows more predictive skill. The revised model is also compared with two non-Gaussian models developed to estimate maximum concentrations in building wakes. The revised model concentration predictions are nearly the same as the predictions of the non-Gaussian models. On the basis of these comparisons of the revised model concentration predictions with experimental data and the predictions of other models, the revised model is found to be an appropriate model for estimating concentrations in the vicinity of buildings.
2013-01-01T23:59:59.000Z
model in southern states of Kerala and Tamil Nadu for non-JHARKHAND (19) KARNATAKA (26) KERALA (28) MADHYA PRADESH (
Aerosol Best Estimate Value-Added Product
Flynn, C; Turner, D; Koontz, A; Chand, D; Sivaraman, C
2012-07-19T23:59:59.000Z
The objective of the Aerosol Best Estimate (AEROSOLBE) value-added product (VAP) is to provide vertical profiles of aerosol extinction, single scatter albedo, asymmetry parameter, and Angstroem exponents for the atmospheric column above the Central Facility at the ARM Southern Great Plains (SGP) site. We expect that AEROSOLBE will provide nearly continuous estimates of aerosol optical properties under a range of conditions (clear, broken clouds, overcast clouds, etc.). The primary requirement of this VAP was to provide an aerosol data set as continuous as possible in both time and height for the Broadband Heating Rate Profile (BBHRP) VAP in order to provide a structure for the comprehensive assessment of our ability to model atmospheric radiative transfer for all conditions. Even though BBHRP has been completed, AEROSOLBE results are very valuable for environmental, atmospheric, and climate research.
Estimating the Energy Use and Efficiency Potential of U.S. Data Centers
Masanet, EricR.
2014-01-01T23:59:59.000Z
Keywords: data centers; energy demand modeling; energyof U.S. data center energy demand under different efficiencyfor estimation of energy demand in different data center
ESTIMATION AND CONTROL OF INDUSTRIAL PROCESSES WITH PARTICLE FILTERS
de Freitas, Nando
ESTIMATION AND CONTROL OF INDUSTRIAL PROCESSES WITH PARTICLE FILTERS Rub´en Morales of industrial processes. In particular, we adopt a jump Markov linear Gaussian (JMLG) model to describe an industrial heat exchanger. The parameters of this model are identi- fied with the expectation maximisation
Estimation of Groundwater Flow Parameters Using Least Squares
Estimation of Groundwater Flow Parameters Using Least Squares K.R. Bailey \\Lambda , B state flow parameters in a groundwater model. We test the approach on numerically generated data algorithm is implemented in parallel using PVM. 1 Introduction The successful modeling of groundwater flow
COUPLING AND COHERENCE ESTIMATES FROM SINGLE-FIRED CYLINDRICAL EXPLOSIONS
Stump, Brian W.
COUPLING AND COHERENCE ESTIMATES FROM SINGLE-FIRED CYLINDRICAL EXPLOSIONS Implications for Using 4 5 6 7 8 test bench pit charge depth burden charge length explosive stemming #12;Single shot) Modeling - Source a) Explosion Source Mueller-Murphy model b) Vertical Spall Opening of horizontal crack
IVCNZ 2002 SUBMISSION 1 Pose Estimation by Applied Numerical Techniques
McCane, Brendan
process of how to deform the model in order to bring it into agreement with the input image. An energy. Keywords--- Numerical Optimisation, Pose Estimation, AnalysisÂbyÂSynthesis, Optimisation Algorithms (HCI). Traditionally, researchers have split approaches into an appearanceÂbased approach and a model
Design of Optimal Experiments for Parameter Estimation of Microalgae
Paris-Sud XI, Université de
Design of Optimal Experiments for Parameter Estimation of Microalgae Growth Models Rafael Mu of microalgae growth useful tools for prediction and process optimization, reliable parameters need the effect of temperature and light on microalgae growth. On the basis of a mathematical model
Joint estimation of phase and phase diffusion for quantum metrology
Mihai D. Vidrighin; Gaia Donati; Marco G. Genoni; Xian-Min Jin; W. Steven Kolthammer; M. S. Kim; Animesh Datta; Marco Barbieri; Ian A. Walmsley
2014-10-20T23:59:59.000Z
Phase estimation, at the heart of many quantum metrology and communication schemes, can be strongly affected by noise, whose amplitude may not be known, or might be subject to drift. Here, we investigate the joint estimation of a phase shift and the amplitude of phase diffusion, at the quantum limit. For several relevant instances, this multiparameter estimation problem can be effectively reshaped as a two-dimensional Hilbert space model, encompassing the description of an interferometer phase probed with relevant quantum states -- split single-photons, coherent states or N00N states. For these cases, we obtain a trade-off bound on the statistical variances for the joint estimation of phase and phase diffusion, as well as optimum measurement schemes. We use this bound to quantify the effectiveness of an actual experimental setup for joint parameter estimation for polarimetry. We conclude by discussing the form of the trade-off relations for more general states and measurements.
