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Note: This page contains sample records for the topic "model output location" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


1

Modeling Multi Output Filtering Effects in PCMOS  

E-Print Network [OSTI]

Modeling Multi Output Filtering Effects in PCMOS Anshul Singh*, Arindam Basu, Keck-Voon Ling, Nanyang Technological University (NTU), Singapore *NTU-Rice Institute of Sustainable and Applied Infodynamics (ISAID), NTU, Singapore $School of Computer Engineering, NTU, Singapore §School of ECE, Georgia

Mooney, Vincent

2

Community Climate System Model (CCSM) Experiments and Output Data  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

The CCSM web makes the source code of various versions of the model freely available and provides access to experiments that have been run and the resulting output data.

3

MODELING MULTI-OUTPUT FILTERING EFFECTS IN PCMOS Anshul Singh*  

E-Print Network [OSTI]

MODELING MULTI-OUTPUT FILTERING EFFECTS IN PCMOS Anshul Singh* , Arindam Basu , Keck-Voon Ling* and Vincent J. Mooney III*$§ Email: anshul.singh@research.iiit.ac.in, {arindam.basu, ekvling}@ntu, Nanyang Technological University (NTU), Singapore * NTU-Rice Institute of Sustainable and Applied

Mooney, Vincent

4

Simple SPICE model for comparison of CMOS output driver circuits  

E-Print Network [OSTI]

to monitor the ground nodes of output driver circuits for noise. Both relative performance and noise levels are generated through the simulations. A test device was built to confirm that the model was effective in speed and noise comparisons. Values were... on CMOS technologies. Journal model is IEEE 'I?ansactions on Automatic Control. A. Literature Survey Research has been done in the past concerning noise generated by digital logic de- vices. In particular, Advanced CMOS Logic (ACL) integrated circuits...

Hermann, John Karl

1993-01-01T23:59:59.000Z

5

Addressing endogeneity in residential location models  

E-Print Network [OSTI]

Some empirical residential location choice models have reported dwelling-unit price estimated parameters that are small, not statistically significant, or even positive. This would imply that households are non-sensitive ...

Guevara-Cue, Cristin Angelo

2005-01-01T23:59:59.000Z

6

Investigating Output Accuracy for a Discrete Event Simulation Model and an Agent Based Simulation Model  

E-Print Network [OSTI]

In this paper, we investigate output accuracy for a Discrete Event Simulation (DES) model and Agent Based Simulation (ABS) model. The purpose of this investigation is to find out which of these simulation techniques is the best one for modelling human reactive behaviour in the retail sector. In order to study the output accuracy in both models, we have carried out a validation experiment in which we compared the results from our simulation models to the performance of a real system. Our experiment was carried out using a large UK department store as a case study. We had to determine an efficient implementation of management policy in the store's fitting room using DES and ABS. Overall, we have found that both simulation models were a good representation of the real system when modelling human reactive behaviour.

Majid, Mazlina Abdul; Siebers, Peer-Olaf

2010-01-01T23:59:59.000Z

7

Use of Advanced Meteorological Model Output for Coastal Ocean Modeling in Puget Sound  

SciTech Connect (OSTI)

It is a great challenge to specify meteorological forcing in estuarine and coastal circulation modeling using observed data because of the lack of complete datasets. As a result of this limitation, water temperature is often not simulated in estuarine and coastal modeling, with the assumption that density-induced currents are generally dominated by salinity gradients. However, in many situations, temperature gradients could be sufficiently large to influence the baroclinic motion. In this paper, we present an approach to simulate water temperature using outputs from advanced meteorological models. This modeling approach was applied to simulate annual variations of water temperatures of Puget Sound, a fjordal estuary in the Pacific Northwest of USA. Meteorological parameters from North American Region Re-analysis (NARR) model outputs were evaluated with comparisons to observed data at real-time meteorological stations. Model results demonstrated that NARR outputs can be used to drive coastal ocean models for realistic simulations of long-term water-temperature distributions in Puget Sound. Model results indicated that the net flux from NARR can be further improved with the additional information from real-time observations.

Yang, Zhaoqing; Khangaonkar, Tarang; Wang, Taiping

2011-06-01T23:59:59.000Z

8

Probabilistic Forecasts of Wind Speed: Ensemble Model Output Statistics  

E-Print Network [OSTI]

. Over the past two decades, ensembles of numerical weather prediction (NWP) models have been developed and phrases: Continuous ranked probability score; Density forecast; Ensem- ble system; Numerical weather prediction; Heteroskedastic censored regression; Tobit model; Wind energy. 1 #12;1 Introduction Accurate

Washington at Seattle, University of

9

Neural Networks for Post-processing Model Output: Caren Marzban  

E-Print Network [OSTI]

variables to the neural network are: Forecast hour, model forecast temperature, relative humidity, wind direction and speed, mean sea level pressure, cloud cover, and precipitation rate and amount. The single to being able to approximate a large class of functions, they are less inclined to overfit data than some

Marzban, Caren

10

Modeling the Energy Output from an In-Stream Tidal Turbine Farm  

E-Print Network [OSTI]

AbstractThis paper is based on a recent paper presented in the 2007 IEEE SMC conference by the same authors [1], discussing an approach to predicting energy output from an instream tidal turbine farm. An in-stream tidal turbine is a device for harnessing energy from tidal currents in channels, and functions in a manner similar to a wind turbine. A group of such turbines distributed in a site is called an in-stream tidal turbine farm which is similar to a wind farm. Approaches to estimating energy output from wind farms cannot be fully transferred to study tidal farms, however, because of the complexities involved in modeling turbines underwater. In this paper, we intend to develop an approach for predicting energy output of an in-stream tidal turbine farm. The mathematical formulation and basic procedure for predicting power output of a stand-alone turbine 1 is presented, which includes several highly nonlinear terms. In order to facilitate the computation and utilize the formulation for predicting power output from a turbine farm, a simplified relationship between turbine distribution and turbine farm energy output is derived. A case study is then conducted by applying the numerical procedure to predict the energy output of the farms. Various scenarios are implemented according to the environmental conditions in Seymour Narrows, British Columbia, Canada. Additionally, energy cost results are presented as an extension. Index Termsrenewable energy, in-stream turbine, tidal current, tidal power, vertical axis turbine, farm system modeling, in-stream tidal turbine farm 1 A stand-alone turbine refers to a turbine around which there is no other turbine that might potentially affect the performance of this turbine.

Ye Li; Barbara J. Lence; Sander M. Calisal

11

Bayesian Emulation of Complex Multi-Output and Dynamic Computer Models  

E-Print Network [OSTI]

Bayesian Emulation of Complex Multi-Output and Dynamic Computer Models Stefano Conti Anthony O the case). In particular, standard Monte Carlo-based methods of sensitivity analysis (extensively reviewed'Hagan, 2002), offering substantial efficiency gains over standard Monte Carlo-based meth- ods. These authors

Oakley, Jeremy

12

Probabilistic Forecasting of (Severe) Thunderstorms in the Netherlands Using Model Output Statistics  

E-Print Network [OSTI]

Probabilistic Forecasting of (Severe) Thunderstorms in the Netherlands Using Model Output Statistics MAURICE J. SCHMEITS, KEES J. KOK, AND DAAN H. P. VOGELEZANG Royal Netherlands Meteorological Institute (KNMI), De Bilt, Netherlands (Manuscript received 29 April 2004, in final form 7 September 2004

Schmeits, Maurice

13

Using Weather Data and Climate Model Output in Economic Analyses of Climate Change  

SciTech Connect (OSTI)

Economists are increasingly using weather data and climate model output in analyses of the economic impacts of climate change. This article introduces a set of weather data sets and climate models that are frequently used, discusses the most common mistakes economists make in using these products, and identifies ways to avoid these pitfalls. We first provide an introduction to weather data, including a summary of the types of datasets available, and then discuss five common pitfalls that empirical researchers should be aware of when using historical weather data as explanatory variables in econometric applications. We then provide a brief overview of climate models and discuss two common and significant errors often made by economists when climate model output is used to simulate the future impacts of climate change on an economic outcome of interest.

Auffhammer, Maximilian [University of California at Berkeley; Hsiang, Solomon M. [Princeton University; Schlenker, Wolfram [Columbia University; Sobel, Adam H. [Columbia University

2013-06-28T23:59:59.000Z

14

Residential mobility and location choice: a nested logit model with sampling of alternatives  

E-Print Network [OSTI]

Waddell, P. : Modeling residential location in UrbanSim. In:D. (eds. ) Modelling Residential Location Choice. Springer,based model system and a residential location model. Urban

Lee, Brian H.; Waddell, Paul

2010-01-01T23:59:59.000Z

15

Scaled Tests and Modeling of Effluent Stack Sampling Location Mixing  

SciTech Connect (OSTI)

The Pacific Northwest National Laboratory researchers used a computational fluid dynamics (CFD) computer code to evaluate the mixing at a sampling system location of a research and development facility. The facility requires continuous sampling for radioactive air emissions. Researchers sought to determine whether the location would meet the criteria for uniform air velocity and contaminant concentration as prescribed in the American National Standard Institute (ANSI) standard, Sampling and Monitoring Releases of Airborne Radioactive Substances from the Stacks and Ducts of Nuclear Facilities. Standard ANSI/HPS N13.1-1999 requires that the sampling location be well-mixed and stipulates specific tests (e.g., velocity, gas, and aerosol uniformity and cyclonic flow angle) to verify the extent of mixing.. The exhaust system for the Radiochemical Processing Laboratory was modeled with a CFD code to better understand the flow and contaminant mixing and to predict mixing test results. The CFD results were compared to actual measurements made at a scale-model stack and to the limited data set for the full-scale facility stack. Results indicated that the CFD code provides reasonably conservative predictions for velocity, gas, and aerosol uniformity. Cyclonic flow predicted by the code is less than that measured by the required methods. In expanding from small to full scale, the CFD predictions for full-scale measurements show similar trends as in the scale model and no unusual effects. This work indicates that a CFD code can be a cost-effective aid in design or retrofit of a facilitys stack sampling location that will be required to meet Standard ANSI/HPS N13.1-1999.

Recknagle, Kurtis P.; Yokuda, Satoru T.; Ballinger, Marcel Y.; Barnett, J. M.

2009-02-01T23:59:59.000Z

16

Cardiac output and stroke volume estimation using a hybrid of three models  

E-Print Network [OSTI]

Cardiac output (CO) and stroke volume (SV) are the key hemodynamic parameters to be monitored and assessed in ambulatory and critically ill patients. The purpose of this study was to introduce and validate a new algorithm ...

Arai, Tatsuya

17

Robust UAV Coordination for Target Tracking using Output-Feedback Model Predictive Control with Moving Horizon Estimation  

E-Print Network [OSTI]

Robust UAV Coordination for Target Tracking using Output-Feedback Model Predictive Control consider the control of two UAVs tracking an evasive moving ground vehicle. The UAVs are small fixed to maintain visibility. The control inputs to the UAVs are computed based on noisy measurements of the UAVs

Hespanha, João Pedro

18

Scalable extraction of error models from the output of error detection circuits  

E-Print Network [OSTI]

Accurate methods of assessing the performance of quantum gates are extremely important. Quantum process tomography and randomized benchmarking are the current favored methods. Quantum process tomography gives detailed information, but significant approximations must be made to reduce this information to a form quantum error correction simulations can use. Randomized benchmarking typically outputs just a single number, the fidelity, giving no information on the structure of errors during the gate. Neither method is optimized to assess gate performance within an error detection circuit, where gates will be actually used in a large-scale quantum computer. Specifically, the important issues of error composition and error propagation lie outside the scope of both methods. We present a fast, simple, and scalable method of obtaining exactly the information required to perform effective quantum error correction from the output of continuously running error detection circuits, enabling accurate prediction of large-scale behavior.

Austin G. Fowler; D. Sank; J. Kelly; R. Barends; John M. Martinis

2014-05-06T23:59:59.000Z

19

Modelling Dynamic Constraints in Electricity Markets and the Costs of Uncertain Wind Output  

E-Print Network [OSTI]

. Keywords: Electricity Markets, Energy Modelling, Optimisation Models, JEL-classification: C61, Q41 Author Affiliations: Felix Msgens Graduate School of Risk Manage- ment and Institute of Energy Economics University of Kln Albertus... cycle ( maxt min,1t min,2t min maxt t 1 d d ? visualizes this structure. Figure 1: Energy Prices with Inter-temporal Constraints tmin,1 tmax P ric e tpart,2 tmin2tpart,1 tpart,3 Costs for Fuel + Start up + Part load operation Demand...

Musgens, Felix; Neuhoff, Karsten

2006-03-14T23:59:59.000Z

20

Locating Pleistocene refugia: Comparing phylogeographic and ecological niche model predictions  

E-Print Network [OSTI]

, American Museum of Natural History, New York, New York, United States of America, 2 International Rice Research Institute, Los Banos, Laguna, Philippines, 3Natural History Museum & Biodiversity Research Center, University of Kansas, Lawrence, Kansas.... Refugia identified in phylogeographic studies are shown as black outlines. Areas predicted to be refugia are in green, areas not predicted are in gray, and hatching indicates approximate locations of ice sheets [68]. Gray lines indicate present day...

Waltari, Eric; Hijmans, Robert J.; Peterson, A. Townsend; Nyá ri, Á rpá d S.; Perkins, Susan L.; Guralnick, Robert P.

2007-07-11T23:59:59.000Z

Note: This page contains sample records for the topic "model output location" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


21

A framework for interpreting climate model outputs Nadja A. Leith and Richard E. Chandler  

E-Print Network [OSTI]

to illustrate the methodology. Some key words: Climate change; Climate model uncertainty; Contemporaneous ARMA acknowledged that human activities have caused changes in the Earth's climate (Solomon et al., 2007). Indeed #12;the hydrological cycle (Solomon et al., 2007). To accommodate this possibility therefore, planners

Guillas, Serge

22

Evaluation of Location-Specific Predictions by a Detailed Simulation Model of Aedes aegypti Populations  

E-Print Network [OSTI]

Evaluation of Location-Specific Predictions by a Detailed Simulation Model of Aedes aegypti Buster is a stochastic, spatially explicit simulation model of Aedes aegypti populations, designed of Location-Specific Predictions by a Detailed Simulation Model of Aedes aegypti Populations. PLoS ONE 6(7): e

Lloyd, Alun

23

Artificial neural networks for input-output dynamic modeling of nonlinear processes  

E-Print Network [OSTI]

&at& tire behavior of n&arlinear SIS(2 and 1&IIMO pro&. esses, provi&1& d that tlrv latter operate closv vnou?h t&& dvsired operating points. In the follow'irrg &lrapters, sex&'ra) rrretlrods of non(&near modeling will be used to u&o&1&'I tl&e samv nonliu... the fnlh)&vh)r, e(tu&(t&nn: R M , V = 1 + gP, + P (1, (3) a(&cl o 11 n&1 u . . u 1?v T= (('a(v (V u st I I? tt 2 . . . n';If N is the 3I x(&1 n&atrix of parameters. ln this n&atrix u& & ls the parameter of c(u&n( ction bet&veen tth model input a...

Sarimveis, Haralambos

2012-06-07T23:59:59.000Z

24

Effectiveness-Equity Models for Facility Location Problems on Tree ...  

E-Print Network [OSTI]

pecially in situations that involve public facilities or resources. ... Department of Decision Sciences, School of Business, The George Washington University, Washington, ... First, the proposed models allow one to identify efficient (or Pareto opti-.

2013-01-19T23:59:59.000Z

25

Reliable p-median facility location problem: two-stage robust models ...  

E-Print Network [OSTI]

plane method in the two-stage facility location problem and power system scheduling ... (ii) Because of the modeling advantages of two-stage RO, we consider real ...... Robust Unit Commitment Problem with Demand Response and Wind.

2012-12-18T23:59:59.000Z

26

Environmental Modelling & Software 15 (2000) 161167 www.elsevier.com/locate/envsoft  

E-Print Network [OSTI]

Environmental Modelling & Software 15 (2000) 161­167 www.elsevier.com/locate/envsoft A fuzzy model "contaminated", defined over the set of 70 sampling sites. The higher the concentration, the higher the degree contaminated sites. The proposed fuzzy model is easy to implement and the results are directly interpretable

Kuncheva, Ludmila I.

27

A Comparison of Simulated Cloud Radar Output from the Multiscale Modeling Framework Global Climate Model with CloudSat Cloud Radar Observations  

SciTech Connect (OSTI)

Over the last few years a new type of global climate model (GCM) has emerged in which a cloud-resolving model is embedded into each grid cell of a GCM. This new approach is frequently called a multiscale modeling framework (MMF) or superparameterization. In this article we present a comparison of MMF output with radar observations from the NASA CloudSat mission, which uses a near-nadir-pointing millimeter-wavelength radar to probe the vertical structure of clouds and precipitation. We account for radar detection limits by simulating the 94 GHz radar reflectivity that CloudSat would observe from the high-resolution cloud-resolving model output produced by the MMF. Overall, the MMF does a good job of reproducing the broad pattern of tropical convergence zones, subtropical belts, and midlatitude storm tracks, as well as their changes in position with the annual solar cycle. Nonetheless, the comparison also reveals a number of model shortfalls including (1) excessive hydrometeor coverage at all altitudes over many convectively active regions, (2) a lack of low-level hydrometeors over all subtropical oceanic basins, (3) excessive low-level hydrometeor coverage (principally precipitating hydrometeors) in the midlatitude storm tracks of both hemispheres during the summer season (in each hemisphere), and (4) a thin band of low-level hydrometeors in the Southern Hemisphere of the central (and at times eastern and western) Pacific in the MMF, which is not observed by CloudSat. This band resembles a second much weaker ITCZ but is restricted to low levels.

Marchand, Roger T.; Haynes, J. M.; Mace, Gerald G.; Ackerman, Thomas P.; Stephens, Graeme L.

2009-01-13T23:59:59.000Z

28

A 2D Random Walk Mobility Model for Location Management Studies in Wireless Networks  

E-Print Network [OSTI]

crossing rate' and `dwell time' studies using the same model with slight modifications for the square cell, namely the square cell and the hexagonal cell have been detailed. The analytical results obtained for location update rates and dwell times have been validated using simulated and published results

Shenoy, Nirmala

29

Training Quench Performance and Quench Location of the Short Superconducting Dipole Models for the LHC  

E-Print Network [OSTI]

The short model program, started in October 1995 to study and validate design variants and assembly of the main LHC dipoles, has achieved its last phase. The last models were focused on the validation of specific design choices to be implemented in the series production, and to the study of the training performance of the coil heads. This paper reports on the manufacturing features of the recent twin-aperture short models, reviews the results of the cold tests and presents a summary of the training quench performance and quench location.

Sanfilippo, S; Tommasini, D; Venturini-Delsolaro, W

2002-01-01T23:59:59.000Z

30

Design science research toward designing/prototyping a repeatable model for testing location management (LM) algorithms for wireless networking.  

E-Print Network [OSTI]

?? The purpose of this research effort was to develop a model that provides repeatable Location Management (LM) testing using a network simulation tool, QualNet (more)

Peacock, Christopher

2012-01-01T23:59:59.000Z

31

Comparisons of four categories of waste recycling in China's paper industry based on physical input-output life-cycle assessment model  

SciTech Connect (OSTI)

Highlights: Black-Right-Pointing-Pointer Using crop straws and wood wastes for paper production should be promoted. Black-Right-Pointing-Pointer Bagasse and textile waste recycling should be properly limited. Black-Right-Pointing-Pointer Imports of scrap paper should be encouraged. Black-Right-Pointing-Pointer Sensitivity analysis, uncertainties and policy implications are discussed. - Abstract: Waste recycling for paper production is an important component of waste management. This study constructs a physical input-output life-cycle assessment (PIO-LCA) model. The PIO-LCA model is used to investigate environmental impacts of four categories of waste recycling in China's paper industry: crop straws, bagasse, textile wastes and scrap paper. Crop straw recycling and wood utilization for paper production have small total intensity of environmental impacts. Moreover, environmental impacts reduction of crop straw recycling and wood utilization benefits the most from technology development. Thus, using crop straws and wood (including wood wastes) for paper production should be promoted. Technology development has small effects on environmental impacts reduction of bagasse recycling, textile waste recycling and scrap paper recycling. In addition, bagasse recycling and textile waste recycling have big total intensity of environmental impacts. Thus, the development of bagasse recycling and textile waste recycling should be properly limited. Other pathways for reusing bagasse and textile wastes should be explored and evaluated. Moreover, imports of scrap paper should be encouraged to reduce large indirect impacts of scrap paper recycling on domestic environment.

Liang Sai [School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084 (China); Zhang, Tianzhu, E-mail: zhangtz@mail.tsinghua.edu.cn [School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084 (China); Xu Yijian [School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084 (China); China Academy of Urban Planning and Design, Beijing 100037 (China)

2012-03-15T23:59:59.000Z

32

Comparing urban solid waste recycling from the viewpoint of urban metabolism based on physical input-output model: A case of Suzhou in China  

SciTech Connect (OSTI)

Highlights: Black-Right-Pointing-Pointer Impacts of solid waste recycling on Suzhou's urban metabolism in 2015 are analyzed. Black-Right-Pointing-Pointer Sludge recycling for biogas is regarded as an accepted method. Black-Right-Pointing-Pointer Technical levels of reusing scrap tires and food wastes should be improved. Black-Right-Pointing-Pointer Other fly ash utilization methods should be exploited. Black-Right-Pointing-Pointer Secondary wastes from reusing food wastes and sludge should be concerned. - Abstract: Investigating impacts of urban solid waste recycling on urban metabolism contributes to sustainable urban solid waste management and urban sustainability. Using a physical input-output model and scenario analysis, urban metabolism of Suzhou in 2015 is predicted and impacts of four categories of solid waste recycling on urban metabolism are illustrated: scrap tire recycling, food waste recycling, fly ash recycling and sludge recycling. Sludge recycling has positive effects on reducing all material flows. Thus, sludge recycling for biogas is regarded as an accepted method. Moreover, technical levels of scrap tire recycling and food waste recycling should be improved to produce positive effects on reducing more material flows. Fly ash recycling for cement production has negative effects on reducing all material flows except solid wastes. Thus, other fly ash utilization methods should be exploited. In addition, the utilization and treatment of secondary wastes from food waste recycling and sludge recycling should be concerned.