How to Estimate the Value of Service Reliability Improvements
Sullivan, Michael J.; Mercurio, Matthew G.; Schellenberg, Josh A.; Eto, Joseph H.
2010-06-08T23:59:59.000Z
A robust methodology for estimating the value of service reliability improvements is presented. Although econometric models for estimating value of service (interruption costs) have been established and widely accepted, analysts often resort to applying relatively crude interruption cost estimation techniques in assessing the economic impacts of transmission and distribution investments. This paper first shows how the use of these techniques can substantially impact the estimated value of service improvements. A simple yet robust methodology that does not rely heavily on simplifying assumptions is presented. When a smart grid investment is proposed, reliability improvement is one of the most frequently cited benefits. Using the best methodology for estimating the value of this benefit is imperative. By providing directions on how to implement this methodology, this paper sends a practical, usable message to the industry.
Pose Estimation via Gauss-Newton-on-manifold Pei Yean Lee and John B. Moore
Moore, John Barratt
on the smooth manifold of rotation matrices, namely the special orthogonal matrices SO3, depicted as the surface of a cone in Fig. 1. Also, in Fig. 1, the feasible domain is depicted as the intersection SO3 K. The cost
Assessing the Reliability of a Human Estimator Gary D. Boetticher, Nazim Lokhandwala
Boetticher, Gary D.
than humans make [2]. Algorithmic-based estimation approaches are based on human subjectivity. The post-architecture from estimating models to current projects and organization environments in order to achieveAssessing the Reliability of a Human Estimator Gary D. Boetticher, Nazim Lokhandwala University
Nondestructive estimates of above-ground biomass using terrestrial laser scanning
Jones, Peter JS
, The Netherlands; 2 CSIRO Land and Water, Private Bag 10, Clayton South, Vic. 3169, Australia; 3 Department these estimates against destructively harvested AGB estimates and AGB derived from allometric equations. We also. Single trees are extracted from the TLS data and quantitative structure models are used to estimate
Switching Mode Generation and Optimal Estimation with Application to Skid-Steering
Hartmann, Mitra J. Z.
to treat the skid-steered vehicle as a switched system, the vehicle's ground interaction is modeled using; optimal estimation; optimal control; estimation algorithms 1 Introduction The skid-steered vehicle (SSVSwitching Mode Generation and Optimal Estimation with Application to Skid-Steering T. M. Caldwell
Developing an alternative model for travel decision-making
Hung, Kam
2009-05-15T23:59:59.000Z
)....................................................................................................................147 35 Estimation of fit indices of self-congruity measurement models ..............................148 36 Estimation of fit indices of travel intention model ....................................................149 37 Estimation of fit indices... Intentions...................................................................................................35 5 Self-congruity and Functional Congruity ....................................................................36 6 Destination...
Measurement enhancement for state estimation
Chen, Jian
2009-05-15T23:59:59.000Z
in the power system. A robust state estimation should have the capability of keeping the system observable during different contingencies, as well as detecting and identifying the gross errors in measurement set and network topology. However, this capability...
Estimation of resources and reserves
Massachusetts Institute of Technology. Energy Laboratory.
1982-01-01T23:59:59.000Z
This report analyzes the economics of resource and reserve estimation. Current concern about energy problems has focused attention on how we measure available energy resources. One reads that we have an eight-year oil ...
Motion Estimation from Disparity Images
Demirdjian, D.
2001-05-07T23:59:59.000Z
A new method for 3D rigid motion estimation from stereo is proposed in this paper. The appealing feature of this method is that it directly uses the disparity images obtained from stereo matching. We assume that the stereo ...
Using percolation techniques to estimate interwell connectivity probability
Li, Weiqiang
2009-06-02T23:59:59.000Z
results for fluid travel time between locations in a percolation model, we developed a method to estimate interwell connectivity. Three parameters are needed to use this approach: the sandbody occupied probability sand p , the dimensionless reservoir... and can estimate the interwell connectivity accurately for thin intervals with sand p in the 60% to 80% range. The proposed method requires that the reservoir interval for evaluation be sufficiently thin so that 2D percolation results can...
Cosmological parameter estimation: impact of CMB aberration
Catena, Riccardo [Institut für Theoretische Physik, Friedrich-Hund-Platz 1, 37077 Göttingen (Germany); Notari, Alessio, E-mail: riccardo.catena@theorie.physik.uni-goettingen.de, E-mail: notari@ffn.ub.es [Departament de Física Fondamental i Institut de Ciéncies del Cosmos, Universitat de Barcelona, Martí i Franqués 1, 08028 Barcelona (Spain)
2013-04-01T23:59:59.000Z
The peculiar motion of an observer with respect to the CMB rest frame induces an apparent deflection of the observed CMB photons, i.e. aberration, and a shift in their frequency, i.e. Doppler effect. Both effects distort the temperature multipoles a{sub lm}'s via a mixing matrix at any l. The common lore when performing a CMB based cosmological parameter estimation is to consider that Doppler affects only the l = 1 multipole, and neglect any other corrections. In this paper we reconsider the validity of this assumption, showing that it is actually not robust when sky cuts are included to model CMB foreground contaminations. Assuming a simple fiducial cosmological model with five parameters, we simulated CMB temperature maps of the sky in a WMAP-like and in a Planck-like experiment and added aberration and Doppler effects to the maps. We then analyzed with a MCMC in a Bayesian framework the maps with and without aberration and Doppler effects in order to assess the ability of reconstructing the parameters of the fiducial model. We find that, depending on the specific realization of the simulated data, the parameters can be biased up to one standard deviation for WMAP and almost two standard deviations for Planck. Therefore we conclude that in general it is not a solid assumption to neglect aberration in a CMB based cosmological parameter estimation.
Risk Estimation Methodology for Launch Accidents.
Clayton, Daniel James; Lipinski, Ronald J.; Bechtel, Ryan D.
2014-02-01T23:59:59.000Z
As compact and light weight power sources with reliable, long lives, Radioisotope Power Systems (RPSs) have made space missions to explore the solar system possible. Due to the hazardous material that can be released during a launch accident, the potential health risk of an accident must be quantified, so that appropriate launch approval decisions can be made. One part of the risk estimation involves modeling the response of the RPS to potential accident environments. Due to the complexity of modeling the full RPS response deterministically on dynamic variables, the evaluation is performed in a stochastic manner with a Monte Carlo simulation. The potential consequences can be determined by modeling the transport of the hazardous material in the environment and in human biological pathways. The consequence analysis results are summed and weighted by appropriate likelihood values to give a collection of probabilistic results for the estimation of the potential health risk. This information is used to guide RPS designs, spacecraft designs, mission architecture, or launch procedures to potentially reduce the risk, as well as to inform decision makers of the potential health risks resulting from the use of RPSs for space missions.
Method and system to estimate variables in an integrated gasification combined cycle (IGCC) plant
Kumar, Aditya; Shi, Ruijie; Dokucu, Mustafa
2013-09-17T23:59:59.000Z
System and method to estimate variables in an integrated gasification combined cycle (IGCC) plant are provided. The system includes a sensor suite to measure respective plant input and output variables. An extended Kalman filter (EKF) receives sensed plant input variables and includes a dynamic model to generate a plurality of plant state estimates and a covariance matrix for the state estimates. A preemptive-constraining processor is configured to preemptively constrain the state estimates and covariance matrix to be free of constraint violations. A measurement-correction processor may be configured to correct constrained state estimates and a constrained covariance matrix based on processing of sensed plant output variables. The measurement-correction processor is coupled to update the dynamic model with corrected state estimates and a corrected covariance matrix. The updated dynamic model may be configured to estimate values for at least one plant variable not originally sensed by the sensor suite.