Liang Sai, E-mail: liangsai09@gmail.com [School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084 (China); Zhang Tianzhu, E-mail: zhangtz@mail.tsinghua.edu.cn [School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084 (China)

2012-01-15T23:59:59.000Z

33

Treanmission Line Fault Location using Interoperability and Integration of Data and Model  

E-Print Network [OSTI]

. The second type is a sparse measurement based fault location scheme using phasor measurements from different substations located in the vicinity where the fault has occurred and can be applied if the measurements are not available from any of the line ends...

Dutta, Papiya

2014-01-10T23:59:59.000Z

34

Commissioning of output factors for uniform scanning proton beams  

SciTech Connect (OSTI)

Purpose: Current commercial treatment planning systems are not able to accurately predict output factors and calculate monitor units for proton fields. Patient-specific field output factors are thus determined by either measurements or empirical modeling based on commissioning data. The objective of this study is to commission output factors for uniform scanning beams utilized at the ProCure proton therapy centers. Methods: Using water phantoms and a plane parallel ionization chamber, the authors first measured output factors with a fixed 10 cm diameter aperture as a function of proton range and modulation width for clinically available proton beams with ranges between 4 and 31.5 cm and modulation widths between 2 and 15 cm. The authors then measured the output factor as a function of collimated field size at various calibration depths for proton beams of various ranges and modulation widths. The authors further examined the dependence of the output factor on the scanning area (i.e., uncollimated proton field), snout position, and phantom material. An empirical model was developed to calculate the output factor for patient-specific fields and the model-predicted output factors were compared to measurements. Results: The output factor increased with proton range and field size, and decreased with modulation width. The scanning area and snout position have a small but non-negligible effect on the output factors. The predicted output factors based on the empirical modeling agreed within 2% of measurements for all prostate treatment fields and within 3% for 98.5% of all treatment fields. Conclusions: Comprehensive measurements at a large subset of available beam conditions are needed to commission output factors for proton therapy beams. The empirical modeling agrees well with the measured output factor data. This investigation indicates that it is possible to accurately predict output factors and thus eliminate or reduce time-consuming patient-specific output measurements for proton treatments.

Zheng Yuanshui; Ramirez, Eric; Mascia, Anthony; Ding Xiaoning; Okoth, Benny; Zeidan, Omar; Hsi Wen; Harris, Ben; Schreuder, Andries N.; Keole, Sameer [ProCure Proton Therapy Center, 5901 West Memorial Road, Oklahoma City, Oklahoma 73142 (United States); ProCure Treatment Centers, 420 North Walnut Street, Bloomington, Indiana 47404 (United States); ProCure Proton Therapy Center, 5901 West Memorial Road, Oklahoma City, Oklahoma 73142 (United States)

2011-04-15T23:59:59.000Z

35

Comparison of CAISO-run Plexos output with LLNL-run Plexos output  

SciTech Connect (OSTI)

In this report we compare the output of the California Independent System Operator (CAISO) 33% RPS Plexos model when run on various computing systems. Specifically, we compare the output resulting from running the model on CAISO's computers (Windows) and LLNL's computers (both Windows and Linux). We conclude that the differences between the three results are negligible in the context of the entire system and likely attributed to minor differences in Plexos version numbers as well as the MIP solver used in each case.

Schmidt, A; Meyers, C; Smith, S

2011-12-20T23:59:59.000Z

36

Environmental Modelling & Software 15 (2000) 681692 www.elsevier.com/locate/envsoft  

E-Print Network [OSTI]

-scale air pollution modelling using adaptive unstructured meshes A.S. Tomlin a,* , S. Ghorai a , G. Hart of Computer Studies, University of Leeds, Leeds LS2 9JT, UK Abstract High resolution models of air pollution but less so in meteorological and air pollution models. However, it is well known that grid resolution has

Utah, University of

37

Enhanced performance CCD output amplifier  

DOE Patents [OSTI]

A low-noise FET amplifier is connected to amplify output charge from a che coupled device (CCD). The FET has its gate connected to the CCD in common source configuration for receiving the output charge signal from the CCD and output an intermediate signal at a drain of the FET. An intermediate amplifier is connected to the drain of the FET for receiving the intermediate signal and outputting a low-noise signal functionally related to the output charge signal from the CCD. The amplifier is preferably connected as a virtual ground to the FET drain. The inherent shunt capacitance of the FET is selected to be at least equal to the sum of the remaining capacitances.

Dunham, Mark E. (Los Alamos, NM); Morley, David W. (Santa Fe, NM)

1996-01-01T23:59:59.000Z

38

UFO - The Universal FeynRules Output  

E-Print Network [OSTI]

We present a new model format for automatized matrix-element generators, the so- called Universal FeynRules Output (UFO). The format is universal in the sense that it features compatibility with more than one single generator and is designed to be flexible, modular and agnostic of any assumption such as the number of particles or the color and Lorentz structures appearing in the interaction vertices. Unlike other model formats where text files need to be parsed, the information on the model is encoded into a Python module that can easily be linked to other computer codes. We then describe an interface for the Mathematica package FeynRules that allows for an automatic output of models in the UFO format.

Cline Degrande; Claude Duhr; Benjamin Fuks; David Grellscheid; Olivier Mattelaer; Thomas Reiter

2012-07-31T23:59:59.000Z

39

UFO - The Universal FeynRules Output  

E-Print Network [OSTI]

We present a new model format for automatized matrix-element generators, the so- called Universal FeynRules Output (UFO). The format is universal in the sense that it features compatibility with more than one single generator and is designed to be flexible, modular and agnostic of any assumption such as the number of particles or the color and Lorentz structures appearing in the interaction vertices. Unlike other model formats where text files need to be parsed, the information on the model is encoded into a Python module that can easily be linked to other computer codes. We then describe an interface for the Mathematica package FeynRules that allows for an automatic output of models in the UFO format.

Degrande, Cline; Fuks, Benjamin; Grellscheid, David; Mattelaer, Olivier; Reiter, Thomas

2011-01-01T23:59:59.000Z

40

Environmental Modelling & Software 19 (2004) 285304 www.elsevier.com/locate/envsoft  

E-Print Network [OSTI]

Water Management District, Everglades Department, PO Box 24680, West Palm Beach, Florida 33416-4680, USA for Ecological Economics, University of Vermont, 590 Main Street, Burlington, VT 05405-0088, USA b South Florida are formulated as STELLA models, which adds to transparency and helps reuse. Spatial transport processes

Vermont, University of

Note: This page contains sample records for the topic "model output location" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


41

Verification of hourly forecasts of wind turbine power output  

SciTech Connect (OSTI)

A verification of hourly average wind speed forecasts in terms of hourly average power output of a MOD-2 was performed for four sites. Site-specific probabilistic transformation models were developed to transform the forecast and observed hourly average speeds to the percent probability of exceedance of an hourly average power output. (This transformation model also appears to have value in predicting annual energy production for use in wind energy feasibility studies.) The transformed forecasts were verified in a deterministic sense (i.e., as continuous values) and in a probabilistic sense (based upon the probability of power output falling in a specified category). Since the smoothing effects of time averaging are very pronounced, the 90% probability of exceedance was built into the transformation models. Semiobjective and objective (model output statistics) forecasts were made compared for the four sites. The verification results indicate that the correct category can be forecast an average of 75% of the time over a 24-hour period. Accuracy generally decreases with projection time out to approx. 18 hours and then may increase due to the fairly regular diurnal wind patterns that occur at many sites. The ability to forecast the correct power output category increases with increasing power output because occurrences of high hourly average power output (near rated) are relatively rare and are generally not forecast. The semiobjective forecasts proved superior to model output statistics in forecasting high values of power output and in the shorter time frames (1 to 6 hours). However, model output statistics were slightly more accurate at other power output levels and times. Noticeable differences were observed between deterministic and probabilistic (categorical) forecast verification results.

Wegley, H.L.

1984-08-01T23:59:59.000Z

42

Multi-horizon solar radiation forecasting for Mediterranean locations using time series models  

E-Print Network [OSTI]

Considering the grid manager's point of view, needs in terms of prediction of intermittent energy like the photovoltaic resource can be distinguished according to the considered horizon: following days (d+1, d+2 and d+3), next day by hourly step (h+24), next hour (h+1) and next few minutes (m+5 e.g.). Through this work, we have identified methodologies using time series models for the prediction horizon of global radiation and photovoltaic power. What we present here is a comparison of different predictors developed and tested to propose a hierarchy. For horizons d+1 and h+1, without advanced ad hoc time series pre-processing (stationarity) we find it is not easy to differentiate between autoregressive moving average (ARMA) and multilayer perceptron (MLP). However we observed that using exogenous variables improves significantly the results for MLP . We have shown that the MLP were more adapted for horizons h+24 and m+5. In summary, our results are complementary and improve the existing prediction techniques ...

Voyant, Cyril; Muselli, Marc; Nivet, Marie Laure

2013-01-01T23:59:59.000Z

43

Where is the ideal location for a US East Coast offshore grid? Michael J. Dvorak,1  

E-Print Network [OSTI]

weather model data from 2006­2010 were used to approximate wind farm output. The offshore grid was located%, and the combined capacity factor was 48% (gross). By interconnecting offshore wind energy farms 450 km apart of no and full-power events. Offshore grids to connect offshore wind energy (OWE) farms have been proposed

44

Sparse Convolved Gaussian Processes for Multi-output Regression  

E-Print Network [OSTI]

the concentration of different heavy metal pollutants [5]. Modelling multiple output variables is a challenge as we methodology for synthetic data and real world applications on pollution prediction and a sensor network. 1

Rattray, Magnus

45

Using Mesoscale Weather Model Output as Boundary Conditions for Atmospheric Large-Eddy Simulations and Wind-Plant Aerodynamic Simulations (Presentation)  

SciTech Connect (OSTI)

Wind plant aerodynamics are directly affected by the microscale weather, which is directly influenced by the mesoscale weather. Microscale weather refers to processes that occur within the atmospheric boundary layer with the largest scales being a few hundred meters to a few kilometers depending on the atmospheric stability of the boundary layer. Mesoscale weather refers to large weather patterns, such as weather fronts, with the largest scales being hundreds of kilometers wide. Sometimes microscale simulations that capture mesoscale-driven variations (changes in wind speed and direction over time or across the spatial extent of a wind plant) are important in wind plant analysis. In this paper, we present our preliminary work in coupling a mesoscale weather model with a microscale atmospheric large-eddy simulation model. The coupling is one-way beginning with the weather model and ending with a computational fluid dynamics solver using the weather model in coarse large-eddy simulation mode as an intermediary. We simulate one hour of daytime moderately convective microscale development driven by the mesoscale data, which are applied as initial and boundary conditions to the microscale domain, at a site in Iowa. We analyze the time and distance necessary for the smallest resolvable microscales to develop.

Churchfield, M. J.; Michalakes, J.; Vanderwende, B.; Lee, S.; Sprague, M. A.; Lundquist, J. K.; Moriarty, P. J.

2013-10-01T23:59:59.000Z

46

Modeling, Performance Analysis and Comparison of Two Level Single Chain Pointer Forwarding Strategy For Location Management in Wireless Mobile Communication  

E-Print Network [OSTI]

Global wireless networks enable mobile users to communicate regardless of their locations. Location management is an important part of the emerging wireless and mobile technology. A Personal Communication System (PCS) network must have an efficient way to keep track of the mobile users to deliver services effectively. Global System for Mobile Communication (GSM) is a commonly accepted standard for mobility management of mobile users. Location management involves location tracking, and location information storage. Location management requires mobile users to register at various registration areas whenever they are on the move. The registration process may cause excessive signaling traffic and long service delays. To improve the efficiency of location tracking and avoid call set up delays, several strategies such as local anchor scheme, per-user caching scheme and several pointer forwarding schemes have been proposed in the past. In this paper, we propose a new "Two Level Single Chain Pointer Forwarding (TLSCP...

Kant, C R; Prakash, N; Kant, Chhaya Ravi; Prakash, Nupur

2006-01-01T23:59:59.000Z

47

A Framework to Determine the Probability Density Function for the Output Power of Wind Farms  

E-Print Network [OSTI]

A Framework to Determine the Probability Density Function for the Output Power of Wind Farms Sairaj to the power output of a wind farm while factoring in the availability of the wind turbines in the farm availability model for the wind turbines, we propose a method to determine the wind-farm power output pdf

Liberzon, Daniel

48

DUAL-OUTPUT HOLA FIRMWARE AND TESTS  

E-Print Network [OSTI]

another channel (thus, "dual-output" HOLA) Another LDC+ROMB block was added to receive data from side S32PCI64 "SOLAR" mezzanine card: Provides access to S-LINK via PCI bus The first prototype of dual-outputDUAL-OUTPUT HOLA FIRMWARE AND TESTS Anton Kapliy Mel Shochet Fukun Tang Daping Weng #12;Summary

49

Simulation of one-minute power output from utility-scale photovoltaic generation systems.  

SciTech Connect (OSTI)

We present an approach to simulate time-synchronized, one-minute power output from large photovoltaic (PV) generation plants in locations where only hourly irradiance estimates are available from satellite sources. The approach uses one-minute irradiance measurements from ground sensors in a climatically and geographically similar area. Irradiance is translated to power using the Sandia Array Performance Model. Power output is generated for 2007 in southern Nevada are being used for a Solar PV Grid Integration Study to estimate the integration costs associated with various utility-scale PV generation levels. Plant designs considered include both fixed-tilt thin-film, and single-axis-tracked polycrystalline Si systems ranging in size from 5 to 300 MW{sub AC}. Simulated power output profiles at one-minute intervals were generated for five scenarios defined by total PV capacity (149.5 MW, 222 WM, 292 MW, 492 MW, and 892 MW) each comprising as many as 10 geographically separated PV plants.

Stein, Joshua S.; Ellis, Abraham; Hansen, Clifford W.

2011-08-01T23:59:59.000Z

50

922 IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 16, NO. 6, AUGUST 1998 Mobility Modeling, Location Tracking, and  

E-Print Network [OSTI]

mobility management to cope with frequent mobile handoff and rerouting of connections. Although much of the key problems within this set is mobility management. Mobility management as defined in [1] entails both connection management and location management. Since ATM is a connection-oriented technology

Hunt, Galen

51

System and method for cancelling the effects of stray magnetic fields from the output of a variable reluctance sensor  

DOE Patents [OSTI]

A sensor system for sensing a rotation of a sensing wheel is disclosed. The sensor system has a sensing coil in juxtaposition with the sensing wheel. Moreover, the sensing coil has a sensing coil output signal indicative of the rotational speed of the sensing wheel. Further, a cancellation coil is located remotely from the sensing coil and connected in series therewith. Additionally, the cancellation coil has a cancellation coil output signal indicative of an environmental disturbance which is effecting the sensing coil output signal. The cancellation coil output signal operates to cancel the effects of the environmental disturbance on the sensing coil output signal.

Chen, Chingchi (Ann Arbor, MI); Degner, Michael W. (Farmington Hills, MI)

2002-11-19T23:59:59.000Z

52

Control of fuel cell power output Federico Zenith, Sigurd Skogestad *  

E-Print Network [OSTI]

Control of fuel cell power output Federico Zenith, Sigurd Skogestad * Department of Chemical A simplified dynamic model for fuel cells is developed, based on the concept of instantaneous characteristic, which is the set of values of current and voltage that a fuel cell can reach instantaneously

Skogestad, Sigurd

53

Bayesian Learning of unobservable output 1 Bayesian Learning of unobservable output  

E-Print Network [OSTI]

Bayesian Learning of unobservable output 1 Bayesian Learning of unobservable output aggregating the consistency of our method and illustrate its efficiency using simulations. Although up to our knowledge there are no similar algorithms for unobservable output, we compared in our simulations to supervised approaches

Provence Aix-Marseille I, Universit de

54

Waveguide submillimetre laser with a uniform output beam  

SciTech Connect (OSTI)

A method for producing non-Gaussian light beams with a uniform intensity profile is described. The method is based on the use of a combined waveguide quasi-optical resonator containing a generalised confocal resonator with an inhomogeneous mirror with absorbing inhomogeneities discretely located on its surface and a hollow dielectric waveguide whose size satisfies the conditions of self-imaging of a uniform field in it. The existence of quasi-homogeneous beams at the output of an optically pumped 0.1188-mm waveguide CH{sub 3}OH laser with a amplitude-stepped mirror is confirmed theoretically and experimentally. (lasers)

Volodenko, A V; Gurin, O V; Degtyarev, A V; Maslov, Vyacheslav A; Svich, V A; Topkov, A N [V.N. Karazin Kharkiv National University, Kharkiv (Ukraine)

2007-01-31T23:59:59.000Z

55

X-ray source assembly having enhanced output stability, and fluid stream analysis applications thereof  

DOE Patents [OSTI]

An x-ray source assembly and method of operation are provided having enhanced output stability. The assembly includes an anode having a source spot upon which electrons impinge and a control system for controlling position of the anode source spot relative to an output structure. The control system can maintain the anode source spot location relative to the output structure notwithstanding a change in one or more operating conditions of the x-ray source assembly. One aspect of the disclosed invention is most amenable to the analysis of sulfur in petroleum-based fuels.

Radley, Ian (Glenmont, NY); Bievenue, Thomas J. (Delmar, NY); Burdett, John H. (Charlton, NY); Gallagher, Brian W. (Guilderland, NY); Shakshober, Stuart M. (Hudson, NY); Chen, Zewu (Schenectady, NY); Moore, Michael D. (Alplaus, NY)

2008-06-08T23:59:59.000Z

56

Anisotropic Grid Adaptation for Multiple Aerodynamic Outputs  

E-Print Network [OSTI]

Anisotropic gridadaptive strategies are presented for viscous flow simulations in which the accurate prediction of multiple aerodynamic outputs (such as the lift, drag, and moment coefficients) is required from a single ...

Venditti, David A.

57

Optimization on Solar Panels: Finding the Optimal Output Brian Y. Lu  

E-Print Network [OSTI]

Optimization on Solar Panels: Finding the Optimal Output Brian Y. Lu January 1, 2013 1 Introduction of solar panel: Routing the configuration between solar cells with a switch matrix. However, their result models and control policies for the optimal output of solar panels. The smallest unit on a solar panel

Lavaei, Javad

58

Quality assurance of solar thermal systems with the ISFH-Input/Output-Procedure  

E-Print Network [OSTI]

Quality assurance of solar thermal systems with the ISFH- Input/Output-Procedure Peter Paerisch different solar systems. The simulation model was validated with measured data. The deviation between meas * Tel. +49 (0)5151-999503, Fax: +49 (0)5151-999500, Email: paerisch@isfh.de Abstract Input/Output

59

PV output smoothing with energy storage.  

SciTech Connect (OSTI)

This report describes an algorithm, implemented in Matlab/Simulink, designed to reduce the variability of photovoltaic (PV) power output by using a battery. The purpose of the battery is to add power to the PV output (or subtract) to smooth out the high frequency components of the PV power that that occur during periods with transient cloud shadows on the PV array. The control system is challenged with the task of reducing short-term PV output variability while avoiding overworking the battery both in terms of capacity and ramp capability. The algorithm proposed by Sandia is purposely very simple to facilitate implementation in a real-time controller. The control structure has two additional inputs to which the battery can respond. For example, the battery could respond to PV variability, load variability or area control error (ACE) or a combination of the three.

Ellis, Abraham; Schoenwald, David Alan

2012-03-01T23:59:59.000Z

60

Predicting the Energy Output of Wind Farms Based on Weather Data: Important Variables and their Correlation  

E-Print Network [OSTI]

Wind energy plays an increasing role in the supply of energy world-wide. The energy output of a wind farm is highly dependent on the weather condition present at the wind farm. If the output can be predicted more accurately, energy suppliers can coordinate the collaborative production of different energy sources more efficiently to avoid costly overproductions. With this paper, we take a computer science perspective on energy prediction based on weather data and analyze the important parameters as well as their correlation on the energy output. To deal with the interaction of the different parameters we use symbolic regression based on the genetic programming tool DataModeler. Our studies are carried out on publicly available weather and energy data for a wind farm in Australia. We reveal the correlation of the different variables for the energy output. The model obtained for energy prediction gives a very reliable prediction of the energy output for newly given weather data.

Vladislavleva, Katya; Neumann, Frank; Wagner, Markus

2011-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "model output location" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


61

Library Locations Locations other than Main Library  

E-Print Network [OSTI]

Library Locations Locations other than Main Library Example: Feminist Studies HQ1410 .U54 2009 University of California, Santa Barbara Library www.library.ucsb.edu Updated 3-2014 A - B.......................................6 Central M - N..................................................Arts Library (Music Building) P

62

STANDARD OPERATING PROCEDURE Location(s): ___________________________________________________  

E-Print Network [OSTI]

of as hazardous waste. 8. Decontamination: Specific instructions: For light contamination of small areas or items12.1 STANDARD OPERATING PROCEDURE for PHENOL Location(s): ___________________________________________________ Chemical(s): Phenol Specific Hazards: May be fatal if inhaled. Harmful if absorbed through skin. Harmful

Pawlowski, Wojtek

63

Bioenergy technology balancing energy output with environmental  

E-Print Network [OSTI]

E2.3 Bioenergy technology ­ balancing energy output with environmental benefitsbenefits John standards #12;Is it right to grow bioenergy? Or How much bioenergy production is right? #12;Historical bioenergy Farmers historically used 25% land for horse feed #12;Energy crops are `solar panels' Solar energy

Levi, Ran

64

Single Inductor Dual Output Buck Converter  

E-Print Network [OSTI]

of value 3V. The main focus areas are low cross regulation between the outputs and supply of completely independent load current levels while maintaining desired values (1.2V,1.5 V) within well controlled ripple levels. Dynamic hysteresis control is used...

Eachempatti, Haritha

2010-07-14T23:59:59.000Z

65

Porous radiant burners having increased radiant output  

DOE Patents [OSTI]

Means and methods for enhancing the output of radiant energy from a porous radiant burner by minimizing the scattering and increasing the adsorption, and thus emission of such energy by the use of randomly dispersed ceramic fibers of sub-micron diameter in the fabrication of ceramic fiber matrix burners and for use therein.

Tong, Timothy W. (Tempe, AZ); Sathe, Sanjeev B. (Tempe, AZ); Peck, Robert E. (Tempe, AZ)

1990-01-01T23:59:59.000Z

66

Anisotropic Grid Adaptation for Multiple Aerodynamic Outputs  

E-Print Network [OSTI]

Anisotropic Grid Adaptation for Multiple Aerodynamic Outputs David A. Venditti and David L Anisotropic gridadaptive strategies are presented for viscous flow simulations in which the accurate estimation and Hessian-based anisotropic grid adaptation. Airfoil test cases are presented to demonstrate

Peraire, Jaime

67

Automated detection and location of indications in eddy current signals  

DOE Patents [OSTI]

A computer implemented information extraction process that locates and identifies eddy current signal features in digital point-ordered signals, signals representing data from inspection of test materials, by enhancing the signal features relative to signal noise, detecting features of the signals, verifying the location of the signal features that can be known in advance, and outputting information about the identity and location of all detected signal features.