Photogrammetry and Laser Imagery Tests for Tank Waste Volume Estimates: Summary Report
Field, Jim G. [Washington River Protection Solutions, LLC, Richland, WA (United States)
2013-03-27T23:59:59.000Z
Feasibility tests were conducted using photogrammetry and laser technologies to estimate the volume of waste in a tank. These technologies were compared with video Camera/CAD Modeling System (CCMS) estimates; the current method used for post-retrieval waste volume estimates. This report summarizes test results and presents recommendations for further development and deployment of technologies to provide more accurate and faster waste volume estimates in support of tank retrieval and closure.
Data Needs for Evolving Motor Vehicle Emission Modeling Approaches
Guensler, Randall
1993-01-01T23:59:59.000Z
Agency; Highway Vehicle Emission Estimates; Office offor Evolving Motor Vehicle Emission Modeling Approachesfor Evolving Motor Vehicle Emission Modeling Approaches
Estimation of soil moisture in paddy field using Artificial Neural Networks
Arif, Chusnul; Setiawan, Budi Indra; Doi, Ryoichi
2013-01-01T23:59:59.000Z
In paddy field, monitoring soil moisture is required for irrigation scheduling and water resource allocation, management and planning. The current study proposes an Artificial Neural Networks (ANN) model to estimate soil moisture in paddy field with limited meteorological data. Dynamic of ANN model was adopted to estimate soil moisture with the inputs of reference evapotranspiration (ETo) and precipitation. ETo was firstly estimated using the maximum, average and minimum values of air temperature as the inputs of model. The models were performed under different weather conditions between the two paddy cultivation periods. Training process of model was carried out using the observation data in the first period, while validation process was conducted based on the observation data in the second period. Dynamic of ANN model estimated soil moisture with R2 values of 0.80 and 0.73 for training and validation processes, respectively, indicated that tight linear correlations between observed and estimated values of s...
Quick Estimate of IRR From Capital Estimate Ratios
Larson, R. J.
specific problem. However, the derivation is simple enough so that a new chart can be derived, using the principles described, which is applicable to a specific situation or class of situations. Using conventional Discounted Cash Flow techniques... of the use of this chart is as follows: The estimate capital to carry out a proj ct is $24,000. The estimated savings to be experienced n the first year of operation is $11,300. 21 ESL-IE-85-05-05 Proceedings from the Seventh National Industrial Energy...
Weldon Spring historical dose estimate
Meshkov, N.; Benioff, P.; Wang, J.; Yuan, Y.
1986-07-01T23:59:59.000Z
This study was conducted to determine the estimated radiation doses that individuals in five nearby population groups and the general population in the surrounding area may have received as a consequence of activities at a uranium processing plant in Weldon Spring, Missouri. The study is retrospective and encompasses plant operations (1957-1966), cleanup (1967-1969), and maintenance (1969-1982). The dose estimates for members of the nearby population groups are as follows. Of the three periods considered, the largest doses to the general population in the surrounding area would have occurred during the plant operations period (1957-1966). Dose estimates for the cleanup (1967-1969) and maintenance (1969-1982) periods are negligible in comparison. Based on the monitoring data, if there was a person residing continually in a dwelling 1.2 km (0.75 mi) north of the plant, this person is estimated to have received an average of about 96 mrem/yr (ranging from 50 to 160 mrem/yr) above background during plant operations, whereas the dose to a nearby resident during later years is estimated to have been about 0.4 mrem/yr during cleanup and about 0.2 mrem/yr during the maintenance period. These values may be compared with the background dose in Missouri of 120 mrem/yr.