Brudnoy, David M. (Albany, NY); Oppenlander, Jane E. (Burnt Hills, NY); Levy, Arthur J. (Schenectady, NY)

2000-01-01T23:59:59.000Z

68

Investigation of the effects of cell model and subcellular location of gold nanoparticles on nuclear dose enhancement factors using Monte Carlo simulation  

SciTech Connect (OSTI)

Purpose: The authors aims were to model how various factors influence radiation dose enhancement by gold nanoparticles (AuNPs) and to propose a new modeling approach to the dose enhancement factor (DEF).Methods: The authors used Monte Carlo N-particle (MCNP 5) computer code to simulate photon and electron transport in cells. The authors modeled human breast cancer cells as a single cell, a monolayer, or a cluster of cells. Different numbers of 5, 30, or 50 nm AuNPs were placed in the extracellular space, on the cell surface, in the cytoplasm, or in the nucleus. Photon sources examined in the simulation included nine monoenergetic x-rays (10100 keV), an x-ray beam (100 kVp), and {sup 125}I and {sup 103}Pd brachytherapy seeds. Both nuclear and cellular dose enhancement factors (NDEFs, CDEFs) were calculated. The ability of these metrics to predict the experimental DEF based on the clonogenic survival of MDA-MB-361 human breast cancer cells exposed to AuNPs and x-rays were compared.Results: NDEFs show a strong dependence on photon energies with peaks at 15, 30/40, and 90 keV. Cell model and subcellular location of AuNPs influence the peak position and value of NDEF. NDEFs decrease in the order of AuNPs in the nucleus, cytoplasm, cell membrane, and extracellular space. NDEFs also decrease in the order of AuNPs in a cell cluster, monolayer, and single cell if the photon energy is larger than 20 keV. NDEFs depend linearly on the number of AuNPs per cell. Similar trends were observed for CDEFs. NDEFs using the monolayer cell model were more predictive than either single cell or cluster cell models of the DEFs experimentally derived from the clonogenic survival of cells cultured as a monolayer. The amount of AuNPs required to double the prescribed dose in terms of mg Au/g tissue decreases as the size of AuNPs increases, especially when AuNPs are in the nucleus and the cytoplasm. For 40 keV x-rays and a cluster of cells, to double the prescribed x-ray dose (NDEF = 2) using 30 nm AuNPs, would require 5.1 0.2, 9 1, 10 1, 10 1 mg Au/g tissue in the nucleus, in the cytoplasm, on the cell surface, or in the extracellular space, respectively. Using 50 nm AuNPs, the required amount decreases to 3.1 0.3, 8 1, 9 1, 9 1 mg Au/g tissue, respectively.Conclusions: NDEF is a new metric that can predict the radiation enhancement of AuNPs for various experimental conditions. Cell model, the subcellular location and size of AuNPs, and the number of AuNPs per cell, as well as the x-ray photon energy all have effects on NDEFs. Larger AuNPs in the nucleus of cluster cells exposed to x-rays of 15 or 40 keV maximize NDEFs.

Cai, Zhongli; Chattopadhyay, Niladri; Kwon, Yongkyu Luke [Department of Pharmaceutical Sciences, University of Toronto, Toronto, Ontario M5S 3M2 (Canada)] [Department of Pharmaceutical Sciences, University of Toronto, Toronto, Ontario M5S 3M2 (Canada); Pignol, Jean-Philippe [Department of Radiation Oncology, University of Toronto, Toronto, Ontario M4N 3M5, Canada and Department of Medical Biophysics, University of Toronto, Toronto, Ontario M4N 3M5 (Canada)] [Department of Radiation Oncology, University of Toronto, Toronto, Ontario M4N 3M5, Canada and Department of Medical Biophysics, University of Toronto, Toronto, Ontario M4N 3M5 (Canada); Lechtman, Eli [Department of Medical Biophysics, University of Toronto, Toronto, Ontario M4N 3M5 (Canada)] [Department of Medical Biophysics, University of Toronto, Toronto, Ontario M4N 3M5 (Canada); Reilly, Raymond M. [Department of Pharmaceutical Sciences, University of Toronto, Toronto, Ontario M5S 3M2 (Canada) [Department of Pharmaceutical Sciences, University of Toronto, Toronto, Ontario M5S 3M2 (Canada); Department of Medical Imaging, University of Toronto, Toronto, Ontario M5S 3E2 (Canada); Toronto General Research Institute, University Health Network, Toronto, Ontario M5G 2C4 (Canada)

2013-11-15T23:59:59.000Z

69

Administrator Ready Reference Guide Customizing an Output Style  

E-Print Network [OSTI]

may be in various sections of the instructions. Some things to look for: - line spacing Preview Utility (Tools, Preview Output Styles) or by simply opening the Output Style Editor (Bibliography, Edit button -- to the right of the output style drop- down). The Output Style Preview Utility

University of Technology, Sydney

70

Off-set stabilizer for comparator output  

DOE Patents [OSTI]

A stabilized off-set voltage is input as the reference voltage to a comparator. In application to a time-interval meter, the comparator output generates a timing interval which is independent of drift in the initial voltage across the timing capacitor. A precision resistor and operational amplifier charge a capacitor to a voltage which is precisely offset from the initial voltage. The capacitance of the reference capacitor is selected so that substantially no voltage drop is obtained in the reference voltage applied to the comparator during the interval to be measured.

Lunsford, James S. (Los Alamos, NM)

1991-01-01T23:59:59.000Z

71

Reversible micromachining locator  

DOE Patents [OSTI]

This invention provides a device which includes a locator, a kinematic mount positioned on a conventional tooling machine, a part carrier disposed on the locator and a retainer ring. The locator has disposed therein a plurality of steel balls, placed in an equidistant position circumferentially around the locator. The kinematic mount includes a plurality of magnets which are in registry with the steel balls on the locator. In operation, a blank part to be machined is placed between a surface of a locator and the retainer ring (fitting within the part carrier). When the locator (with a blank part to be machined) is coupled to the kinematic mount, the part is thus exposed for the desired machining process. Because the locator is removably attachable to the kinematic mount, it can easily be removed from the mount, reversed, and reinserted onto the mount for additional machining. Further, the locator can likewise be removed from the mount and placed onto another tooling machine having a properly aligned kinematic mount. Because of the unique design and use of magnetic forces of the present invention, positioning errors of less than 0.25 micrometer for each machining process can be achieved. 7 figs.

Salzer, L.J.; Foreman, L.R.

1999-08-31T23:59:59.000Z

72

Reversible micromachining locator  

DOE Patents [OSTI]

This invention provides a device which includes a locator, a kinematic mount positioned on a conventional tooling machine, a part carrier disposed on the locator and a retainer ring. The locator has disposed therein a plurality of steel balls, placed in an equidistant position circumferentially around the locator. The kinematic mount includes a plurality of magnets which are in registry with the steel balls on the locator. In operation, a blank part to be machined is placed between a surface of a locator and the retainer ring (fitting within the part carrier). When the locator (with a blank part to be machined) is coupled to the kinematic mount, the part is thus exposed for the desired machining process. Because the locator is removably attachable to the kinematic mount, it can easily be removed from the mount, reversed, and reinserted onto the mount for additional machining. Further, the locator can likewise be removed from the mount and placed onto another tooling machine having a properly aligned kinematic mount. Because of the unique design and use of magnetic forces of the present invention, positioning errors of less than 0.25 micrometer for each machining process can be achieved.

Salzer, Leander J. (Los Alamos, NM); Foreman, Larry R. (Los Alamos, NM)

1999-01-01T23:59:59.000Z

73

World crude output overcomes Persian Gulf disruption  

SciTech Connect (OSTI)

Several OPEC producers made good on their promises to replace 2.7 MMbpd of oil exports that vanished from the world market after Iraq took over Kuwait. Even more incredibly, they accomplished this while a breathtaking 1.2- MMbopd reduction in Soviet output took place during the course of 1991. After Abu Dhabi, Indonesia, Iran, Libya, Nigeria, Saudi Arabia and Venezuela turned the taps wide open, their combined output rose 2.95 MMbopd. Put together with a 282,000-bopd increase by Norway and contributions from smaller producers, this enabled world oil production to remain within 400,000 bopd of its 1990 level. The 60.5-MMbopd average was off by just 0.7%. This paper reports that improvement took place in five of eight regions. Largest increases were in Western Europe and Africa. Greatest reductions occurred in Eastern Europe and the Middle East. Fifteen nations produced 1 MMbopd or more last year, compared with 17 during 1990.

Not Available

1992-02-01T23:59:59.000Z

74

SARAH 3.2: Dirac Gauginos, UFO output, and more  

E-Print Network [OSTI]

SARAH is a Mathematica package optimized for the fast, efficient and precise study of supersymmetric models beyond the MSSM: a new model can be defined in a short form and all vertices are derived. This allows SARAH to create model files for FeynArts/FormCalc, CalcHep/CompHep and WHIZARD/OMEGA. The newest version of SARAH now provides the possibility to create model files in the UFO format which is supported by MadGraph 5, MadAnalysis, GoSam, and soon by Herwig++. Furthermore, SARAH also calculates the mass matrices, RGEs and one-loop corrections to the mass spectrum. This information is used to write source code for SPheno in order to create a precision spectrum generator for the given model. This spectrum-generator-generator functionality as well as the output of WHIZARD and CalcHep model files have seen further improvement in this version. Also models including Dirac Gauginos are supported with the new version of SARAH, and additional checks for the consistency of model implementations have been created.

Florian Staub

2013-02-12T23:59:59.000Z

75

Reversible micromachining locator  

DOE Patents [OSTI]

A locator with a part support is used to hold a part onto the kinematic mount of a tooling machine so that the part can be held in or replaced in exactly the same position relative to the cutting tool for machining different surfaces of the part or for performing different machining operations on the same or different surfaces of the part. The locator has disposed therein a plurality of steel balls placed at equidistant positions around the planar surface of the locator and the kinematic mount has a plurality of magnets which alternate with grooves which accommodate the portions of the steel balls projecting from the locator. The part support holds the part to be machined securely in place in the locator. The locator can be easily detached from the kinematic mount, turned over, and replaced onto the same kinematic mount or another kinematic mount on another tooling machine without removing the part to be machined from the locator so that there is no need to touch or reposition the part within the locator, thereby assuring exact replication of the position of the part in relation to the cutting tool on the tooling machine for each machining operation on the part.

Salzer, Leander J. (Los Almos, NM); Foreman, Larry R. (late of Los Alamos, NM)

2002-01-01T23:59:59.000Z

76

Application of computer voice input/output  

SciTech Connect (OSTI)

The advent of microprocessors and other large-scale integration (LSI) circuits is making voice input and output for computers and instruments practical; specialized LSI chips for speech processing are appearing on the market. Voice can be used to input data or to issue instrument commands; this allows the operator to engage in other tasks, move about, and to use standard data entry systems. Voice synthesizers can generate audible, easily understood instructions. Using voice characteristics, a control system can verify speaker identity for security purposes. Two simple voice-controlled systems have been designed at Los Alamos for nuclear safeguards applicaations. Each can easily be expanded as time allows. The first system is for instrument control that accepts voice commands and issues audible operator prompts. The second system is for access control. The speaker's voice is used to verify his identity and to actuate external devices.

Ford, W.; Shirk, D.G.

1981-01-01T23:59:59.000Z

77

Coordinated Output Regulation of Multiple Heterogeneous Linear Systems  

E-Print Network [OSTI]

, the generalizations of coordination of multiple linear dynamic systems to the cooperative output regulation problemCoordinated Output Regulation of Multiple Heterogeneous Linear Systems Ziyang Meng, Tao Yang, Dimos V. Dimarogonas, and Karl H. Johansson Abstract-- The coordinated output regulation problem

Dimarogonas, Dimos

78

Quality assurance with the ISFH-Input/Output-Procedure 6-year-experience with 14 solar thermal systems  

E-Print Network [OSTI]

Quality assurance with the ISFH-Input/Output-Procedure 6-year-experience with 14 solar thermal the confidence in solar thermal energy. The so called Input/Output-Procedure is controlling the solar heat systems. The simulation model was validated with measured data and a lot of failures in 11 solar thermal

79

Locating Heat Recovery Opportunities  

E-Print Network [OSTI]

Basic concepts of heat recovery are defined as they apply to the industrial community. Methods for locating, ranking, and developing heat recovery opportunities are presented and explained. The needs for useful heat 'sinks' are emphasized as equal...

Waterland, A. F.

1981-01-01T23:59:59.000Z

80

International land rig locator  

SciTech Connect (OSTI)

Mechanical specifications, ratings, locations, and status are listed for each of the 5,000 contract rotary drilling rigs operated by the more than 700 independent drilling contractors throughout the Free World.

Not Available

1984-03-01T23:59:59.000Z

Note: This page contains sample records for the topic "model output location" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


81

International land rig locator  

SciTech Connect (OSTI)

Mechanical specifications, ratings, locations, and status are listed for each of the 5,000 contract rotary drilling rigs operated by more than 700 independent drilling contractors throughout the Free World.

Not Available

1983-09-01T23:59:59.000Z

82

Location linked information  

E-Print Network [OSTI]

This work builds an infrastructure called Location Linked Information that offers a means to associate digital information with public, physical places. This connection creates a hybrid virtual/physical space, called glean ...

Mankins, Matthew William David, 1975-

2003-01-01T23:59:59.000Z

83

a r r i o r BUILDING# NAME LOCATION BUILDING# NAME LOCATION OTHER BUILDINGS LOCATION SORORITIES LOCATION  

E-Print Network [OSTI]

Admissions Parking Palmer Lake B l a c k W a r r i o r R i v e r BUILDING# NAME LOCATION BUILDING# NAME LOCATION OTHER BUILDINGS LOCATION SORORITIES LOCATION 7046 70127012 1155 10331033 1150 1039 1038

Carver, Jeffrey C.

84

Uncertainty and sensitivity analysis for photovoltaic system modeling.  

SciTech Connect (OSTI)

We report an uncertainty and sensitivity analysis for modeling DC energy from photovoltaic systems. We consider two systems, each comprised of a single module using either crystalline silicon or CdTe cells, and located either at Albuquerque, NM, or Golden, CO. Output from a PV system is predicted by a sequence of models. Uncertainty in the output of each model is quantified by empirical distributions of each model's residuals. We sample these distributions to propagate uncertainty through the sequence of models to obtain an empirical distribution for each PV system's output. We considered models that: (1) translate measured global horizontal, direct and global diffuse irradiance to plane-of-array irradiance; (2) estimate effective irradiance from plane-of-array irradiance; (3) predict cell temperature; and (4) estimate DC voltage, current and power. We found that the uncertainty in PV system output to be relatively small, on the order of 1% for daily energy. Four alternative models were considered for the POA irradiance modeling step; we did not find the choice of one of these models to be of great significance. However, we observed that the POA irradiance model introduced a bias of upwards of 5% of daily energy which translates directly to a systematic difference in predicted energy. Sensitivity analyses relate uncertainty in the PV system output to uncertainty arising from each model. We found that the residuals arising from the POA irradiance and the effective irradiance models to be the dominant contributors to residuals for daily energy, for either technology or location considered. This analysis indicates that efforts to reduce the uncertainty in PV system output should focus on improvements to the POA and effective irradiance models.

Hansen, Clifford W.; Pohl, Andrew Phillip; Jordan, Dirk [National Center for Photovoltaics, National Renewable Energy Laboratory, Golden, CO] [National Center for Photovoltaics, National Renewable Energy Laboratory, Golden, CO

2013-12-01T23:59:59.000Z

85

Computer Lab Information Location  

E-Print Network [OSTI]

M340 Computer Lab Information · Location: The computer labs accessible to you are Weber 205 it is recommended that you save your files on a floppy when you are finished. · There is another directory, g:\\m340 to the saved files you have to add the directory to the Matlab path. To do this type addpath g:\\m340

Dangelmayr, Gerhard

86

SWAT 2012 Input/Output Documentation  

E-Print Network [OSTI]

The Soil and Water Assessment Tool (SWAT) is a comprehensive model that requires a diversity of information in order to run. Novice users may feel overwhelmed by the variety and number of inputs when they first begin to use the model. This document...

Arnold, J.G.; Kiniry, J.R.; Srinivasan, R.; Williams, J.R.; Haney, E.B.; Neitsch, S.L.

2013-03-04T23:59:59.000Z

87

action potential output: Topics by E-print Network  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

HF efficiency, but does not necessarily yield a higher measurable power (power in the bucket). For low Carroll, David L. 376 A Spatial Analysis of Multivariate Output from...

88

advisory capability output: Topics by E-print Network  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

HF efficiency, but does not necessarily yield a higher measurable power (power in the bucket). For low Carroll, David L. 453 A Spatial Analysis of Multivariate Output from...

89

NREL: Wind Research - Boosting Wind Plant Power Output by 4%...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Boosting Wind Plant Power Output by 4%-5% through Coordinated Turbine Controls July 30, 2014 Wind plant underperformance has plagued wind plant developers for years. To address...

90

Single-photon quantum router with multiple output ports  

E-Print Network [OSTI]

We study the multi-channel quantum routing of the single photons in a waveguide-emitter system. The channels are composed by the waveguides and are connected by intermediate two-level emitters. By adjusting the intermediate emitters, the output channels of the input single photons can be controlled. This is demonstrated for the cases of one output channel, two output channels and the generic N output channels. The results show that the multi-channel quantum routing of single photons can be well achieved in present system. This sheds light on the experimental realization of quantum routing of single photons.

Wei-Bin Yan; Heng Fan

2013-11-26T23:59:59.000Z

91

Transportation Networks and Location A Geometric Approach  

E-Print Network [OSTI]

Transportation Networks and Location A Geometric Approach Belén Palop1,2 1Departamento de March 2009 Florida State University #12;Belén Palop, UVa, SUNY Outline Transportation Network Model;Transportation Network Model Belén Palop, UVa, SUNY Outline Transportation Network Model Network placement

Palop del Río, Belén

92

Method of locating underground mines fires  

DOE Patents [OSTI]

An improved method of locating an underground mine fire by comparing the pattern of measured combustion product arrival times at detector locations with a real time computer-generated array of simulated patterns. A number of electronic fire detection devices are linked thru telemetry to a control station on the surface. The mine's ventilation is modeled on a digital computer using network analysis software. The time reguired to locate a fire consists of the time required to model the mines' ventilation, generate the arrival time array, scan the array, and to match measured arrival time patterns to the simulated patterns.

Laage, Linneas (Eagam, MN); Pomroy, William (St. Paul, MN)

1992-01-01T23:59:59.000Z

93

Bayesian analysis of computer code outputs  

E-Print Network [OSTI]

real-world phenomena. They are typically used to predict the corresponding real-world phenomenon, as in the following examples. Modern weather forecasting is done using enormously complex models of the atmosphere (and its interactions with land and sea). The primary intention is to predict future weather, given information about current conditions. Manufacturers of motor car engines build models to predict their behaviour. They are used to explore possible variations in engine design, and thereby to avoid the time and expense of actually building many unsuccessful variants in the search for an improved design. Water engineers build network ow models of sewer systems, in order to predict where problems of surcharging and ooding will arise under rainstorm conditions. They are then used to explore changes to the network to solve those problems. Models of atmospheric dispersion are used to predict the spread and deposition

Marc C Kennedy; Anthony O& apos; Hagan; Neil Higgins

2002-01-01T23:59:59.000Z

94

GAMS program used to estimate capacity output using a distance function with both good and bad output, variable returns to scale and weak disposability of the bad outputs.  

E-Print Network [OSTI]

." VIMS Marine resource Report N. 2007-6. August 2007. Author: John B. Walden NMFS/NEFSC 166 Water St(obs) weights ; POSITIVE Variable weight, lambda; EQUATIONS CONSTR1(GOUTPUT, OBS) DEA constraint for each output

95

Electric current locator  

DOE Patents [OSTI]

The disclosure herein provides an apparatus for location of a quantity of current vectors in an electrical device, where the current vector has a known direction and a known relative magnitude to an input current supplied to the electrical device. Mathematical constants used in Biot-Savart superposition equations are determined for the electrical device, the orientation of the apparatus, and relative magnitude of the current vector and the input current, and the apparatus utilizes magnetic field sensors oriented to a sensing plane to provide current vector location based on the solution of the Biot-Savart superposition equations. Description of required orientations between the apparatus and the electrical device are disclosed and various methods of determining the mathematical constants are presented.

King, Paul E. (Corvallis, OR); Woodside, Charles Rigel (Corvallis, OR)

2012-02-07T23:59:59.000Z

96

TRIPLE OUTPUT POWER SUPPLY Agilent MODEL E3630A  

E-Print Network [OSTI]

, manufacture, and intended use of the instrument. Agilent Technologies assumes no liability for the customer, the instrument chassis and cabinet must be connected to an electrical ground. The instrument must be connected to the ac power supply mains through a three-conductor power cable, with the third wire firmly connected

Ravikumar, B.

97

FAST MULTI-CLASS IMAGE ANNOTATION WITH RANDOM SUBWINDOWS AND MULTIPLE OUTPUT RANDOMIZED TREES  

E-Print Network [OSTI]

of Electrical Engineering and Computer Science 2Bioinformatics and Modeling - GIGA-R University of Li`ege, Sart annotation, machine learning, decision trees, extremely randomized trees, structured outputs Abstract significantly outperforms the basic method and shows good performances with respect to the state

Wehenkel, Louis

98

Analytical input-output and supply chain study of China's coke and steel sectors  

E-Print Network [OSTI]

I design an input-output model to investigate the energy supply chain of coal-coke-steel in China. To study the demand, supply, and energy-intensity issues for coal and coke from a macroeconomic perspective, I apply the ...

Li, Yu, 1976-

2004-01-01T23:59:59.000Z

99

Abstract: Wind Energy Conversion Systems (WECS) produce fluctuating output power, which may cause voltage fluctuations and  

E-Print Network [OSTI]

: An approach to model the solar cell system with coupled multi-physics equations (photovoltaic, electrothermalAbstract: Wind Energy Conversion Systems (WECS) produce fluctuating output power, which may cause in a network of any size can be performed. An algorithm for flicker measurement in the frequency do- main

Gross, George

100

Cooling output optimization of an air handling unit Andrew Kusiak *, Mingyang Li  

E-Print Network [OSTI]

supply temperature and supply air temperature in response to the dynamic cooling load and changingCooling output optimization of an air handling unit Andrew Kusiak *, Mingyang Li Department mining Neural network Multi-objective optimization Evolutionary computation Dynamic modeling Cooling

Kusiak, Andrew

Note: This page contains sample records for the topic "model output location" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


101

Challenges in Predicting Power Output from Offshore Wind Farms  

E-Print Network [OSTI]

Challenges in Predicting Power Output from Offshore Wind Farms R. J. Barthelmie1 and S. C. Pryor2 Abstract: Offshore wind energy is developing rapidly in Europe and the trend is towards large wind farms an offshore wind farm, accurate assessment of the wind resource/power output from the wind farm is a necessity

Pryor, Sara C.

102

ANALOG-DIGITAL INPUT OUTPUT SYSTEM FOR APPLE CO  

E-Print Network [OSTI]

ADIOS ANALOG-DIGITAL INPUT OUTPUT SYSTEM FOR APPLE CO NATIONAL RADIO ASTRONOMY OBSERVATORY TABLES ADIOS - ANALOG-DIGITAL INPUT OUTPUT SYSTEM FOR APPLE COMPUTER TABLE FOR CONTENTS Page I Module and Apple Card (Photograph) Figure 3 Complete Apple/ADIOS System (Photograph) Figure 4 Analog

Groppi, Christopher

103

Most efficient quantum thermoelectric at finite power output  

E-Print Network [OSTI]

Machines are only Carnot efficient if they are reversible, but then their power output is vanishingly small. Here we ask, what is the maximum efficiency of an irreversible device with finite power output? We use a nonlinear scattering theory to answer this question for thermoelectric quantum systems; heat engines or refrigerators consisting of nanostructures or molecules that exhibit a Peltier effect. We find that quantum mechanics places an upper bound on both power output, and on the efficiency at any finite power. The upper bound on efficiency equals Carnot efficiency at zero power output, but decays with increasing power output. It is intrinsically quantum (wavelength dependent), unlike Carnot efficiency. This maximum efficiency occurs when the system lets through all particles in a certain energy window, but none at other energies. A physical implementation of this is discussed, as is the suppression of efficiency by a phonon heat flow.

Robert S. Whitney

2014-03-13T23:59:59.000Z

104

ARM - Instrument Location Table  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary)morphinanInformation InInformation InExplosionAnnouncements MediagovCampaignsListgovInstrumentsLocation Table

105

Relationship Among Efficiency and Output Power of Heat Energy Converters  

E-Print Network [OSTI]

Relationship among efficiency and output power of heat-electric energy converters as well as of any converters for transforming of heat energy into any other kind of energy is considered. It is shown, that the parameter efficiency does not determine univocally the output power of a converter. It is proposed to use another parameter for determination of working ability of heat energy converters. It is shown, that high output power can not be achieved by any kind of Stirling-type converters in spite of their high efficiency.

Alexander Luchinskiy

2004-09-02T23:59:59.000Z

106

Steady-state bumpless transfer under controller uncertainty using the state/output feedback topology  

SciTech Connect (OSTI)

Linear quadratic (LQ) bumpless transfer design introduced recently by Turner and Walker gives a very convenient and straightforward computational procedure for the steady-state bumpless transfer operator synthesis. It is, however, found to be incapable of providing convergence of the output of the offline controller to that of the online controller in several industrial applications, producing bumps in the plant output in the wake of controller transfer. An examination of this phenomenon reveals that the applications in question are characterized by a significant mismatch, further referred to as controller uncertainty, between the dynamics of the implemented controllers and their models used in the transfer operator computation. To address this problem, while retaining the convenience of the Turner and Walker design, a novel state/output feedback bumpless transfer topology is introduced that employs the nominal state of the offline controller and, through the use of an additional controller/model mismatch compensator, also the offline controller output. A corresponding steady-state bumpless transfer design procedure along with the supporting theory is developed for a large class of systems. Due to these features, it is demonstrated to solve a long-standing problem of high-quality steady-state bumpless transfer from the industry standard low-order nonlinear multiloop PID-based controllers to the modern multiinput-multioutput (MIMO) robust controllers in the megawatt/throttle pressure control of a typical coal-fired boiler/turbine unit.

Zheng, K.; Lee, A.H.; Bentsman, J.; Taft, C.W. [University of Illinois, Urbana, IL (United States)

2006-01-15T23:59:59.000Z

107

Investigation and design of a secure, transportable fluoride-salt-cooled high-temperature reactor (TFHR) for isolated locations  

E-Print Network [OSTI]

In this work we describe a preliminary design for a transportable fluoride salt cooled high temperature reactor (TFHR) intended for use as a variable output heat and electricity source for off-grid locations. The goals of ...

Macdonald, Ruaridh (Ruaridh R.)

2014-01-01T23:59:59.000Z

108

Computability in Anonymous Networks: Revocable vs. Irrecovable Outputs  

E-Print Network [OSTI]

Computability in Anonymous Networks: Revocable vs. Irrecovable Outputs Yuval Emek1 , Jochen Seidel2, and leader election. 1 Introduction We study computability in networks, referred to hereafter as distributed

109

Development of Regional Wind Resource and Wind Plant Output Datasets...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

50-47676 March 2010 Development of Regional Wind Resource and Wind Plant Output Datasets Final Subcontract Report 15 October 2007 - 15 March 2009 3TIER Seattle, Washington National...

110

The Effect of Signal Quality on Six Cardiac Output Estimators  

E-Print Network [OSTI]

The effect of signal quality on the accuracy of cardiac output (CO) estimation from arterial blood pressure (ABP) was evaluated using data from the MIMIC II database. Thermodilution CO (TCO) was the gold standard. A total ...

Mark, Roger Greenwood

111

Corticospinal Output to Hindlimb Muscles in the Primate  

E-Print Network [OSTI]

The overall goal of this study was to investigate the properties of corticospinal output to a wide range of hindlimb muscles in the primate and to map the representation of individual muscles in hindlimb motor cortex. ...

Hudson, Heather M

2011-05-31T23:59:59.000Z

112

Grid adaptation for functional outputs of compressible flow simulations  

E-Print Network [OSTI]

An error correction and grid adaptive method is presented for improving the accuracy of functional outputs of compressible flow simulations. The procedure is based on an adjoint formulation in which the estimated error in ...

Venditti, David Anthony, 1973-

2002-01-01T23:59:59.000Z

113

Spring loaded locator pin assembly  

DOE Patents [OSTI]

This invention deals with spring loaded locator pins. Locator pins are sometimes referred to as captured pins. This is a mechanism which locks two items together with the pin that is spring loaded so that it drops into a locator hole on the work piece.

Groll, Todd A. (Idaho Falls, ID); White, James P. (Pocatelo, ID)

1998-01-01T23:59:59.000Z

114

Spring loaded locator pin assembly  

DOE Patents [OSTI]

This invention deals with spring loaded locator pins. Locator pins are sometimes referred to as captured pins. This is a mechanism which locks two items together with the pin that is spring loaded so that it drops into a locator hole on the work piece. 5 figs.

Groll, T.A.; White, J.P.

1998-03-03T23:59:59.000Z

115

Determining Optimal Locations for New Wind Energy Development in Iowa.  

E-Print Network [OSTI]

??The purpose of this research is to generate the most accurate model possible for predicting locations most suitable for new wind energy development using a (more)

Mann, David

2011-01-01T23:59:59.000Z

116

Entrance Maze Locations  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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),Feet) Year Jan Feb Mar Apr MayAtmospheric Optical Depth7-1D: Vegetation ProposedUsing Zirconia NanoparticlesSmartAffects the FutureEnrico Rossi College2005ModelMaze

117

The world of quantum noise and the fundamental output process  

E-Print Network [OSTI]

A stationary theory of quantum stochastic processes of second order is outlined. It includes KMS processes in wide sense like the equilibrium finite temperature quantum noise given by the Planck's spectral formula. It is shown that for each stationary noise there exists a natural output process output process which is identical to the noise in the infinite temperature limit, and flipping with the noise if the time is reversed at finite temperature. A canonical Hilbert space representation of the quantum noise and the fundamental output process is established and a decomposition of their spectra is found. A brief explanation of quantum stochastic integration with respect to the input-output processes is given using only correlation functions. This provides a mathematical foundation for linear stationary filtering transformations of quantum stochastic processes. It is proved that the colored quantum stationary noise and its time-reversed version can be obtained in the second order theory by a linear nonadapted filtering of the standard vacuum noise uniquely defined by the canonical creation and annihilation operators on the spectrum of the input-output pair.

V. P. Belavkin; O. Hirota; R. Hudson

2005-10-04T23:59:59.000Z

118

Microwave generated electrodeless lamp for producing bright output  

SciTech Connect (OSTI)

A microwave generated electrodeless light source for producing a bright output comprising a lamp structure including a microwave chamber and a plasma medium-containing lamp envelope having a maximum dimension which is substantially less than a wavelength disposed therein. To provide the desired radiation output the interior of the chamber is coated with a UV-reflective material and the chamber has an opening for allowing UV radiation to exit, which is covered with a metallic mesh. The chamber is arranged to be near-resonant at a single wavelength, and the lamp envelope has a fill including mercury at an operating pressure of 1-2 atmospheres, while a power density of at least 250-300 (watts/cm/sup 3/) is coupled to the envelope to result in a relatively high deep UV output at a relatively high brightness.

Wood, Ch. H.; Ury, M. G.

1985-03-26T23:59:59.000Z

119

Self-consistent input-output formulation of quantum feedback  

SciTech Connect (OSTI)

A simple method of analyzing quantum feedback circuits is presented. The classical analysis of feedback circuits can be generalized to apply to quantum systems by mapping the field operators of various outputs to other inputs via the standard input-output formalism. Unfortunately, this has led to unphysical results such as the violation of the Heisenberg uncertainty principle for in-loop fields. This paper shows that this general approach can be redeemed by ensuring a self-consistently Hermitian Hamiltonian. The calculations are based on a noncommutative calculus of operator derivatives. A full description of several examples of quantum linear and nonlinear feedback for optical systems is presented.

Yanagisawa, M. [Department of Engineering, The Australian National University, Canberra, ACT 0200 (Australia); Hope, J. J. [Department of Quantum Science, The Australian National University, Canberra, ACT 0200 (Australia)

2010-12-15T23:59:59.000Z

120

Output power characteristics and performance of TOPAZ II Thermionic Fuel Element No. 24  

SciTech Connect (OSTI)

A final report on the output power characteristics and capabilities of single cell TOPAZ II Thermionic Fuel Element (TFE) No. 24 is presented. Thermal power tests were conducted for over 3000 hours to investigate converter performance under normal and adverse operating conditions. Experiments conducted include low power testing, high power testing, air introduction to the interelectrode gap, collector temperature optimization, thermal modeling, and output power characteristic measurements. During testing, no unexpected degradation in converter performance was observed. The TFE has been removed from the test stand and returned to Scientific Industrial Association {open_quote}{open_quote}LUCH{close_quote}{close_quote} for materials analysis and report. This research was conducted at the Thermionic System Evaluation Test (TSET) Facility at the New Mexico Engineering Research Institute (NMERI) as a part of the Topaz International Program (TIP) by the Air Force Phillips Laboratory (PL). {copyright} {ital 1996 American Institute of Physics.}

Luchau, D.W.; Bruns, D.R. [Team Specialty Services, Inc., TOPAZ International Program, 901 University Blvd., SE, Albuquerque, New Mexico 87106 (United States); Izhvanov, O.; Androsov, V. [JV INERTEK, Scientific Industrial Association ``Luch``, 24 Zheleznodorozhnaya, Podolsk, (Russia) 142100

1996-03-01T23:59:59.000Z

Note: This page contains sample records for the topic "model output location" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


121

Development of a 402.5 MHz 140 kW Inductive Output Tube  

SciTech Connect (OSTI)

This report contains the results of Phase I of an SBIR to develop a Pulsed Inductive Output Tube (IOT) with 140 kW at 400 MHz for powering H-proton beams. A number of sources, including single beam and multiple beam klystrons, can provide this power, but the IOT provides higher efficiency. Efficiencies exceeding 70% are routinely achieved. The gain is typically limited to approximately 24 dB; however, the availability of highly efficient, solid state drivers reduces the significance of this limitation, particularly at lower frequencies. This program initially focused on developing a 402 MHz IOT; however, the DOE requirement for this device was terminated during the program. The SBIR effort was refocused on improving the IOT design codes to more accurately simulate the time dependent behavior of the input cavity, electron gun, output cavity, and collector. Significant improvement was achieved in modeling capability and simulation accuracy.

R. Lawrence Ives; Michael Read, Robert Jackson

2012-05-09T23:59:59.000Z

122

Convergent relaxations of polynomial matrix inequalities and static output feedback  

E-Print Network [OSTI]

(LMI) relaxations to solve non-convex polynomial matrix in- equality (PMI) optimization problems minimizers that satisfy the PMI. The approach is successfully applied to PMIs arising from static output- mulated as polynomial matrix inequality (PMI) optimization problems in the controller parameters

Henrion, Didier

123

Output-Sensitive Algorithms for Tukey Depth and Related Problems  

E-Print Network [OSTI]

Output-Sensitive Algorithms for Tukey Depth and Related Problems David Bremner University of New de Bruxelles Pat Morin Carleton University Abstract The Tukey depth (Tukey 1975) of a point p halfspace that contains p. Algorithms for computing the Tukey depth of a point in various dimensions

Morin, Pat

124

TRICOLOR LIGHT EMITTING DIODE DOT MATRIX DISPLAY SYSTEM WITHAUDIO OUTPUT  

E-Print Network [OSTI]

1 TRICOLOR LIGHT EMITTING DIODE DOT MATRIX DISPLAY SYSTEM WITHAUDIO OUTPUT Grantham Pang, Chi emitting diodes; tricolor display; audio communication. I. Introduction This paper relates to a tricolor broadcasting through the visible light rays transmitted by the display panel or assembly. Keywords: light

Pang, Grantham

125

Soft-Input Soft-Output Sphere Decoding Christoph Studer  

E-Print Network [OSTI]

Soft-Input Soft-Output Sphere Decoding Christoph Studer Integrated Systems Laboratory ETH Zurich Laboratory ETH Zurich, 8092 Zurich, Switzerland Email: boelcskei@nari.ee.ethz.ch Abstract--Soft-input soft, 8092 Zurich, Switzerland Email: studer@iis.ee.ethz.ch Helmut Bölcskei Communication Technology

126

The effects of output transformers on distortion in audio amplifiers  

E-Print Network [OSTI]

Introduction ~. . . . . . . . , . . . . . . ~. . . . . 7 Frequency Discrimination. . . . . . . . . . . . . . . . 9 Harmonic Distortion. ~ ~. . . . ~ 21 Distortion by the Intermodulationmethod. . . . . . . . 47 Comparison of Harmonic and Intermodulation... current in the primary as a function of frequency . 19 Output voltage of transformer 3 without direct current in the primary as a function of frequency 20 Block diagram for measuring distortion by the harmonic method 26 Per cent harmonic distortion...

Lanier, Ross Edwin

1949-01-01T23:59:59.000Z

127

The continuity of the output entropy of positive maps  

SciTech Connect (OSTI)

Global and local continuity conditions for the output von Neumann entropy for positive maps between Banach spaces of trace-class operators in separable Hilbert spaces are obtained. Special attention is paid to completely positive maps: infinite dimensional quantum channels and operations. It is shown that as a result of some specific properties of the von Neumann entropy (as a function on the set of density operators) several results on the output entropy of positive maps can be obtained, which cannot be derived from the general properties of entropy type functions. In particular, it is proved that global continuity of the output entropy of a positive map follows from its finiteness. A characterization of positive linear maps preserving continuity of the entropy (in the following sense: continuity of the entropy on an arbitrary subset of input operators implies continuity of the output entropy on this subset) is obtained. A connection between the local continuity properties of two completely positive complementary maps is considered. Bibliography: 21 titles.

Shirokov, Maxim E [Steklov Mathematical Institute, Russian Academy of Sciences, Moscow (Russian Federation)

2011-10-31T23:59:59.000Z

128

Maximizing output from oil reservoirs without water breakthrough  

E-Print Network [OSTI]

Maximizing output from oil reservoirs without water breakthrough S.K. Lucas School of Mathematics, revised May 2003, published 45(3), 2004, 401­422 Abstract Often in oil reservoirs a layer of water lies, for example, Muskat [8], Bear [1]). When oil is removed from the reservoir by an oil well, it will generate

Lucas, Stephen

129

Mobile Alternative Fueling Station Locator  

SciTech Connect (OSTI)

The Department of Energy's Alternative Fueling Station Locator is available on-the-go via cell phones, BlackBerrys, or other personal handheld devices. The mobile locator allows users to find the five closest biodiesel, electricity, E85, hydrogen, natural gas, and propane fueling sites using Google technology.

Not Available

2009-04-01T23:59:59.000Z

130

Model Development Development of a system emulating the global carbon cycle in Earth system models  

E-Print Network [OSTI]

developed a loosely coupled model (LCM) which can represent the outputs of a GCMbased Earth system model

K. Tachiiri; J. C. Hargreaves; J. D. Annan; A. Oka; A. Abe-ouchi; M. Kawamiya

2010-01-01T23:59:59.000Z

131

Weak values and weak coupling maximizing the output of weak measurements  

SciTech Connect (OSTI)

In a weak measurement, the average output ?o? of a probe that measures an observable A{sup -hat} of a quantum system undergoing both a preparation in a state ?{sub i} and a postselection in a state E{sub f} is, to a good approximation, a function of the weak value A{sub w}=Tr[E{sub f}A{sup -hat} ?{sub i}]/Tr[E{sub f}?{sub i}], a complex number. For a fixed coupling ?, when the overlap Tr[E{sub f}?{sub i}] is very small, A{sub w} diverges, but ?o? stays finite, often tending to zero for symmetry reasons. This paper answers the questions: what is the weak value that maximizes the output for a fixed coupling? What is the coupling that maximizes the output for a fixed weak value? We derive equations for the optimal values of A{sub w} and ?, and provide the solutions. The results are independent of the dimensionality of the system, and they apply to a probe having a Hilbert space of arbitrary dimension. Using the SchrdingerRobertson uncertainty relation, we demonstrate that, in an important case, the amplification ?o? cannot exceed the initial uncertainty ?{sub o} in the observable o{sup -hat}, we provide an upper limit for the more general case, and a strategy to obtain ?o???{sub o}. - Highlights: We have provided a general framework to find the extremal values of a weak measurement. We have derived the location of the extremal values in terms of preparation and postselection. We have devised a maximization strategy going beyond the limit of the SchrdingerRobertson relation.

Di Lorenzo, Antonio, E-mail: dilorenzo.antonio@gmail.com

2014-06-15T23:59:59.000Z

132

aid maximum output: Topics by E-print Network  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

at a given geographic location. Taking the solar irradiation levels, the ambient temperature, and the Sun's position angles as inputs, a multilayer feed-forward neural network...

133

Optical device with conical input and output prism faces  

DOE Patents [OSTI]

A device for radially translating radiation in which a right circular cylinder is provided at each end thereof with conical prism faces. The faces are oppositely extending and the device may be severed in the middle and separated to allow access to the central part of the beam. Radiation entering the input end of the device is radially translated such that radiation entering the input end at the perimeter is concentrated toward the output central axis and radiation at the input central axis is dispersed toward the output perimeter. Devices are disclosed for compressing beam energy to enhance drilling techniques, for beam manipulation of optical spatial frequencies in the Fourier plane and for simplification of dark field and color contrast microscopy. Both refracting and reflecting devices are disclosed.

Brunsden, Barry S. (Chicago, IL)

1981-01-01T23:59:59.000Z

134

A CMOS contact imager for locating individual Honghao Ji, David Sander, Alfred Haas, Pamela A. Abshire  

E-Print Network [OSTI]

to the background illumination. The imager is capable of locating dark objects in a bright background or bright objects in a dark background. The loca- tions of recognized cells are generated as outputs to alleviate of intracel- lular processes, drug development, medical diagnostics, and the development of cell-based sensors

Maryland at College Park, University of

135

Reliable Gas Turbine Output: Attaining Temperature Independent Performance  

E-Print Network [OSTI]

RELIABLE GAS TURBINE OUTPUT; ATTAINING TEMPERATURE INDEPENDENT PERFORMANCE James E. Neeley, P.E. Power Plant Engineer Public Utility Commission of Texas Austin, Texas ABSTRACT Improvements in gas turbine efficiency, coupled... with dropping gas prices, has made gas turbines a popular choice of utilities to supply peaking as well as base load power in the form of combined cycle power plants. Today, because of the gas turbine's compactness, low maintenance, and high levels...

Neeley, J. E.; Patton, S.; Holder, F.

136

Development of output user interface software to support analysis  

SciTech Connect (OSTI)

Data processing software packages such as VSOP and MCNPX are softwares that has been scientifically proven and complete. The result of VSOP and MCNPX are huge and complex text files. In the analyze process, user need additional processing like Microsoft Excel to show informative result. This research develop an user interface software for output of VSOP and MCNPX. VSOP program output is used to support neutronic analysis and MCNPX program output is used to support burn-up analysis. Software development using iterative development methods which allow for revision and addition of features according to user needs. Processing time with this software 500 times faster than with conventional methods using Microsoft Excel. PYTHON is used as a programming language, because Python is available for all major operating systems: Windows, Linux/Unix, OS/2, Mac, Amiga, among others. Values that support neutronic analysis are k-eff, burn-up and mass Pu{sup 239} and Pu{sup 241}. Burn-up analysis used the mass inventory values of actinide (Thorium, Plutonium, Neptunium and Uranium). Values are visualized in graphical shape to support analysis.

Wahanani, Nursinta Adi, E-mail: sintaadi@batan.go.id; Natsir, Khairina, E-mail: sintaadi@batan.go.id; Hartini, Entin, E-mail: sintaadi@batan.go.id [Center for Development of Nuclear Informatics - National Nuclear Energy Agency, PUSPIPTEK, Serpong, Tangerang, Banten (Indonesia)

2014-09-30T23:59:59.000Z

137

Location-aware active signage  

E-Print Network [OSTI]

Three-dimensional route maps, which depict a path from one location to another, can be powerful tools for visualizing and communicating directions. This thesis presents a client-server architecture for generating and ...