Lee, Ann B..
in the Modelling of Hurricane Tracks6 Susan M. Buchman, Ann B. Lee1 , Chad M. Schafer Department of Statistics variability of tropical cyclones in the North Atlantic; each datum in this case is an entire hurricane
New findings about the complementary relationship-based evaporation estimation methods
Szilagyi, Jozsef
KEYWORDS Complementary relationship; AdvectionAridity model; Areal evaporation; Potential evaporation; Apparent potential evaporation; Wet environment evaporation; Evapotranspiration Summary A novel approach of long- term mean evaporation (E) estimation of the AdvectionAridity (AA) model when vali- dated
Air Pollution and Mortality: Estimating Regional and National DoseResponse Relationships
Dominici, Francesca
Air Pollution and Mortality: Estimating Regional and National DoseResponse Relationships Francesca was linear. KEY WORDS: Air pollution; Data augmentation; Generalized additive model; Hierarchical model, possibly nonrepresentative, locations. The National Morbidity, Mortality, and Air Pollution Study (NMMAPS
Fedrigo, Melissa
2009-11-26T23:59:59.000Z
Field measured estimates of aboveground biomass (AGB) for 15 transects in Bwindi Impenetrable National Park (BINP), Uganda were used to generate a number of prediction models for estimating aboveground biomass (AGB) over the full extent of BINP. AGB...
Adaptive Generalized Estimation Equation with Bayes Classifier for the Job Assignment Problem
Lin, King-Ip "David"
or linear programming do not work well for data with high level of noise. Moreover, our model aims at beingAdaptive Generalized Estimation Equation with Bayes Classifier for the Job Assignment Problem Yulan classifiers to enhance decisionmaking models for the job assignment problem. Adaptive Generalized Estimation
Dose estimates in a loss of lead shielding truck accident.
Dennis, Matthew L.; Osborn, Douglas M.; Weiner, Ruth F.; Heames, Terence John (Alion Science & Technology Albuquerque, NM)
2009-08-01T23:59:59.000Z
The radiological transportation risk & consequence program, RADTRAN, has recently added an updated loss of lead shielding (LOS) model to it most recent version, RADTRAN 6.0. The LOS model was used to determine dose estimates to first-responders during a spent nuclear fuel transportation accident. Results varied according to the following: type of accident scenario, percent of lead slump, distance to shipment, and time spent in the area. This document presents a method of creating dose estimates for first-responders using RADTRAN with potential accident scenarios. This may be of particular interest in the event of high speed accidents or fires involving cask punctures.
Adjusted Estimates of Texas Natural Gas Production
U.S. Energy Information Administration (EIA) Indexed Site
1 Energy Information Administration Adjusted Estimates of Texas Natural Gas Production Background The Energy Information Administration (EIA) is adjusting its estimates of natural...
Hydrogen Production Cost Estimate Using Biomass Gasification...
Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site
Cost Estimate Using Biomass Gasification: Independent Review Hydrogen Production Cost Estimate Using Biomass Gasification: Independent Review This independent review is the...
An Improved Virial Estimate of Solar Active Region Energy
M. S. Wheatland; T. R. Metcalf
2005-09-21T23:59:59.000Z
The MHD virial theorem may be used to estimate the magnetic energy of active regions based on vector magnetic fields measured at the photosphere or chromosphere. However, the virial estimate depends on the measured vector magnetic field being force-free. Departure from force-freeness leads to an unknown systematic error in the virial energy estimate, and an origin dependence of the result. We present a method for estimating the systematic error by assuming that magnetic forces are confined to a thin layer near the photosphere. If vector magnetic field measurements are available at two levels in the low atmosphere (e.g. the photosphere and the chromosphere), the systematic error may be directly calculated using the observed horizontal and vertical field gradients, resulting in an energy estimate which is independent of the choice of origin. If (as is generally the case) measurements are available at only one level, the systematic error may be approximated using the observed horizontal field gradients together with a simple linear force-free model for the vertical field gradients. The resulting `improved' virial energy estimate is independent of the choice of origin, but depends on the choice of the model for the vertical field gradients, i.e. the value of the linear force-free parameter $\\alpha$. This procedure is demonstrated for five vector magnetograms, including a chromospheric magnetogram.