Nichols, Patrick James, 1981-

2004-01-01T23:59:59.000Z

138

State-space model identification and feedback control of unsteady aerodynamic forces  

E-Print Network [OSTI]

Unsteady aerodynamic models are necessary to accurately simulate forces and develop feedback controllers for wings in agile motion; however, these models are often high dimensional or incompatible with modern control techniques. Recently, reduced-order unsteady aerodynamic models have been developed for a pitching and plunging airfoil by linearizing the discretized Navier-Stokes equation with lift-force output. In this work, we extend these reduced-order models to include multiple inputs (pitch, plunge, and surge) and explicit parameterization by the pitch-axis location, inspired by Theodorsen's model. Next, we investigate the na\\"{\\i}ve application of system identification techniques to input--output data and the resulting pitfalls, such as unstable or inaccurate models. Finally, robust feedback controllers are constructed based on these low-dimensional state-space models for simulations of a rigid flat plate at Reynolds number 100. Various controllers are implemented for models linearized at base angles of ...

Brunton, Steven L; Rowley, Clarence W

2014-01-01T23:59:59.000Z

139

WORKING PAPER N 2009 -11 Regulatory policy and the location  

E-Print Network [OSTI]

Pamina Koenig Megan MacGarvie JEL Codes: F23, I18 Keywords: Pharmaceutical industry, location choices: pharmaceutical industry, location choices, price regulations, discrete choice model This paper was prepared plants. The pharmaceutical industry is one example of this type of industry. The pharmaceutical industry

Paris-Sud XI, Université de

140

Predicting Debris-Slide Locations in Northwestern California1  

E-Print Network [OSTI]

Predicting Debris-Slide Locations in Northwestern California1 Mark E. Reid,2 Stephen D. Ellen,3 tested four topographic models for predicting locations of debris-slide sources: 1) slope; 2) proximity to stream; 3) SHALSTAB with "standard" parameters; and 4) debris-slide-prone landforms, which delineates

Standiford, Richard B.

Note: This page contains sample records for the topic "model output location" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


141

Synchronized sampling improves fault location  

SciTech Connect (OSTI)

Transmission line faults must be located accurately to allow maintenance crews to arrive at the scene and repair the faulted section as soon as possible. Rugged terrain and geographical layout cause some sections of power transmission lines to be difficult to reach. In the past, a variety of fault location algorithms were introduced as either an add-on feature in protective relays or stand-alone implementation in fault locators. In both cases, the measurements of current and voltages were taken at one terminal of a transmission line only. Under such conditions, it may become difficult to determine the fault location accurately, since data from other transmission line ends are required for more precise computations. In the absence of data from the other end, existing algorithms have accuracy problems under several circumstances, such as varying switching and loading conditions, fault infeed from the other end, and random value of fault resistance. Most of the one-end algorithms were based on estimation of voltage and current phasors. The need to estimate phasors introduces additional difficulty in high-speed tripping situations where the algorithms may not be fast enough in determining fault location accurately before the current signals disappear due to the relay operation and breaker opening. This article introduces a unique concept of high-speed fault location that can be implemented either as a simple add-on to the digital fault recorders (DFRs) or as a stand-alone new relaying function. This advanced concept is based on the use of voltage and current samples that are synchronously taken at both ends of a transmission line. This sampling technique can be made readily available in some new DFR designs incorporating receivers for accurate sampling clock synchronization using the satellite Global Positioning System (GPS).

Kezunovic, M. [Texas A and M Univ., College Station, TX (United States)] [Texas A and M Univ., College Station, TX (United States); Perunicic, B. [Lamar Univ., Beaumont, TX (United States)] [Lamar Univ., Beaumont, TX (United States)

1995-04-01T23:59:59.000Z

142

NCPART: management of ICEMDDN output for numerical control users  

SciTech Connect (OSTI)

NCPART is a procedure developed by the Numerical Control Department at Bendix Kansas City Division to handle the entry to and exit from ICEMDDN, and process all of the local files output by ICEMDDN. The NCPART procedure is menu driven, and provides automatic access to ICEMDDN and any files necessary to process information with ICEM for numerical Control users. Basically, the procedure handles all of the ICEMDDN operations that involve operating system commands, and frees the NC programmer to concentrate on his/her work as a programmer.

Rossini, B.F.

1986-04-01T23:59:59.000Z

143

Output-Based Error Estimation and Adaptation for Uncertainty Quantification  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLasDelivered‰PNG IHDR€ÍSolar Energy SystemsFebruary 7-8,March 8,8)Normal 27 1 54InOutput-Based

144

Location logistics of industrial facilities  

E-Print Network [OSTI]

of company intent1ons is not made at the correct time and in the correct manner. 6. Recommend Best Areas for Further Invest1 ations. Once the on-site evaluations have been completed, the 11st of possibilities is reduced still further and only the best... location and site selection. This data was gathered through library research, atten- dance of various industr1al development conferences, sol1citation of mater1als from individuals currently involved with industrial facil1ties location, and various...

Hammack, William Eugene

1981-01-01T23:59:59.000Z

145

Method and system for managing an electrical output of a turbogenerator  

DOE Patents [OSTI]

The system and method manages an electrical output of a turbogenerator in accordance with multiple modes. In a first mode, a direct current (DC) bus receives power from a turbogenerator output via a rectifier where turbogenerator revolutions per unit time (e.g., revolutions per minute (RPM)) or an electrical output level of a turbogenerator output meet or exceed a minimum threshold. In a second mode, if the turbogenerator revolutions per unit time or electrical output level of a turbogenerator output are less than the minimum threshold, the electric drive motor or a generator mechanically powered by the engine provides electrical energy to the direct current bus.

Stahlhut, Ronnie Dean (Bettendorf, IA); Vuk, Carl Thomas (Denver, IA)

2010-08-24T23:59:59.000Z

146

Boston, Massachusetts Location: Boston, MA  

E-Print Network [OSTI]

-recovery ventilation and water-source heat pumps Each unit has fresh air ducted independently. Each residence is warmed by a heat pump that taps the Trigen Energy Corporation steam lines that run underneath the street. #12;WallsBoston, Massachusetts #12;Location: Boston, MA Building type(s): Multi-unit residential, Retail 350

Prevedouros, Panos D.

147

Building Address Locations -Assumes entire  

E-Print Network [OSTI]

Building Address Locations - Assumes entire building unless noted Designation Submit through* 560, 4 BU Crosstown Center 801 Massachusetts Ave Floor 1, 2 BMC BCD Building 800 Harrison Avenue BCD BMC Biosquare III 670 Albany Floors 2, 3, 6, 7 BMC Biosquare III 670 Albany Floors 1, 4, 5, 8 BU Building

Guenther, Frank

148

Enhancing e-waste estimates: Improving data quality by multivariate InputOutput Analysis  

SciTech Connect (OSTI)

Highlights: A multivariate InputOutput Analysis method for e-waste estimates is proposed. Applying multivariate analysis to consolidate data can enhance e-waste estimates. We examine the influence of model selection and data quality on e-waste estimates. Datasets of all e-waste related variables in a Dutch case study have been provided. Accurate modeling of time-variant lifespan distributions is critical for estimate. - Abstract: Waste electrical and electronic equipment (or e-waste) is one of the fastest growing waste streams, which encompasses a wide and increasing spectrum of products. Accurate estimation of e-waste generation is difficult, mainly due to lack of high quality data referred to market and socio-economic dynamics. This paper addresses how to enhance e-waste estimates by providing techniques to increase data quality. An advanced, flexible and multivariate InputOutput Analysis (IOA) method is proposed. It links all three pillars in IOA (product sales, stock and lifespan profiles) to construct mathematical relationships between various data points. By applying this method, the data consolidation steps can generate more accurate time-series datasets from available data pool. This can consequently increase the reliability of e-waste estimates compared to the approach without data processing. A case study in the Netherlands is used to apply the advanced IOA model. As a result, for the first time ever, complete datasets of all three variables for estimating all types of e-waste have been obtained. The result of this study also demonstrates significant disparity between various estimation models, arising from the use of data under different conditions. It shows the importance of applying multivariate approach and multiple sources to improve data quality for modelling, specifically using appropriate time-varying lifespan parameters. Following the case study, a roadmap with a procedural guideline is provided to enhance e-waste estimation studies.

Wang, Feng, E-mail: fwang@unu.edu [Institute for Sustainability and Peace, United Nations University, Hermann-Ehler-Str. 10, 53113 Bonn (Germany); Design for Sustainability Lab, Faculty of Industrial Design Engineering, Delft University of Technology, Landbergstraat 15, 2628CE Delft (Netherlands); Huisman, Jaco [Institute for Sustainability and Peace, United Nations University, Hermann-Ehler-Str. 10, 53113 Bonn (Germany); Design for Sustainability Lab, Faculty of Industrial Design Engineering, Delft University of Technology, Landbergstraat 15, 2628CE Delft (Netherlands); Stevels, Ab [Design for Sustainability Lab, Faculty of Industrial Design Engineering, Delft University of Technology, Landbergstraat 15, 2628CE Delft (Netherlands); Bald, Cornelis Peter [Institute for Sustainability and Peace, United Nations University, Hermann-Ehler-Str. 10, 53113 Bonn (Germany); Statistics Netherlands, Henri Faasdreef 312, 2492 JP Den Haag (Netherlands)

2013-11-15T23:59:59.000Z

149

A Wavelet-Based Variability Model (WVM) for Solar PV Power Plants  

E-Print Network [OSTI]

Model (WVM) for Solar PV Power Plants Matthew Lave, Jansolar photovoltaic (PV) power plant output given a singleproduce a simulated power plant output. The WVM is validated

Lave, Matthew; Kleissl, Jan; Stein, Joshua S

2013-01-01T23:59:59.000Z

150

Design of a 3.3 V analog video line driver with controlled output impedance  

E-Print Network [OSTI]

impedance of the line. The main requirements for design are high output swing, high linearity, matched impedance to the line and power efficiency. These requirements are addressed by a class AB amplifier whose output impedance can be controlled through...

Ramachandran, Narayan Prasad

2004-09-30T23:59:59.000Z

151

Predicting the Power Output of Distributed Renewable Energy Resources within a Broad Geographical Region  

E-Print Network [OSTI]

Predicting the Power Output of Distributed Renewable Energy Resources within a Broad Geographical potentially dis- tributed renewable energy resources (su years, estimating the power output of in- herently intermittent and potentially distributed renewable

Chalkiadakis, Georgios

152

Spatial Interference Mitigation for Multiple Input Multiple Output Ad Hoc Networks: MISO Gains  

E-Print Network [OSTI]

Spatial Interference Mitigation for Multiple Input Multiple Output Ad Hoc Networks: MISO Gains beamforming for a multiple input single output (MISO) ad hoc network to increase the density of successful

Paris-Sud XI, Universit de

153

Regulatory Reform to Promote Clean Energy: The Potential of Output-Based Emissions Standards  

SciTech Connect (OSTI)

Barriers to industrial energy-efficient technologies hinder their use. A number of EPA analyses and industrial experts have found that the utilization of input-based emissions standards (measured in parts-per-million or pounds/MMBtu) in the Clean Air Act creates a regulatory barrier to the installation and deployment of technologies that emit fewer criteria pollutants and use energy more efficiently. Changing emission management strategies to an output-based emissions standard (measured in tons of pollutant emitted) is a way to ameliorate some of these barriers. Combined heat and power (CHP) is one of the key technologies that would see increased industrial application if the emissions standards were modified. Many states have made this change since the EPA first approved it in 2000, although direction from the Federal government could speed implementation modifications. To analyze the national impact of accelerated state adoption of output-based standards on CHP technologies, this paper uses detailed National Energy Modeling System (NEMS) and spreadsheet analysis illustrating two phased-in adoption scenarios for output-based emissions standards in the industrial sector. Benefit/cost metrics are calculated from a private and public perspective, and also a social perspective that considers the criteria and carbon air pollution emissions. These scenarios are compared to the reference case of AEO 2010 and are quite favorable, with a social benefit-cost ratio of 16.0 for a five-year phase-in scenario. In addition, the appropriateness of the Federal role, applicability, technology readiness, and administrative feasibility are discussed.

Cox, Matthew [Georgia Institute of Technology] [Georgia Institute of Technology; Brown, Dr. Marilyn Ann [Georgia Institute of Technology] [Georgia Institute of Technology; Jackson, Roderick K [ORNL] [ORNL

2011-01-01T23:59:59.000Z

154

The electrical and lumen output characteristics of an RF lamp  

SciTech Connect (OSTI)

Low pressure rf discharges have been studied for over a century. Their first practical application for lighting was proposed by Tesla in 1891. Since then hundreds of patents have been published attempting to implement rf lighting. However, progress in understanding rf discharge phenomena (mostly driven by plasma processing needs) and dramatic improvement in the performance/cost ratio of rf power sources have recently opened the door for development of rf light sources. Today commercial inductively coupled electrodeless lamps are offered by Matsuhita, Philips and GE. In this work the authors present measurements of the electrical characteristics and lumen output from a 2.65 MHz driven inductively coupled light source. Measurements were made on a spherical lamp of 3.125 inch diameter with a re-entrant cavity that houses a cylindrical ferrite core around which is wrapped the primary coil.

Alexandrovich, B.M.; Godyak, V.A.; Piejak, R.B. [Osram Sylvania Inc., Beverly, MA (United States)

1996-12-31T23:59:59.000Z

155

Quantum teleportation scheme by selecting one of multiple output ports  

E-Print Network [OSTI]

The scheme of quantum teleportation, where Bob has multiple (N) output ports and obtains the teleported state by simply selecting one of the N ports, is thoroughly studied. We consider both deterministic version and probabilistic version of the teleportation scheme aiming to teleport an unknown state of a qubit. Moreover, we consider two cases for each version: (i) the state employed for the teleportation is fixed to a maximally entangled state, and (ii) the state is also optimized as well as Alice's measurement. We analytically determine the optimal protocols for all the four cases, and show the corresponding optimal fidelity or optimal success probability. All these protocols can achieve the perfect teleportation in the asymptotic limit of $N\\to\\infty$. The entanglement properties of the teleportation scheme are also discussed.

Satoshi Ishizaka; Tohya Hiroshima

2009-04-06T23:59:59.000Z

156

GAMS program used to estimate capacity output using a distance function with both desirable and undesirable outputs, and weak disposability for the undesirable outputs.  

E-Print Network [OSTI]

." VIMS Marine resource Report N. 2007-6. August 2007. Author: John B. Walden NMFS/NEFSC 166 Water St(obs,var) variuable input utilization rate weight(obs) weights ; POSITIVE Variable weight, lambda; EQUATIONS CONSTR1 /dd_res_crs.txt/ MODEL CAP /ALL/; /*Use all the equations. Alternatively, the model could be solved

157

Dosimetric characterization and output verification for conical brachytherapy surface applicators. Part I. Electronic brachytherapy source  

SciTech Connect (OSTI)

Purpose: Historically, treatment of malignant surface lesions has been achieved with linear accelerator based electron beams or superficial x-ray beams. Recent developments in the field of brachytherapy now allow for the treatment of surface lesions with specialized conical applicators placed directly on the lesion. Applicators are available for use with high dose rate (HDR){sup 192}Ir sources, as well as electronic brachytherapy sources. Part I of this paper will discuss the applicators used with electronic brachytherapy sources; Part II will discuss those used with HDR {sup 192}Ir sources. Although the use of these applicators has gained in popularity, the dosimetric characteristics including depth dose and surface dose distributions have not been independently verified. Additionally, there is no recognized method of output verification for quality assurance procedures with applicators like these. Existing dosimetry protocols available from the AAPM bookend the cross-over characteristics of a traditional brachytherapy source (as described by Task Group 43) being implemented as a low-energy superficial x-ray beam (as described by Task Group 61) as observed with the surface applicators of interest. Methods: This work aims to create a cohesive method of output verification that can be used to determine the dose at the treatment surface as part of a quality assurance/commissioning process for surface applicators used with HDR electronic brachytherapy sources (Part I) and{sup 192}Ir sources (Part II). Air-kerma rate measurements for the electronic brachytherapy sources were completed with an Attix Free-Air Chamber, as well as several models of small-volume ionization chambers to obtain an air-kerma rate at the treatment surface for each applicator. Correction factors were calculated using MCNP5 and EGSnrc Monte Carlo codes in order to determine an applicator-specific absorbed dose to water at the treatment surface from the measured air-kerma rate. Additionally, relative dose measurements of the surface dose distributions and characteristic depth dose curves were completed in-phantom. Results: Theoretical dose distributions and depth dose curves were generated for each applicator and agreed well with the measured values. A method of output verification was created that allows users to determine the applicator-specific dose to water at the treatment surface based on a measured air-kerma rate. Conclusions: The novel output verification methods described in this work will reduce uncertainties in dose delivery for treatments with these kinds of surface applicators, ultimately improving patient care.

Fulkerson, Regina K., E-mail: rmkenned@gmail.com; Micka, John A.; DeWerd, Larry A. [Department of Medical Physics, University of WisconsinMadison, Madison, Wisconsin 53705 (United States)] [Department of Medical Physics, University of WisconsinMadison, Madison, Wisconsin 53705 (United States)

2014-02-15T23:59:59.000Z

158

A H-infinity Fault Detection and Diagnosis Scheme for Discrete Nonlinear System Using Output Probability Density Estimation  

SciTech Connect (OSTI)

In this paper, a H-infinity fault detection and diagnosis (FDD) scheme for a class of discrete nonlinear system fault using output probability density estimation is presented. Unlike classical FDD problems, the measured output of the system is viewed as a stochastic process and its square root probability density function (PDF) is modeled with B-spline functions, which leads to a deterministic space-time dynamic model including nonlinearities, uncertainties. A weighting mean value is given as an integral function of the square root PDF along space direction, which leads a function only about time and can be used to construct residual signal. Thus, the classical nonlinear filter approach can be used to detect and diagnose the fault in system. A feasible detection criterion is obtained at first, and a new H-infinity adaptive fault diagnosis algorithm is further investigated to estimate the fault. Simulation example is given to demonstrate the effectiveness of the proposed approaches.

Zhang Yumin; Lum, Kai-Yew [Temasek Laboratories, National University of Singapore, Singapore 117508 (Singapore); Wang Qingguo [Depa. Electrical and Computer Engineering, National University of Singapore, Singapore 117576 (Singapore)

2009-03-05T23:59:59.000Z

159

Site Location of Development Act (Maine)  

Broader source: Energy.gov [DOE]

The Site Location of Development Act regulates the locations chosen for state, municipal, quasi-municipal, educational, charitable, commercial and industrial developments with respect to the...

160

Persistent Uniform Resource Locators (PURLs) | Scientific and...  

Office of Scientific and Technical Information (OSTI)

Locators (PURLs) Print page Print page PURLs (Persistent Uniform Resource Locators) are Web addresses that act as permanent identifiers in the face of a dynamic and changing Web...

Note: This page contains sample records for the topic "model output location" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


161

Energy Department Launches Alternative Fueling Station Locator...  

Broader source: Energy.gov (indexed) [DOE]

Launches Alternative Fueling Station Locator App Energy Department Launches Alternative Fueling Station Locator App November 7, 2013 - 11:16am Addthis As part of the Obama...

162

LOCATION: Johnson County Sheriff's Office  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsruc DocumentationP-SeriesFlickrinformationPostdocs &JeffIntensitySurfaceLOCATION: Johnson County

163

Ombuds Office Location & Hours  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLas Conchas recoveryLaboratorySpeeding access1 TechnicalOil inventories inOmbuds Office Location

164

Verification and Uncertainty Reduction of Amchitka Underground Nuclear Testing Models  

SciTech Connect (OSTI)

The modeling of Amchitka underground nuclear tests conducted in 2002 is verified and uncertainty in model input parameters, as well as predictions, has been reduced using newly collected data obtained by the summer 2004 field expedition of CRESP. Newly collected data that pertain to the groundwater model include magnetotelluric (MT) surveys conducted on the island to determine the subsurface salinity and porosity structure of the subsurface, and bathymetric surveys to determine the bathymetric maps of the areas offshore from the Long Shot and Cannikin Sites. Analysis and interpretation of the MT data yielded information on the location of the transition zone, and porosity profiles showing porosity values decaying with depth. These new data sets are used to verify the original model in terms of model parameters, model structure, and model output verification. In addition, by using the new data along with the existing data (chemistry and head data), the uncertainty in model input and output is decreased by conditioning on all the available data. A Markov Chain Monte Carlo (MCMC) approach is adapted for developing new input parameter distributions conditioned on prior knowledge and new data. The MCMC approach is a form of Bayesian conditioning that is constructed in such a way that it produces samples of the model parameters that eventually converge to a stationary posterior distribution. The Bayesian MCMC approach enhances probabilistic assessment. Instead of simply propagating uncertainty forward from input parameters into model predictions (i.e., traditional Monte Carlo approach), MCMC propagates uncertainty backward from data onto parameters, and then forward from parameters into predictions. Comparisons between new data and the original model, and conditioning on all available data using MCMC method, yield the following results and conclusions: (1) Model structure is verified at Long Shot and Cannikin where the high-resolution bathymetric data collected by CRESP yield profiles matching those used to construct the Long Shot and Cannikin model cross sections in 2002. (2) Distributions of model input parameters (recharge, conductivity, and recharge-conductivity ratio) used in 2002 for the three sites are verified where the new data indicate distributions with narrower ranges (smaller uncertainty) but within the range employed in the 2002 model. (3) As a conservative approach, distribution of fracture porosity used in 2002 was deliberately skewed toward lower values. New CRESP data indicate that the selected porosity range was overly conservative. In addition, the range of porosity values obtained from the analysis of the MT data is found to generally be about three orders of magnitude lower than range of values used in the 2002 model, though the values themselves are much larger from the MT data. (4) Distributions of the flow model output (head distribution, salinity distribution, groundwater fluxes) resulting from the 2002 model for the three sites are verified where the new model output after conditioning on the data lie within the range of the 2002 model output. (5) Cannikin model output at location of well UAe-1 is not fully verified where the new model results for small salinity values are not fully enclosed by the uncertainty bounds of the original model output. (6) With the new porosities developed from the analysis of MT data, radionuclides require thousands of years to reach the seafloor. No breakthrough resulted for any of the three sites within the 2000 year model timeframe, despite ignoring all retardation mechanisms (sorption, radionuclide trapping in glass, matrix diffusion, and radioactive decay). (7) The no-breakthrough results verify the original model in the sense that this result lies within the uncertainty bounds of the 2002 model expressed as + 2 {sigma}{sub Q} and - 2 {sigma}{sub Q}. The lower bound, - 2 {sigma}{sub Q}, in the 2002 model gave negative values implying that the bound is essentially zero. The current results of no-breakthrough match this lower bound. (8) Si

Ahmed Hassan; Jenny Chapman

2006-02-01T23:59:59.000Z

165

Fail safe controllable output improved version of the electromechanical battery  

DOE Patents [OSTI]

Mechanical means are provided to control the voltages induced in the windings of a generator/motor. In one embodiment, a lever is used to withdraw or insert the entire stator windings from the cavity where the rotating field exists. In another embodiment, voltage control and/or switching off of the output is achievable with a variable-coupling generator/motor. A stator is made up of two concentric layers of windings, with a larger number of turns on the inner layer of windings than the outer layer of windings. The windings are to be connected in series electrically, that is, their voltages add vectorially. The mechanical arrangement is such that one or both of the windings can be rotated with respect to the other winding about their common central axis. Another improved design for the stator assembly of electromechanical batteries provides knife switch contacts that are in electrical contact with the stator windings. The operation of this embodiment depends on the fact that an abnormally large torque will be exerted on the stator structure during any short-circuit condition. 4 figs.

Post, R.F.

1999-01-19T23:59:59.000Z

166

Output Performance and Payback Analysis of a Residential Photovoltaic System in Colorado: Preprint  

SciTech Connect (OSTI)

Cost of installation and ownership of a 9.66-kilowatt (kW) residential photovoltaic system is described, and the performance of this system over the past 3 years is shown. The system is located in Colorado at 40 degrees latitude and consists of arrays on two structures. Two arrays are installed on a detached garage, and these are each composed of 18 Kyocera 130-W modules strung in series facing south at an angle of 40 degrees above horizontal. Each 18-panel array feeds into a Xantrex/Schneider Electric 2.8-kW inverter. The other two arrays are installed on the house and face south at an angle of 30 degrees. One of these arrays has twelve 205-W Kyocera panels in series, and the other is made up of twelve 210-Kyocera panels. Each of these arrays feeds into Xantrex/Schneider Electric 3.3-kW inverters. Although there are various shading issues from trees and utility poles and lines, the overall output resembles that which is expected from PVWatts, a solar estimate program. The array cost, which was offset by rebates from the utility company and federal tax credits, was $1.17 per watt. Considering measured system performance, the estimated payback time of the system is 9 years.

Johnston, S.

2012-06-01T23:59:59.000Z

167

Updated Eastern Interconnect Wind Power Output and Forecasts for ERGIS: July 2012  

SciTech Connect (OSTI)

AWS Truepower, LLC (AWST) was retained by the National Renewable Energy Laboratory (NREL) to update wind resource, plant output, and wind power forecasts originally produced by the Eastern Wind Integration and Transmission Study (EWITS). The new data set was to incorporate AWST's updated 200-m wind speed map, additional tall towers that were not included in the original study, and new turbine power curves. Additionally, a primary objective of this new study was to employ new data synthesis techniques developed for the PJM Renewable Integration Study (PRIS) to eliminate diurnal discontinuities resulting from the assimilation of observations into mesoscale model runs. The updated data set covers the same geographic area, 10-minute time resolution, and 2004?2006 study period for the same onshore and offshore (Great Lakes and Atlantic coast) sites as the original EWITS data set.

Pennock, K.

2012-10-01T23:59:59.000Z

168

Process and Intermediate Calculations User AccessInputs Outputs  

E-Print Network [OSTI]

density, canopy base height, fuel moisture) · Weather · Fire History · Ignition History Analytic Models Behavior · DEM (Elevation, slope, aspect) · Vegetation (Fuel models, crown cover, stand height, bulk Smoke Analysis Management of Unplanned Ignitions: Each cell is evaluated using a probabilistic footprint

169

INTRODUCTION The power output of insect flight muscles is proportional to muscle  

E-Print Network [OSTI]

#12;2239 INTRODUCTION The power output of insect flight muscles is proportional to muscle polaris) to forage in suboptimal thermal conditions (Heinrich, 1993). Recently, bumble bee (Bombus

Nieh, James

170

Combining frequency and time domain approaches to systems with multiple spike train input and output  

E-Print Network [OSTI]

between neuronal spike trains. Prog Biophys Mol Biol Vapnikto systems with multiple spike train input and output D. R.Keywords Multiple spike trains Neural coding Maximum

Brillinger, D. R.; Lindsay, K. A.; Rosenberg, J. R.

2009-01-01T23:59:59.000Z

171

Automated Fault Location In Smart Distribution Systems  

E-Print Network [OSTI]

of utilizing a suitable fault location method. As distribution systems are gradually evolving into smart distribution systems, application of more accurate fault location methods based on gathered data from various Intelligent Electronic Devices (IEDs...

Lotfifard, Saeed

2012-10-19T23:59:59.000Z

172

Analysis of the AirTouch automatic vehicle location system's ability to locate moving vehicles  

E-Print Network [OSTI]

Automatic vehicle location systems are becoming more prevalent in diverse transportation applications. Their ability to locate vehicles can assist in locating emergency and public transit vehicles for better real-time dispatching as well...

Henry, Tracy Lynn

1995-01-01T23:59:59.000Z

173

Abstract--The behavior of Solar Photo-Voltaic Generation (SPVG) in the grid is defined by the way its output active and  

E-Print Network [OSTI]

its output active and reactive power are controlled; the reactive power can be controlled directly). Therefore, two basic modeling approaches are considered in the present work: constant reactive power of electricity. The Ontario Power Authority (OPA), as per the Green Energy Act [1], considers renewable energy

Cañizares, Claudio A.

174

HSPICE and WaveView Tutorial Hspice is used for circuit simulation and WaveView is used to view output waveforms.  

E-Print Network [OSTI]

NNano-E Hs Electron Sc San Fr S spice Q Mich Hamid nics & C chool of rancisco San Fra Spr Quick By be downloaded from the following website: http://ptm.asu.edu/ Click on the latest models and download 16nm PTM "hspice job aborted". In that case, please open the output file (inv.out) and search for error to see

Mahmoodi, Hamid

175

ARM: ARSCL: multiple outputs from first Clothiaux algorithms on Vaisala or Belfort ceilometers, Micropulse lidar, and MMCR  

DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

ARSCL: multiple outputs from first Clothiaux algorithms on Vaisala or Belfort ceilometers, Micropulse lidar, and MMCR

Coulter, Richard; Widener, Kevin; Bharadwaj, Nitin; Johnson, Karen; Martin, Timothy

176

PWM Inverter Output Filter Cost to Losses Trade Off and Optimal Design  

E-Print Network [OSTI]

PWM Inverter Output Filter Cost to Losses Trade Off and Optimal Design Robert J. Pasterczyk Jean--This paper describes how to design the output filter of a PWM inverter used in a Uninterruptible Power SupplyVA 3-ph. PWM inverter is taken as example. B. Design Constraints Uninterruptible Power Supply (UPS

Paris-Sud XI, Université de

177

Estimating Solar PV Output Using Modern Space/Time Geostatistics (Presentation)  

SciTech Connect (OSTI)

This presentation describes a project that uses mapping techniques to predict solar output at subhourly resolution at any spatial point, develop a methodology that is applicable to natural resources in general, and demonstrate capability of geostatistical techniques to predict the output of a potential solar plant.

Lee, S. J.; George, R.; Bush, B.

2009-04-29T23:59:59.000Z

178

Generating Isolated Outputs in a Multilevel Modular Capacitor Clamped DC-DC Converter  

E-Print Network [OSTI]

balance between the fuel cell and any energy storage inside the vehicle, and provides continuous power) for Hybrid Electric and Fuel Cell Vehicles Faisal H. Khan1 , Leon M. Tolbert2 1 Electric Power Research transformers to generate isolated ac outputs. These isolated outputs can be rectified and filtered to obtain

Tolbert, Leon M.

179

Experimental Results on Multiple-Input Single-Output (MISO) Time Reversal for UWB  

E-Print Network [OSTI]

Experimental Results on Multiple-Input Single-Output (MISO) Time Reversal for UWB Systems with multiple-input single- output (MISO) antennas over ultra-wideband (UWB) channels. In particular, temporal and spatial focusing as well as array gain are studied based on a (4 1) MISO scheme in an office environment

Qiu, Robert Caiming

180

Optimizing the Output of a Human-Powered Energy Harvesting System with Miniaturization and Integrated Control  

E-Print Network [OSTI]

1 Optimizing the Output of a Human-Powered Energy Harvesting System with Miniaturization mechanical energy from human foot-strikes and explore its configuration and control towards optimized energy output. Dielectric Elastomers (DEs) are high-energy density, soft, rubber-like material

Potkonjak, Miodrag

Note: This page contains sample records for the topic "model output location" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


181

Fine-grained Photovoltaic Output Prediction using a Bayesian Ensemble Prithwish Chakraborty1,2  

E-Print Network [OSTI]

generation is increasingly reliant on renewable power sources, e.g., solar (pho- tovoltaic or PV) and wind Increasingly, local and distributed power generation e.g., through solar (photovoltaic or PV), wind, fuel cells and intermittent in their energy output, which makes integration with the power grid challenging. PV output

Ramakrishnan, Naren

182

High-Efficiency Multiple-Output DC-DC Conversion for Low-Voltage Systems  

E-Print Network [OSTI]

This versatile power converter controller provides dual outputs at a fixed switching frequency and can regulate either output voltage or target system delay (using an external -- filter). In the voltage regulation mode, the output voltage is monitored with an analog--digital (A/D) converter, and the feedback compensation network is implemented digitally. The generation of the pulsewidth modulation (PWM) signal is done with a hybrid delay line/counter approach, which saves power and area relative to previous implementations. Power devices are included on chip to create the two independently regulated output PWM signals. The key features of this design are its low-power dissipation, reconfigurability, use of either delay or voltage feedback, and multiple outputs.

Abram P. Dancy; Rajeevan Amirtharajah; Anantha P. Chandrakasan

2000-01-01T23:59:59.000Z

183

Method for leveling the power output of an electromechanical battery as a function of speed  

DOE Patents [OSTI]

The invention is a method of leveling the power output of an electromechanical battery during its discharge, while at the same time maximizing its power output into a given load. The method employs the concept of series resonance, employing a capacitor the parameters of which are chosen optimally to achieve the desired near-flatness of power output over any chosen charged-discharged speed ratio. Capacitors are inserted in series with each phase of the windings to introduce capacitative reactances that act to compensate the inductive reactance of these windings. This compensating effect both increases the power that can be drawn from the generator before inductive voltage drops in the windings become dominant and acts to flatten the power output over a chosen speed range. The values of the capacitors are chosen so as to optimally flatten the output of the generator over the chosen speed range. 3 figs.

Post, R.F.

1999-03-16T23:59:59.000Z

184

COMMUNICATION Does the Location of a Mutation Determine the Ability  

E-Print Network [OSTI]

COMMUNICATION Does the Location of a Mutation Determine the Ability to Form Amyloid Fibrils? Marina by a domain swapping mechanism. Domain swapping is a specific means by which oligomeric proteins are formed that the mutations in our model system facilitate domain swapping as the pathway to amyloid for- mation (Figure 1(b

Regan, Lynne

185

Structural Location of Disease-associated Single-nucleotide Polymorphisms  

E-Print Network [OSTI]

Structural Location of Disease-associated Single-nucleotide Polymorphisms Nathan O. Stitziel1 , Yan-synonymous single-nucleotide polymorphism (nsSNP) of genes introduces amino acid changes to proteins, and plays reserved Keywords: single-nucleotide polymorphism; alpha shape; hidden Markov model; surface pockets

Pervouchine, Dmitri D.

186

VEHICLE USE RECORD M/Y DEPARTMENT VEHICLE LOCATION  

E-Print Network [OSTI]

VEHICLE USE RECORD M/Y DEPARTMENT VEHICLE LOCATION Date Origin/Destination Purpose Time Out Time) Accuracy of Information (b) Valid Driver's License VEHICLE # TAG # VEHICLE MAKE, MODEL, AND YEAR NOTE: Vehicle logs must be maintained for audit purposes. It is important that all of the required information

Watson, Craig A.

187

Final Report - From Measurements to Models: Cross-Comparison of Measured and Simulated Behavioral States of the Atmosphere  

SciTech Connect (OSTI)

The ARM sites and the ARM Mobile Facility (AMF) were constructed to make measurements of the atmosphere and radiation system in order to quantify deficiencies in the simulation of clouds within models and to make improvements in those models. While the measurement infrastructure of ARM is well-developed and a model parameterization testbed capability has been established, additional effort is needed to develop statistical techniques which permit the comparison of simulation output from atmospheric models with actual measurements. Our project establishes a new methodology for objectively comparing ARM measurements to the outputs of leading global climate models and reanalysis data. The quantitative basis for this comparison is provided by a statistical procedure which establishes an exhaustive set of mutually-exclusive, recurring states of the atmosphere from sets of multivariate atmospheric and cloud conditions, and then classifies multivariate measurements or simulation outputs into those states. Whether measurements and models classify the atmosphere into the same states at specific locations through time provides an unequivocal comparison result. Times and locations in both geographic and state space of model-measurement agreement and disagreement will suggest directions for the collection of additional measurements at existing sites, provide insight into the global representativeness of the current ARM sites (suggesting locations and times for use of the AMF), and provide a basis for improvement of models. Two different analyses were conducted: One, using the Parallel Climate Model, focused on an IPCC climate change scenario and clusters that characterize long-term changes in the hydrologic cycle. The other, using the GISS Model E GCM and the ARM Active Remotely Sensed Cloud Layers product, explored current climate cloud regimes in the Tropical West Pacific.

Del Genio, Anthony D; Hoffman, Forrest M; Hargrove, Jr, William W

2007-10-22T23:59:59.000Z

188

Helicopter magnetic survey conducted to locate wells  

SciTech Connect (OSTI)

A helicopter magnetic survey was conducted in August 2007 over 15.6 sq mi at the Naval Petroleum Reserve No. 3s (NPR-3) Teapot Dome Field near Casper, Wyoming. The surveys purpose was to accurately locate wells drilled there during more than 90 years of continuous oilfield operation. The survey was conducted at low altitude and with closely spaced flight lines to improve the detection of wells with weak magnetic response and to increase the resolution of closely spaced wells. The survey was in preparation for a planned CO2 flood for EOR, which requires a complete well inventory with accurate locations for all existing wells. The magnetic survey was intended to locate wells missing from the well database and to provide accurate locations for all wells. The ability of the helicopter magnetic survey to accurately locate wells was accomplished by comparing airborne well picks with well locations from an intense ground search of a small test area.

Veloski, G.A.; Hammack, R.W.; Stamp, V. (Rocky Mountain Oilfield Testing Center); Hall, R. (Rocky Mountain Oilfield Testing Center); Colina, K. (Rocky Mountain Oilfield Testing Center)

2008-07-01T23:59:59.000Z

189

Community Detection from Location-Tagged Networks  

E-Print Network [OSTI]

Many real world systems or web services can be represented as a network such as social networks and transportation networks. In the past decade, many algorithms have been developed to detect the communities in a network using connections between nodes. However in many real world networks, the locations of nodes have great influence on the community structure. For example, in a social network, more connections are established between geographically proximate users. The impact of locations on community has not been fully investigated by the research literature. In this paper, we propose a community detection method which takes locations of nodes into consideration. The goal is to detect communities with both geographic proximity and network closeness. We analyze the distribution of the distances between connected and unconnected nodes to measure the influence of location on the network structure on two real location-tagged social networks. We propose a method to determine if a location-based community detection...

Liu, Zhi

2015-01-01T23:59:59.000Z

190

Location theory and the location of industry along an interstate highway  

E-Print Network [OSTI]

to determine the significance of these locational factors among plants with different characteristics that have located in certain localities should provide pertinent information with both practical and theoretical implications. Since 1956, approximately 64... Summary of Plant Location Theory Cost Fac'tots . . . . . . . . . . . . . ~ The Importance of 'the Demand Factor Greenhut's General Theory of Plant Location and the Intangible Factor Location Factors as Revealed by Empirical Study Greenhut's Case...

Miller, James Patterson

1965-01-01T23:59:59.000Z

191

Finding the quantum thermoelectric with maximal efficiency and minimal entropy production at given power output  

E-Print Network [OSTI]

We investigate the nonlinear scattering theory for quantum systems with strong Seebeck and Peltier effects, and consider their use as heat-engines and refrigerators with finite power outputs. This article gives detailed derivations of the results summarized in Phys. Rev. Lett. 112, 130601 (2014). It shows how to use the scattering theory to find (i) the quantum thermoelectric with maximum possible power output, and (ii) the quantum thermoelectric with maximum efficiency at given power output. The latter corresponds to a minimal entropy production at that power output. These quantities are of quantum origin since they depend on system size over electronic wavelength, and so have no analogue in classical thermodynamics. The maximal efficiency coincides with Carnot efficiency at zero power output, but decreases with increasing power output. This gives a fundamental lower bound on entropy production, which means that reversibility (in the thermodynamic sense) is impossible for finite power output. The suppression of efficiency by (nonlinear) phonon and photon effects is addressed in detail; when these effects are strong, maximum efficiency coincides with maximum power. Finally, we show in particular limits (typically without magnetic fields) that relaxation within the quantum system does not allow the system to exceed the bounds derived for relaxation-free systems, however a general proof of this remains elusive.

Robert S. Whitney

2015-01-28T23:59:59.000Z

192

Finding the quantum thermoelectric with maximal efficiency and minimal entropy production at given power output  

E-Print Network [OSTI]

We investigate the nonlinear scattering theory for quantum systems with strong Seebeck and Peltier effects, and consider their use as heat-engines and refrigerators with finite power outputs. This article gives detailed derivations of the results summarized in Phys. Rev. Lett. 112, 130601 (2014). It shows how to use the scattering theory to find (i) the quantum thermoelectric with maximum possible power output, and (ii) the quantum thermoelectric with maximum efficiency at given power output. The latter corresponds to a minimal entropy production at that power output. These quantities are of quantum origin since they depend on system size over electronic wavelength, and so have no analogue in classical thermodynamics. The maximal efficiency coincides with Carnot efficiency at zero power output, but decreases with increasing power output. This gives a fundamental lower bound on entropy production, which means that reversibility (in the thermodynamic sense) is impossible for finite power output. The suppression of efficiency by (nonlinear) phonon and photon effects is addressed in detail; when these effects are strong, maximum efficiency coincides with maximum power. Finally, we show in particular limits (typically without magnetic fields) that relaxation within the quantum system does not allow the system to exceed the bounds derived for relaxation-free systems, however, a general proof of this remains elusive.

Robert S. Whitney

2015-03-16T23:59:59.000Z

193

Regenerator Location Problem in Flexible Optical Networks  

E-Print Network [OSTI]

Nov 22, 2014 ... Abstract: In this study we introduce the regenerator location problem in flexible optical networks (RLP-FON). With a given traffic demand,...

BARIS YILDIZ

2014-11-22T23:59:59.000Z

194

Table S1. Mixed-model ANOVA and Tukey's HSD results for the diversity of co-occurring ant species in plots. Sites were locations within 5 different forest stands within  

E-Print Network [OSTI]

Table S1. Mixed-model ANOVA and Tukey's HSD results for the diversity of co- occurring ant species.64 0.0385 year*site*ground*ant 4 0.08581728 0.02145432 0.20 0.9400 Tukey's Studentized Range (HSD) Tests for Number of species. Means with the same letter are not significantly different. Tukey Grouping

195

Locational-based Coupling of Electricity Markets: Benefits from Coordinating Unit Commitment and Balancing Markets  

E-Print Network [OSTI]

We formulate a series of stochastic models for committing and dispatching electric generators subject to transmission limits. The models are used to estimate the benefits of electricity locational marginal pricing (LMP) that arise from better...

van der Weijde, Adriaan Hendrik; Hobbs, Benjamin F.

196

Numerical simulations of output pulse extraction from a high-power microwave compressor with a plasma switch  

SciTech Connect (OSTI)

Numerical simulations of the process of electromagnetic energy release from a high-power microwave pulse compressor comprising a gas-filled cavity and interference switch were carried out. A microwave plasma discharge in a rectangular waveguide H-plane tee was modeled with the use of the fully electromagnetic particle-in-cell code MAGIC. The gas ionization, plasma evolution, and interaction with RF fields accumulated within the compressor were simulated using different approaches provided by the MAGIC code: particle-in-cell approach accounting for electron-neutral collisions, gas conductivity model based on the concept of mobility, and hybrid modeling. The dependences of the microwave output pulse peak power and waveform on parameters that can be controlled in experiments, such as an external ionization rate, RF field amplitude, and background gas pressure, were investigated.

Shlapakovski, Anatoli; Beilin, Leonid; Bliokh, Yuri; Donskoy, Moshe; Krasik, Yakov E. [Physics Department, Technion, Haifa 32000 (Israel); Hadas, Yoav [Department of Applied Physics, Rafael, PO Box 2250, Haifa 31021 (Israel); Schamiloglu, Edl [Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, New Mexico 87131 (United States)

2014-05-07T23:59:59.000Z

197

Fault Locating, Prediction and Protection (FLPPS)  

SciTech Connect (OSTI)

One of the main objectives of this DOE-sponsored project was to reduce customer outage time. Fault location, prediction, and protection are the most important aspects of fault management for the reduction of outage time. In the past most of the research and development on power system faults in these areas has focused on transmission systems, and it is not until recently with deregulation and competition that research on power system faults has begun to focus on the unique aspects of distribution systems. This project was planned with three Phases, approximately one year per phase. The first phase of the project involved an assessment of the state-of-the-art in fault location, prediction, and detection as well as the design, lab testing, and field installation of the advanced protection system on the SCE Circuit of the Future located north of San Bernardino, CA. The new feeder automation scheme, with vacuum fault interrupters, will limit the number of customers affected by the fault. Depending on the fault location, the substation breaker might not even trip. Through the use of fast communications (fiber) the fault locations can be determined and the proper fault interrupting switches opened automatically. With knowledge of circuit loadings at the time of the fault, ties to other circuits can be closed automatically to restore all customers except the faulted section. This new automation scheme limits outage time and increases reliability for customers. The second phase of the project involved the selection, modeling, testing and installation of a fault current limiter on the Circuit of the Future. While this project did not pay for the installation and testing of the fault current limiter, it did perform the evaluation of the fault current limiter and its impacts on the protection system of the Circuit of the Future. After investigation of several fault current limiters, the Zenergy superconducting, saturable core fault current limiter was selected for installation. Because of some testing problems with the Zenergy fault current limiter, installation was delayed until early 2009 with it being put into operation on March 6, 2009. A malfunction of the FCL controller caused the DC power supply to the superconducting magnet to be turned off. This inserted the FCL impedance into the circuit while it was in normal operation causing a voltage resonance condition. While these voltages never reached a point where damage would occur on customer equipment, steps were taken to insure this would not happen again. The FCL was reenergized with load on December 18, 2009. A fault was experienced on the circuit with the FCL in operation on January 14, 2010. The FCL operated properly and reduced the fault current by about 8%, what was expected from tests and modeling. As of the end of the project, the FCL was still in operation on the circuit. The third phase of the project involved the exploration of several advanced protection ideas that might be at a state where they could be applied to the Circuit of the Future and elsewhere in the SCE electrical system. Based on the work done as part of the literature review and survey, as well as a number of internal meetings with engineering staff at SCE, a number of ideas were compiled. These ideas were then evaluated for applicability and ability to be applied on the Circuit of the Future in the time remaining for the project. Some of these basic ideas were implemented on the circuit including measurement of power quality before and after the FCL. It was also decided that we would take what was learned as part of the Circuit of the Future work and extend it to the next generation circuit protection for SCE. Also at this time, SCE put in a proposal to the DOE for the Irvine Smart Grid Demonstration using ARRA funding. SCE was successful in obtaining funding for this proposal, so it was felt that exploration of new protection schemes for this Irvine Smart Grid Demonstration would be a good use of the project resources. With this in mind, a protection system that uses fault interrupting switches, hi

Yinger, Robert, J.; Venkata, S., S.; Centeno, Virgilio

2010-09-30T23:59:59.000Z

198

Locating and tracking assets using RFID  

E-Print Network [OSTI]

. In this research, we will focus on how to ?nd the location of an item by using RFID in real time indoors to track equipment. When an item needs to be located, the purpose of using RFID is to minimize the searching time, e?ort, and investment cost. Thus...