Feasibility Studies of Applying Kalman Filter Techniques to Power System Dynamic State Estimation
Huang, Zhenyu; Schneider, Kevin P.; Nieplocha, Jarek
2007-08-01T23:59:59.000Z
Abstract—Lack of dynamic information in power system operations mainly attributes to the static modeling of traditional state estimation, as state estimation is the basis driving many other operations functions. This paper investigates the feasibility of applying Kalman filter techniques to enable the inclusion of dynamic modeling in the state estimation process and the estimation of power system dynamic states. The proposed Kalman-filter-based dynamic state estimation is tested on a multi-machine system with both large and small disturbances. Sensitivity studies of the dynamic state estimation performance with respect to measurement characteristics – sampling rate and noise level – are presented as well. The study results show that there is a promising path forward to implementation the Kalman-filter-based dynamic state estimation with the emerging phasor measurement technologies.
Preliminary relative permeability estimates of methanehydrate-bearing sand
Seol, Yongkoo; Kneafsey, Timothy J.; Tomutsa, Liviu; Moridis,George J.
2006-05-08T23:59:59.000Z
The relative permeability to fluids in hydrate-bearing sediments is an important parameter for predicting natural gas production from gas hydrate reservoirs. We estimated the relative permeability parameters (van Genuchten alpha and m) in a hydrate-bearing sand by means of inverse modeling, which involved matching water saturation predictions with observations from a controlled waterflood experiment. We used x-ray computed tomography (CT) scanning to determine both the porosity and the hydrate and aqueous phase saturation distributions in the samples. X-ray CT images showed that hydrate and aqueous phase saturations are non-uniform, and that water flow focuses in regions of lower hydrate saturation. The relative permeability parameters were estimated at two locations in each sample. Differences between the estimated parameter sets at the two locations were attributed to heterogeneity in the hydrate saturation. Better estimates of the relative permeability parameters require further refinement of the experimental design, and better description of heterogeneity in the numerical inversions.
Preliminary relative permeability estimates of methanehydrate-bearing sand
Seol, Yongkoo; Kneafsey, Timothy J.; Tomutsa, Liviu; Moridis,George J.
2006-05-08T23:59:59.000Z
The relative permeability to fluids in hydrate-bearingsediments is an important parameter for predicting natural gas productionfrom gas hydrate reservoirs. We estimated the relative permeabilityparameters (van Genuchten alpha and m) in a hydrate-bearing sand by meansof inverse modeling, which involved matching water saturation predictionswith observations from a controlled waterflood experiment. We used x-raycomputed tomography (CT) scanning to determine both the porosity and thehydrate and aqueous phase saturation distributions in the samples. X-rayCT images showed that hydrate and aqueous phase saturations arenon-uniform, and that water flow focuses in regions of lower hydratesaturation. The relative permeability parameters were estimated at twolocations in each sample. Differences between the estimated parametersets at the two locations were attributed to heterogeneity in the hydratesaturation. Better estimates of the relative permeability parametersrequire further refinement of the experimental design, and betterdescription of heterogeneity in the numerical inversions.
Joseph, Earl C.; Conway, Steve; Dekate, Chirag
2013-09-30T23:59:59.000Z
This study investigated how high-performance computing (HPC) investments can improve economic success and increase scientific innovation. This research focused on the common good and provided uses for DOE, other government agencies, industry, and academia. The study created two unique economic models and an innovation index: 1 A macroeconomic model that depicts the way HPC investments result in economic advancements in the form of ROI in revenue (GDP), profits (and cost savings), and jobs. 2 A macroeconomic model that depicts the way HPC investments result in basic and applied innovations, looking at variations by sector, industry, country, and organization size. ? A new innovation index that provides a means of measuring and comparing innovation levels. Key findings of the pilot study include: IDC collected the required data across a broad set of organizations, with enough detail to create these models and the innovation index. The research also developed an expansive list of HPC success stories.
Efficient Power System State Estimation
Lavaei, Javad
monitoring of power systems. 2. Background Power systems have four main components: transmission, sub-transmissionEfficient Power System State Estimation Zafirah Baksh Expected BS, Department of Electrical Engineering May 2013 ELEN E4511 Power Systems Analysis Professor Javad Lavaeiyanesi #12;1. Introduction Power