Kim, Gak Gyu

2009-05-15T23:59:59.000Z

199

RECYCLING PROGRAM TYPE LOCATION ALLOWED NOT ALLOWED  

E-Print Network [OSTI]

RECYCLING PROGRAM TYPE LOCATION ALLOWED NOT ALLOWED Batteries, toner, ink cartridges & cell phones and recycling is an important part of that effort. Below is a guide to on-campus recycling at RSMAS: Visit http://www.rsmas.miami.edu/msgso/ for map of recycling bin locations. NOTE: This is not an exhaustive list. If unauthorized items are found

Miami, University of

200

Location Privacy and the Personal Distributed Environment  

E-Print Network [OSTI]

Location Privacy and the Personal Distributed Environment Robert C Atkinson, Swee Keow Goo, James-- The Personal Distributed Environment is a new concept being developed within the Mobile VCE Core 3 research, wherever their location: ubiquitous access. Devices are co-ordinated by Device Management Entities (DMEs

Atkinson, Robert C

Note: This page contains sample records for the topic "model output location" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


201

Output dominance as a predictor of humor content in verbal productions  

E-Print Network [OSTI]

-dominance-ordered feature lists generated for each of the concepts. It was hypothesized that juxtapositions judged funny would rely more often on properties with significantly different output dominance scores per concept, while those judged not funny would involve fewer...

Hull, Rachel Gayle

2000-01-01T23:59:59.000Z

202

Examining the Variability of Wind Power Output in the Regulation Time Frame: Preprint  

SciTech Connect (OSTI)

This work examines the distribution of changes in wind power for different time scales in the regulation time frame as well as the correlation of changes in power output for individual wind turbines in a wind plant.

Hodge, B. M.; Shedd, S.; Florita, A.

2012-08-01T23:59:59.000Z

203

Augmentation of Power Output of Axisymmetric Ducted Wind Turbines by Porous Trailing Edge Disks  

E-Print Network [OSTI]

This paper presents analytical and experimental results that demonstrated that the power output from a ducted wind turbine can be dramatically increased by the addition of a trailing edge device such as a porous disk. In ...

widnall, sheila

2014-06-30T23:59:59.000Z

204

A Hardware Implementation of the Soft Output Viterbi Algorithm for Serially Concatenated Convolutional Codes  

E-Print Network [OSTI]

This thesis outlines the hardware design of a soft output Viterbi algorithm decoder for use in a serially concatenated convolutional code system. Convolutional codes and their related structures are described, as well as the algorithms used...

Werling, Brett William

2010-06-28T23:59:59.000Z

205

Primate Motor Cortex: Individual and Ensemble Neuron-Muscle Output Relationships  

E-Print Network [OSTI]

The specific aims of this study were to: 1) investigate the encoding of forelimb muscle activity timing and magnitude by corticomotoneuronal (CM) cells, 2) test the stability of primary motor cortex (M1) output to forelimb ...

Griffin, Darcy Michelle

2008-07-30T23:59:59.000Z

206

Multilevel Cascade H-bridge Inverter DC Voltage Estimation Through Output Voltage Sensing  

E-Print Network [OSTI]

system as the inverter power supply may vary. For example, interface of solar panels or fuel cell. The output voltage is then processed by a DSP unit that uses the signals that command the switches

Tolbert, Leon M.

207

Input-Output as a Method of Evaluahon of the Economic Impact of Water Resources Development  

E-Print Network [OSTI]

In this report the results of a study of the use of input-output analysis to evaluate the economic impact of water resources development are presented. Blackburn Crossing reservoir on the Upper Neches river was the subject development...

Canion, R. L.; Trock, W. L.

208

Code design for multiple-input multiple-output broadcast channels  

E-Print Network [OSTI]

Recent information theoretical results indicate that dirty-paper coding (DPC) achieves the entire capacity region of the Gaussian multiple-input multiple-output (MIMO) broadcast channel (BC). This thesis presents practical code designs for Gaussian...

Uppal, Momin Ayub

2009-06-02T23:59:59.000Z

209

Water Power Calculator Temperature and Analog Input/Output Module Ambient Temperature Testing  

SciTech Connect (OSTI)

Water Power Calculator Temperature and Analog input/output Module Ambient Temperature Testing A series of three ambient temperature tests were conducted for the Water Power Calculator development using the INL Calibration Laboratorys Tenney Environmental Chamber. The ambient temperature test results demonstrate that the Moore Industries Temperature Input Modules, Analog Input Module and Analog Output Module, ambient temperature response meet or exceed the manufactures specifications

Mark D. McKay

2011-02-01T23:59:59.000Z

210

Exploring the circadian outputs and function of HPT-1 in Neurospora crassa  

E-Print Network [OSTI]

EXPLORING THE CIRCADIAN OUTPUTS AND FUNCTIONS OF HTP-1 IN NEUROSPORA CRASSA An Undergraduate Research Scholars Thesis by JUSTIN WAYDE VICKERY Submitted to Honors and Undergraduate Research Texas A&M University in partial fulfillment... ......................................................................................................................... 25 1 ABSTRACT Exploring the circadian outputs and functions of HPT-1 in N. crassa. (May 2014) Justin Wayde Vickery Department of Biology Texas A&M University Research Advisor: Dr. Deborah Bell-Pedersen Department of Biology...

Vickery, Justin Wayde

2013-09-28T23:59:59.000Z

211

Analytical protostellar disk models 1: the effect of internal dissipation and surface irradiation on the structure of disks and the location of the snow line around Sun-like stars  

E-Print Network [OSTI]

We construct a new set of self-consistent analytical disk models by taking into account both viscous and radiative sources of thermal energy. We analyze the non-isothermal structure of the disk across the mid-plane for optically thick disks, and use the standard two-temperature model in the case of optically thin disks. We deduce a set of general formula for the relationship between the mass accretion rate and the surface density profile. Our results recover those of Chiang & Goldreich in the optically thin regions, but extend their work for the opaque regions of the disk. For the purpose of illustration, we apply our theory in this paper to determine the structure of protostellar disks around T Tauri stars under a state of steady accretion and derive the corresponding radial distribution function of various disk properties such as surface density and temperature near the mid-plane. We calculate the position of the snow line around a sun-like T Tauri star, and deduce that it can evolve from well outside 10 AU during FU Orionis outbursts, to about 4 AU during passive accretion phase, to the present-day orbital radius of Venus and finally re-expand to over 2.2 AU during the protostellar- to-debris disk transition. This non-monotonous evolution of the snow line may provide some novel and deterministic explanation for the total water content and its isotopic composition of both Venus and the Earth. In the optically thin, outermost regions of the disk we find that the surface density profile of the dust varies roughly as 1/r, which is consistent with mm observations of spatially resolved disk of Mundy et al. (2000).

Pascale Garaud; Douglas N. C. Lin

2006-05-03T23:59:59.000Z

212

SFSU Building Coordinators List College or Administrative Unit Location(s)  

E-Print Network [OSTI]

SFSU Building Coordinators List College or Administrative Unit Location(s) Building Coordinator81193 cathym@sfsu.edu GYM 102B Student Services Building SSB Mirel Tikkanen x53566 mtikkane@sfsu.edu SSB

213

The Value of Flexibility in Robust Location-Transportation Problem  

E-Print Network [OSTI]

production and distribution of products can be delayed until actual orders are ... such as hub locations, supplier locations, air freight hub locations, railway station

2014-11-24T23:59:59.000Z

214

Output Harmonic Termination Techniques for AlGaN/GaN HEMT Power Amplifiers Using Active Integrated Antenna Approach  

E-Print Network [OSTI]

Output Harmonic Termination Techniques for AlGaN/GaN HEMT Power Amplifiers Using Active Integrated 1200, Los Angeles, CA 90045 Abstract -- In this paper, effects of output harmonic terminations on PAE termination, we observe a substantial increase in PAE and output power. Further, we demonstrate the high

Itoh, Tatsuo

215

Developing a theory of nightclub location choice  

E-Print Network [OSTI]

This work is an investigation of the factors that influence where nightclubs locate within a city. Nightclubs, like other social spaces, provide important social and economic benefits in the urban environment. As amenities, ...

Crim, Stephen J. (Stephen Johnson)

2008-01-01T23:59:59.000Z

216

THE PLANAR HUB LOCATION PROBLEM: A PROBABILISTIC ...  

E-Print Network [OSTI]

Nov 5, 2012 ... Aykin and Brown, [4]. ...... [8] J.F. Campbell, Integer programming formulations of discrete hub location problems, European J. of O.R.. 72(1994)...

2012-11-21T23:59:59.000Z

217

Personal Digital Assistant PDA ----Location Based  

E-Print Network [OSTI]

, xur],[ ybl, yur ]) k k=100 K k k- AminAmin kLk k Amax TmaxTmax kAminLocation Anonymization ConstraintsAmax TmaxLocation Service Quality Constraints 3.3 3.3.1 id, loc, query id loc (x,y)query GPS / l- l- k- l- k l- l l- l- m-invariant 2 29 #12;[22] A B C D E F R1 R2 R3 6 Outlier 6

218

Distributed quantitative precipitation forecasts combining information from radar and numerical weather prediction model outputs  

E-Print Network [OSTI]

Applications of distributed Quantitative Precipitation Forecasts (QPF) range from flood forecasting to transportation. Obtaining QPF is acknowledged to be one of the most challenging areas in hydrology and meteorology. ...

Ganguly, Auroop Ratan

2002-01-01T23:59:59.000Z

219

Scaling analyses of forcings and outputs of a simplified Last1 Millennium climate model2  

E-Print Network [OSTI]

its responses with those of multiproxies and the NASA GISS-ER2 GCM. 22 became too weak at 27 longer scales. At small scales, the GISS ER2

Lovejoy, Shaun

220

Dissemination of Climate Model Output to the Public and Commercial Sector  

SciTech Connect (OSTI)

Climate is defined by the Glossary of Meteorology as the mean of atmospheric variables over a period of time ranging from as short as a few months to multiple years and longer. Although the term climate is often used to refer to long-term weather statistics, the broader definition of climate is the time evolution of a system consisting of the atmosphere, hydrosphere, lithosphere, and biosphere. Physical, chemical, and biological processes are involved in interactions among the components of the climate system. Vegetation, soil moisture, and glaciers are part of the climate system in addition to the usually considered temperature and precipitation (Pielke, 2008). Climate change refers to any systematic change in the long-term statistics of climate elements (such as temperature, pressure, or winds) sustained over several decades or longer. Climate change can be initiated by external forces, such as cyclical variations in the Earth's solar orbit that are thought to have caused glacial and interglacial periods within the last 2 million years (Milankovitch, 1941). However, a linear response to astronomical forcing does not explain many other observed glacial and interglacial cycles (Petit et al., 1999). It is now understood that climate is influenced by the interaction of solar radiation with atmospheric greenhouse gasses (e.g., carbon dioxide, chlorofluorocarbons, methane, nitrous oxide, etc.), aerosols (airborne particles), and Earth's surface. A significant aspect of climate are the interannual cycles, such as the El Nino La Nina cycle which profoundly affects the weather in North America but is outside the scope of weather forecasts. Some of the most significant advances in understanding climate change have evolved from the recognition of the influence of ocean circulations upon the atmosphere (IPCC, 2007). Human activity can affect the climate system through increasing concentrations of atmospheric greenhouse gases, air pollution, increasing concentrations of aerosol, and land alteration. A particular concern is that atmospheric levels of CO{sub 2} may be rising faster than at any time in Earth's history, except possibly following rare events like impacts from large extraterrestrial objects (AMS, 2007). Atmospheric CO{sub 2} concentrations have increased since the mid-1700s through fossil fuel burning and changes in land use, with more than 80% of this increase occurring since 1900. The increased levels of CO{sub 2} will remain in the atmosphere for hundreds to thousands of years. The complexity of the climate system makes it difficult to predict specific aspects of human-induced climate change, such as exactly how and where changes will occur, and their magnitude. The Intergovernmental Panel for Climate Change (IPCC) was established by World Meteorological Organization (WMO) and the United Nations in 1988. The IPCC was tasked with assessing the scientific, technical and socioeconomic information needed to understand the risk of human-induced climate change, its observed and projected impacts, and options for adaptation and mitigation. The IPCC concluded in its Fourth Assessment Report (AR4) that warming of the climate system is unequivocal, and that most of the observed increase in globally averaged temperatures since the mid-20th century is very likely due to the observed increased in anthropogenic greenhouse gas concentrations (IPCC, 2007).

Robert Stockwell, PhD

2010-09-23T23:59:59.000Z

Note: This page contains sample records for the topic "model output location" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


221

A Comparison of Simulated Cloud Radar Output from the Multiscale Modeling  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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),Feet) Year Jan Feb Mar Apr May Jun Jul(Summary)morphinanInformation Desert SouthwestTechnologies |November 2011 Mon,Electrocatalysis |Framework Global Climate

222

Dosimetric characterization and output verification for conical brachytherapy surface applicators. Part II. High dose rate {sup 192}Ir sources  

SciTech Connect (OSTI)

Purpose: Historically, treatment of malignant surface lesions has been achieved with linear accelerator based electron beams or superficial x-ray beams. Recent developments in the field of brachytherapy now allow for the treatment of surface lesions with specialized conical applicators placed directly on the lesion. Applicators are available for use with high dose rate (HDR){sup 192}Ir sources, as well as electronic brachytherapy sources. Part I of this paper discussed the applicators used with electronic brachytherapy sources. Part II will discuss those used with HDR {sup 192}Ir sources. Although the use of these applicators has gained in popularity, the dosimetric characteristics have not been independently verified. Additionally, there is no recognized method of output verification for quality assurance procedures with applicators like these. Methods: This work aims to create a cohesive method of output verification that can be used to determine the dose at the treatment surface as part of a quality assurance/commissioning process for surface applicators used with HDR electronic brachytherapy sources (Part I) and{sup 192}Ir sources (Part II). Air-kerma rate measurements for the {sup 192}Ir sources were completed with several models of small-volume ionization chambers to obtain an air-kerma rate at the treatment surface for each applicator. Correction factors were calculated using MCNP5 and EGSnrc Monte Carlo codes in order to determine an applicator-specific absorbed dose to water at the treatment surface from the measured air-kerma rate. Additionally, relative dose measurements of the surface dose distributions and characteristic depth dose curves were completed in-phantom. Results: Theoretical dose distributions and depth dose curves were generated for each applicator and agreed well with the measured values. A method of output verification was created that allows users to determine the applicator-specific dose to water at the treatment surface based on a measured air-kerma rate. Conclusions: The novel output verification methods described in this work will reduce uncertainties in dose delivery for treatments with these kinds of surface applicators, ultimately improving patient care.

Fulkerson, Regina K., E-mail: rmkenned@gmail.com; Micka, John A.; DeWerd, Larry A. [Department of Medical Physics, University of WisconsinMadison, Madison, Wisconsin 53705 (United States)] [Department of Medical Physics, University of WisconsinMadison, Madison, Wisconsin 53705 (United States)

2014-02-15T23:59:59.000Z

223

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

3. Summary Statistics for Coal Refining Plants, 2012 - 2014" "(thousand short tons)" "Year and","Coal Receipts","Average Price of Coal Receipts","Coal Used","Coal Stocks1"...

224

SAS Output  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

4. Nitrogen Oxides Control Technology Emissions Reduction Factors Nitrogen Oxides Control Technology EIA-Code(s) Reduction Factor Advanced Overfire Air AA 30% Alternate Burners BF...

225

SAS Output  

Gasoline and Diesel Fuel Update (EIA)

Boiler Spreader Stoker Boiler Tangential Boiler All Other Boiler Types Combustion Turbine Internal Combustion Engine Agricultural Byproducts AB Source: 1 Lbs per ton 0.08 0.01...

226

SAS Output  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

System Type Firing Configuration Tangential Boiler All Other Boiler Types Combustion Turbine Internal Combustion Engine Fuel EIA Fuel Code Source and Tables (As Appropriate)...

227

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

"(thousand short tons)" "Census Division","June 30 2014","March 31 2014","June 30 2013","Percent Change" "and State",,,,"(June 30)" ,,,,"2014 versus 2013" "Middle...

228

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

to Date" "Census Division","April - June","January - March","April - June",2014,2013,"Percent" "and State1",2014,2014,2013,,,"Change" "Middle Atlantic" "...

229

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

to Date" "Census Division","April - June","January - March","April - June",2014,2013,"Percent" ,2014,2014,2013,,,"Change" "Middle Atlantic",1222,1214,1247,2435,2460,-1...

230

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

,,,,"Year to Date" "Commodity","April - June","January - March","April - June",2014,2013,"Percent" ,2014,2014,2013,,,"Change" "Coke" " Sales",1969,1865,1969,3834,3905,-1.8 "...

231

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

to Date" "Census Division","April - June","January - March","April - June",2014,2013,"Percent" ,2014,2014,2013,,,"Change" "Middle Atlantic",1599,1503,1622,3102,3178,-2.4...

232

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

to Date" "Census Division","April - June","January - March","April - June",2014,2013,"Percent" "and State",2014,2014,2013,,,"Change" "Middle Atlantic",113.65,114.55,139.64,...

233

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

,,,,"Year to Date" "NAICS Code","April - June","January - March","April - June",2014,2013,"Percent" ,2014,2014,2013,,,"Change" "311 Food Manufacturing",2085,2575,2256,4660,4817,...

234

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

Code" "(thousand short tons)" "NAICS Code","June 30 2014","March 31 2014","June 30 2013","Percent Change" ,,,,"(June 30)" ,,,,"2014 versus 2013" "311 Food...

235

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

to Date" "Census Division","April - June","January - March","April - June",2014,2013,"Percent" "and State",2014,2014,2013,,,"Change" "New England",20,30,21,51,48,5.5 "...

236

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

to Date" "Census Division","April - June","January - March","April - June",2014,2013,"Percent" "and State",2014,2014,2013,,,"Change" "Middle Atlantic",19,58,25,77,79,-2.7 "...

237

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

to Date" "Census Division","April - June","January - March","April - June",2014,2013,"Percent" "and State",2014,2014,2013,,,"Change" "New England","w","w","w","w","w","w" "...

238

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

"(thousand short tons)" "Census Division","June 30 2014","March 31 2014","June 30 2013","Percent Change" "and State",,,,"(June 30)" ,,,,"2014 versus 2013" "New...

239

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

to Date" "Census Division","April - June","January - March","April - June",2014,2013,"Percent" "and State1",2014,2014,2013,,,"Change" "New England" " Btu",13306,12964,13323...

240

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

,"Sector1",,,"Institutional Users",,"Distributors" 2008 " March 31",146497,1462,4818,448,153225,34876,188101 " June 30",152542,1756,4983,478,159760,32086,191846 "...

Note: This page contains sample records for the topic "model output location" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


241

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

,,,,"Year to Date" "NAICS Code","April - June","January - March","April - June",2014,2013,"Percent" ,2014,2014,2013,,,"Change" "311 Food Manufacturing",2111,2386,2214,4497,4570,...

242

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

to Date" "Census Division","April - June","January - March","April - June",2014,2013,"Percent" "and State",2014,2014,2013,,,"Change" "Middle Atlantic",21,59,20,80,73,10.4 "...

243

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

to Date" "Census Division","April - June","January - March","April - June",2014,2013,"Percent" "and State",2014,2014,2013,,,"Change" "New England",21,29,22,50,48,3.1 "...

244

SAS Output  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared0 ResourceAwards SAGE Awards A(SAPC) Working GroupB..3.3. Revenue

245

SAS Output  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared0 ResourceAwards SAGE Awards A(SAPC) Working GroupB..3.3. Revenue4.

246

SAS Output  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared0 ResourceAwards SAGE Awards A(SAPC) Working GroupB..3.3.

247

SAS Output  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared0 ResourceAwards SAGE Awards A(SAPC) Working GroupB..3.3.A.

248

SAS Output  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared0 ResourceAwards SAGE Awards A(SAPC) Working GroupB..3.3.A.B.

249

SAS Output  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared0 ResourceAwards SAGE Awards A(SAPC) Working GroupB..3.3.A.B.A. Net

250

SAS Output  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared0 ResourceAwards SAGE Awards A(SAPC) Working GroupB..3.3.A.B.A.

251

SAS Output  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared0 ResourceAwards SAGE Awards A(SAPC) Working GroupB..3.3.A.B.A.A.

252

SAS Output  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared0 ResourceAwards SAGE Awards A(SAPC) Working GroupB..3.3.A.B.A.A.B.

253

SAS Output  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared0 ResourceAwards SAGE Awards A(SAPC) Working

254

SAS Output  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared0 ResourceAwards SAGE Awards A(SAPC) WorkingB. Winter Net Internal

255

SAS Output  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared0 ResourceAwards SAGE Awards A(SAPC) WorkingB. Winter Net

256

SAS Output  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared0 ResourceAwards SAGE Awards A(SAPC) WorkingB. Winter NetB.

257

SAS Output  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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),Feet) Year Jan Feb Mar Apr MayAtmosphericNuclear Security Administration the1 -the Mid-Infrared0 ResourceAwards SAGE Awards A(SAPC) WorkingB. Winter NetB.4.5.

258

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional Gasoline Blend.1.

259

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional Gasoline Blend.1.2.

260

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional Gasoline

Note: This page contains sample records for the topic "model output location" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


261

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional Gasoline. Number of

262

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional Gasoline. Number

263

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional Gasoline. Number3.

264

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional Gasoline. Number3.5.

265

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional Gasoline.

266

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional Gasoline.7. Average

267

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional Gasoline.7.

268

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional Gasoline.7.9.

269

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional Gasoline.7.9.0.

270

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional Gasoline.7.9.0.1.

271

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional Gasoline.7.9.0.1.2.

272

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional

273

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. Green Pricing

274

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. Green PricingA.

275

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. Green PricingA.B.

276

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. Green

277

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. GreenB. Net

278

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. GreenB. Net3.A.

279

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. GreenB. Net3.A.B.

280

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. GreenB.

Note: This page contains sample records for the topic "model output location" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


281

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. GreenB.B. Net

282

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. GreenB.B. NetA.

283

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. GreenB.B. NetA.B.

284

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. GreenB.B.

285

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. GreenB.B.7. Net

286

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. GreenB.B.7. Net8.

287

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. GreenB.B.7.

288

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. GreenB.B.7.0. Net

289

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. GreenB.B.7.0.

290

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. GreenB.B.7.0.2.

291

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4. GreenB.B.7.0.2.3.

292

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.

293

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5. Net Generation

294

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5. Net Generation6.

295

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5. Net

296

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5. Net8. Net

297

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5. Net8. Net9. Net

298

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5. Net8. Net9.

299

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5. Net8. Net9.1.

300

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5. Net8. Net9.1.2.

Note: This page contains sample records for the topic "model output location" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


301

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5. Net8.

302

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5. Net8.4. Useful

303

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5. Net8.4. Useful.

304

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5. Net8.4.

305

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5. Net8.4.B.

306

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5. Net8.4.B.3.

307

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5. Net8.4.B.3.4.

308

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5. Net8.4.B.3.4.5.

309

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.

310

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A. Net Summer

311

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A. Net SummerB.

312

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A. Net SummerB.C.

313

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A. Net

314

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A. Net0. Net

315

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A. Net0. Net1.

316

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A. Net0. Net1.2.

317

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A. Net0.

318

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A. Net0.4.

319

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A. Net0.4.A.

320

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A. Net0.4.A.B.

Note: This page contains sample records for the topic "model output location" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


321

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A. Net0.4.A.B.C.

322

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A.

323

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A.E. Coal:

324

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A.E. Coal:F.

325

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A.E. Coal:F.A.

326

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A.E. Coal:F.A.B.

327

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A.E.

328

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A.E.D. Petroleum

329

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A.E.D.

330

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A.E.D.F.

331

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A.E.D.F.A.

332

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A.E.D.F.A.B.

333

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A.E.D.F.A.B.C.

334

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on CokersA2.Conventional4.5.A.E.D.F.A.B.C.D.

335

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity on

336

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: Consumption for

337

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: Consumption forA.

338

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: Consumption forA.B.

339

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: Consumption forA.B.C.

340

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: Consumption forA.B.C.D.

Note: This page contains sample records for the topic "model output location" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


341

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: Consumption

342

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: ConsumptionF. Natural

343

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: ConsumptionF. NaturalD.

344

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: ConsumptionF.

345

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: ConsumptionF.F. Wood /

346

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: ConsumptionF.F. Wood /A.

347

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: ConsumptionF.F. Wood

348

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: ConsumptionF.F. WoodC.

349

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: ConsumptionF.F. WoodC.D.

350

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: ConsumptionF.F.

351

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: ConsumptionF.F.F.

352

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: ConsumptionF.F.F.A.

353

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: ConsumptionF.F.F.A.B.

354

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke: ConsumptionF.F.F.A.B.C.

355

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:

356

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E. Biogenic Municipal

357

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E. Biogenic MunicipalF.

358

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E. Biogenic MunicipalF.D.

359

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E. Biogenic

360

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E. BiogenicF. Other Waste

Note: This page contains sample records for the topic "model output location" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


361

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E. BiogenicF. Other

362

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E. BiogenicF. Other0.

363

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E. BiogenicF. Other0.1.

364

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E. BiogenicF. Other0.1.2.

365

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E. BiogenicF.

366

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E. BiogenicF.4.

367

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E. BiogenicF.4.1. Stocks

368

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E. BiogenicF.4.1. Stocks2

369

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E. BiogenicF.4.1.

370

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E. BiogenicF.4.1.4.

371

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E. BiogenicF.4.1.4..

372

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E. BiogenicF.4.1.4..3.

373

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E. BiogenicF.4.1.4..3.4.

374

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.

375

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6. Receipts, Average

376

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6. Receipts, Average7

377

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6. Receipts, Average78.

378

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6. Receipts,

379

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6. Receipts,0.

380

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6. Receipts,0.1.

Note: This page contains sample records for the topic "model output location" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


381

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6. Receipts,0.1.2.

382

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6. Receipts,0.1.2.3.

383

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6. Receipts,0.1.2.3.4.

384

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.

385

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6. Receipts of

386

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6. Receipts of7.

387

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6. Receipts of7.8.

388

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6. Receipts of7.8.9.

389

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6. Receipts

390

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6. Receipts1.

391

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6. Receipts1.2.

392

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6. Receipts1.2.3.

393

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6. Receipts1.2.3.4.

394

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6. Receipts1.2.3.4.5.

395

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6.

396

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6.2. Average Tested

397

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6.2. Average Tested3.

398

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6.2. Average

399

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6.2. Average.

400

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6.2. Average.2.

Note: This page contains sample records for the topic "model output location" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


401

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6.2. Average.2.3.

402

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6.2. Average.2.3.4.

403

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6.2. Average.2.3.4.5.

404

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6.2.

405

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6.2.7. Energy

406

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6.2.7. Energy8.

407

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6.2.7. Energy8.9.

408

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia,(Million Barrels) Crude Oil Reserves in NonproducingAdditions to Capacity onF. Petroleum Coke:E.6.6.2.7. Energy8.9.A.5.

409

SAS Output  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

Bituminous Coal BIT Source: 1 205.30000 Distillate Fuel Oil DFO Source: 1 161.38600 Geothermal GEO Estimate from EIA, Office of Integrated Analysis and Forecasting 16.59983 Jet...

410

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

1. U.S. Coal Summary Statistics, 2008 - 2014" "(thousand short tons)" "Year and","Production1","Imports","Waste Coal","Producer and","Consumption","Exports","Consumer","Losses and"...

411

SAS Output  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLas ConchasPassive Solar HomePromisingStoriesSANDIA REPORT SAND 2011-39584. Average Retail Price

412

SAS Output  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLas ConchasPassive Solar HomePromisingStoriesSANDIA REPORT SAND 2011-39584. Average Retail

413

SAS Output  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLas ConchasPassive Solar HomePromisingStoriesSANDIA REPORT SAND 2011-39584. Average Retail1.

414

SAS Output  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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),Feet) Year Jan Feb Mar Apr May JunDatastreamsmmcrcalgovInstrumentsrucLas ConchasPassive Solar HomePromisingStoriesSANDIA REPORT SAND 2011-39584. Average Retail1.2.

415

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)Percent of U.S.Percent of U.S.Coal

416

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)Percent of U.S.Percent of

417

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)Percent of U.S.Percent ofProductive

418

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)Percent of U.S.Percent

419

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)Percent of U.S.PercentProductive

420

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)Percent of

Note: This page contains sample records for the topic "model output location" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


421

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)Percent ofRecoverable Coal Reserves

422

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)Percent ofRecoverable Coal

423

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)Percent ofRecoverable

424

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)Percent ofRecoverableAverage Number

425

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)Percent ofRecoverableAverage

426

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)Percent ofRecoverableAverageand

427

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)Percent

428

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal Productivity by State

429

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal Productivity by State2.

430

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal Productivity by

431

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal Productivity by4. Coal

432

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal Productivity by4.

433

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal Productivity by4.6.

434

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal Productivity by4.6.7.

435

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal Productivity by4.6.7.8.

436

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal Productivity

437

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal ProductivityUnderground

438

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal

439

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal1. Average Sales Price

440

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal1. Average Sales Price2.

Note: This page contains sample records for the topic "model output location" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


441

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal1. Average Sales

442

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal1. Average Sales4.

443

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal1. Average Sales4.Coal

444

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal1. Average

445

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal1. AverageCoal

446

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal1. AverageCoalCoal

447

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal1. AverageCoalCoalCoal

448

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal1.

449

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal1.Report No.: DOE/EIA

450

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ <Information Administration (EIA) 10 MECS Survey Data 2010Feet)PercentCoal1.Report No.: DOE/EIA0.

451

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price decreases The448

452

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price decreases The448U.S.

453

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price decreases The448U.S.Average

454

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price decreases

455

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price decreasesSteam Coal Exports by

456

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price decreasesSteam Coal Exports

457

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price decreasesSteam Coal

458

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price decreasesSteam CoalAverage

459

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price decreasesSteam CoalAverageU.S.

460

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price decreasesSteam

Note: This page contains sample records for the topic "model output location" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


461

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price decreasesSteamCoal Production,

462

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price decreasesSteamCoal

463

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price decreasesSteamCoalU.S. Coke

464

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price decreasesSteamCoalU.S.

465

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price decreasesSteamCoalU.S.by

466

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price decreasesSteamCoalU.S.byU.S.

467

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price

468

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price Quantity and Average Price of

469

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price Quantity and Average Price

470

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price Quantity and Average

471

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

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 CenterFranconia, Virginia:FAQ < RAPID Jump to:SeadovCooperativeA2. World9, 2014 Residential propane price Quantity and Average U.S.

472

SAS Output  

Gasoline and Diesel Fuel Update (EIA)

B. U.S. Transformer Sustained Automatic Outage Counts and Hours by High-Voltage Size and NERC Region, 2012 Sustained Automatic Outage Counts High-Side Voltage (kV) Eastern...

473

SAS Output  

Gasoline and Diesel Fuel Update (EIA)

B. U.S. Transformer Outages by Type and NERC region, 2012 Outage Type Eastern Interconnection TRE WECC Contiguous U.S. Circuit Outage Counts Automatic Outages (Sustained) 16.00 --...

474

SAS Output  

Gasoline and Diesel Fuel Update (EIA)

B. U.S. Transformer Sustained Automatic Outage Counts and Hours by Cause Code and by NERC Region, 2012 Transformer Outage Counts Sustained Outage Causes FRCC MRO NPCC RFC SERC SPP...

475

SAS Output  

U.S. Energy Information Administration (EIA) Indexed Site

,109.81,115.95,110.07,117.4,-6.2 "315 Apparel Manufacturing","w","w","w","w","w","w" "321 Wood Product Manufacturing","w","-","w","w","w","w" "322 Paper Manufacturing",87.55,88.68,...

476

A combined compensation method for the output voltage of an insulated core transformer power supply  

SciTech Connect (OSTI)

An insulated core transformer (ICT) power supply is an ideal high-voltage generator for irradiation accelerators with energy lower than 3 MeV. However, there is a significant problem that the structure of the segmented cores leads to an increase in the leakage flux and voltage differences between rectifier disks. A high level of consistency in the output of the disks helps to achieve a compact structure by improving the utilization of both the rectifier components and the insulation distances, and consequently increase the output voltage of the power supply. The output voltages of the disks which are far away from the primary coils need to be improved to reduce their inhomogeneity. In this study, by investigating and comparing the existing compensation methods, a new combined compensation method is proposed, which increases the turns on the secondary coils and employs parallel capacitors to improve the consistency of the disks, while covering the entire operating range of the power supply. This method turns out to be both feasible and effective during the development of an ICT power supply. The non-uniformity of the output voltages of the disks is less than 3.5% from no-load to full-load, and the power supply reaches an output specification of 350 kV/60 mA.

Yang, L.; Yang, J., E-mail: jyang@mail.hust.edu.cn; Liu, K. F.; Qin, B.; Chen, D. Z. [State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan 430074 (China)

2014-06-15T23:59:59.000Z

477

Note: Synchronous energy extraction through four output ports of microwave compressor  

SciTech Connect (OSTI)

The energy stored in a resonant cavity was extracted through four output ports and added in phase in a common line. Operation of a single switch provided synchronism and the power portions transmitted through the ports were combined in a waveguide turnstile junction. Estimation shows that the compressor peak power can reach a value eight times as much as the switched wave power, provided the output pulsewidth is shortened by the same factor with reference to the cavity double transit time. The performance of the X-band compressor prototype was investigated. Signals radiated through each of four output ports had identical envelope shapes and equal peak power values. The reflected wave did not accompany the power combining. The pulses of 1.2 MW peak power and 1.6 ns pulse width were obtained when the compressor was driven by the 50 kW pulse power magnetron generator.

Avgustinovich, V. A.; Artemenko, S. N.; Novikov, S. A.; Yushkov, Yu. G. [Tomsk Polytechnic University, 2-a Lenina, Tomsk 634050 (Russian Federation)

2013-06-15T23:59:59.000Z

478

Driver expectancy in locating automotive controls  

E-Print Network [OSTI]

of the dimmer switch 150 3 lb Effect of age on expected location of the dimmer switch 150 31c Effect of years of driving experience on expected location of the dimmer switch. 151 31d Effect of miles driven in the past year on expected location... IOO. C Sn. i 36. 2 8/. 5 80. 0 87. 5 A=/0. 0 ZD. D 50. 0 0. 0 /0 D 12 5 2D. O 30. 0 0. 0 80. 0 80. 0 62 IDD. O 100. 0 10[. 0 Bn. o o. o 7. 5 20. 0 40. 0 37'. 5 85. 0 23 3 17. 5 16. / 74. 2 42. 5 SZ. 5 Climate C ntrol 17. 2 43. 0 36...

Francis, Dawn Suzette

1990-01-01T23:59:59.000Z

479

Leak locating microphone, method and system for locating fluid leaks in pipes  

DOE Patents [OSTI]

A leak detecting microphone inserted directly into fluid within a pipe includes a housing having a first end being inserted within the pipe and a second opposed end extending outside the pipe. A diaphragm is mounted within the first housing end and an acoustic transducer is coupled to the diaphragm for converting acoustical signals to electrical signals. A plurality of apertures are provided in the housing first end, the apertures located both above and below the diaphragm, whereby to equalize fluid pressure on either side of the diaphragm. A leak locating system and method are provided for locating fluid leaks within a pipe. A first microphone is installed within fluid in the pipe at a first selected location and sound is detected at the first location. A second microphone is installed within fluid in the pipe at a second selected location and sound is detected at the second location. A cross-correlation is identified between the detected sound at the first and second locations for identifying a leak location.

Kupperman, David S. (Oak Park, IL); Spevak, Lev (Highland Park, IL)

1994-01-01T23:59:59.000Z

480

Earthquake locations and seismic velocity models for Southern California  

E-Print Network [OSTI]

systems using a conjugate gradient method. We constrain thesuch as the conjugate gradient method are effective ineven when the conjugate gradient method is used to solve the

Lin, Guoqing

2007-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "model output location" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


481

Modeling and Solving Location Routing and Scheduling Problems  

E-Print Network [OSTI]

Oct 13, 2008 ... ... a standard approach for solving large-scale integer programming .... The algorithm fans out from the source node, repeatedly examining the.

2008-10-13T23:59:59.000Z

482

OPTIMAL LOCATION OF ISOLATION VALVES IN WATER  

E-Print Network [OSTI]

CHAPTER 7 OPTIMAL LOCATION OF ISOLATION VALVES IN WATER DISTRIBUTION SYSTEMS: A RELIABILITY systems to serve expanding population centers. Both the adaptation of existing technologies in water supply systems account for the largest cost item in future maintenance budgets. The aging

Mays, Larry W.

483

Recycling Bin Guide Locations and prices  

E-Print Network [OSTI]

Recycling Bin Guide Locations and prices Metal Bins Deskside Bins with Side Saddle Rubbermaid Bins.58 for auxiliaries. And Non-Public Areas Public Offices Non-Public Recyclables Recyclables RecyclablesTrash Trash Trash #12;New Recycling Bin Guidelines Frequently Asked Questions (as of December 2008) · Why

Kirschner, Denise

484

Exact Location : Date of Accident : AM PM  

E-Print Network [OSTI]

SSN Cell Phone Home Phone Work Phone Exact Location : Date of Accident : AM PM Date accident treatment provided? Yes No Where Was time lost from work? Yes No If yes, how long? Could this accident have the following information as soon as it relates to your work related accident/injury/illness within 72 hours

Swaddle, John

485

US-CERT Control System Center Input/Output (I/O) Conceputal Design  

SciTech Connect (OSTI)

This document was prepared for the US-CERT Control Systems Center of the National Cyber Security Division (NCSD) of the Department of Homeland Security (DHS). DHS has been tasked under the Homeland Security Act of 2002 to coordinate the overall national effort to enhance the protection of the national critical infrastructure. Homeland Security Presidential Directive HSPD-7 directs the federal departments to identify and prioritize critical infrastructure and protect it from terrorist attack. The US-CERT National Strategy for Control Systems Security was prepared by the NCSD to address the control system security component addressed in the National Strategy to Secure Cyberspace and the National Strategy for the Physical Protection of Critical Infrastructures and Key Assets. The US-CERT National Strategy for Control Systems Security identified five high-level strategic goals for improving cyber security of control systems; the I/O upgrade described in this document supports these goals. The vulnerability assessment Test Bed, located in the Information Operations Research Center (IORC) facility at Idaho National Laboratory (INL), consists of a cyber test facility integrated with multiple test beds that simulate the nation's critical infrastructure. The fundamental mission of the Test Bed is to provide industry owner/operators, system vendors, and multi-agency partners of the INL National Security Division a platform for vulnerability assessments of control systems. The Input/Output (I/O) upgrade to the Test Bed (see Work Package 3.1 of the FY-05 Annual Work Plan) will provide for the expansion of assessment capabilities within the IORC facility. It will also provide capabilities to connect test beds within the Test Range and other Laboratory resources. This will allow real time I/O data input and communication channels for full replications of control systems (Process Control Systems [PCS], Supervisory Control and Data Acquisition Systems [SCADA], and components). This will be accomplished through the design and implementation of a modular infrastructure of control system, communications, networking, computing and associated equipment, and measurement/control devices. The architecture upgrade will provide a flexible patching system providing a quick ''plug and play''configuration through various communication paths to gain access to live I/O running over specific protocols. This will allow for in-depth assessments of control systems in a true-to-life environment. The full I/O upgrade will be completed through a two-phased approach. Phase I, funded by DHS, expands the capabilities of the Test Bed by developing an operational control system in two functional areas, the Science & Technology Applications Research (STAR) Facility and the expansion of various portions of the Test Bed. Phase II (see Appendix A), funded by other programs, will complete the full I/O upgrade to the facility.

Not Available

2005-02-01T23:59:59.000Z

486

Handling Ambiguity via Input-Output Kernel Learning Xinxing Xu Ivor W. Tsang Dong Xu  

E-Print Network [OSTI]

of Computer Engineering, Nanyang Technological University, Singapore xuxi0006@ntu.edu.sg IvorTsang@ntu.edu.sg dongxu@ntu.edu.sg Abstract--Data ambiguities exist in many data mining and machine learning applications the effectiveness of our proposed IOKL framework. Keywords-Group Multiple Kernel Learning; Input-Output Kernel

Tsang Wai Hung "Ivor"

487

SOLAR ENERGY (conditionally accepted 1/2010) QUANTIFYING PV POWER OUTPUT VARIABILITY  

E-Print Network [OSTI]

SOLAR ENERGY (conditionally accepted 1/2010) QUANTIFYING PV POWER OUTPUT VARIABILITY Thomas E create major problems that will require major mitigation efforts. #12;SOLAR ENERGY (conditionally industry believe it could constrain the penetration of gridconnected PV. The U.S. Department of Energy

Perez, Richard R.

488

Improved thermoelectric power output from multilayered polyethylenimine doped carbon nanotube based organic composites  

SciTech Connect (OSTI)

By appropriately selecting the carbon nanotube type and n-type dopant for the conduction layers in a multilayered carbon nanotube composite, the total device thermoelectric power output can be increased significantly. The particular materials chosen in this study were raw single walled carbon nanotubes for the p-type layers and polyethylenimine doped single walled carbon nanotubes for the n-type layers. The combination of these two conduction layers leads to a single thermocouple Seebeck coefficient of 96 4??VK{sup ?1}, which is 6.3 times higher than that previously reported. This improved Seebeck coefficient leads to a total power output of 14.7 nW per thermocouple at the maximum temperature difference of 50?K, which is 44 times the power output per thermocouple for the previously reported results. Ultimately, these thermoelectric power output improvements help to increase the potential use of these lightweight, flexible, and durable organic multilayered carbon nanotube based thermoelectric modules in low powered electronics applications, where waste heat is available.

Hewitt, Corey A.; Montgomery, David S.; Barbalace, Ryan L.; Carlson, Rowland D.; Carroll, David L., E-mail: carroldl@wfu.edu [Center for Nanotechnology and Molecular Materials, Wake Forest University, 501 Deacon Blvd., Winston Salem, North Carolina 27105 (United States)

2014-05-14T23:59:59.000Z

489

The effects of energy policies in China on GDP, industrial output and new energy profits1  

E-Print Network [OSTI]

1 The effects of energy policies in China on GDP, industrial output and new energy profits1 Ming-Jie Lu, C.-Y. Cynthia Lin and Song Chen Abstract This paper examines the effects of energy policies and the profits of new energy companies using instruments to address the potential endogeneity of the policies

Lin, C.-Y. Cynthia

490

Uni-Traveling-Carrier Photodiodes with Increased Output Response and Low Intermodulation  

E-Print Network [OSTI]

Uni-Traveling-Carrier Photodiodes with Increased Output Response and Low Intermodulation Distortion-traveling-carrier photodiodes have been fabricated and tested to investigate the influence of the doping profile in several of the device layers on saturation characteristics and linearity. Two particular photodiode (PD) structures

Bowers, John

491

THE EFFECTS OF NET ENTANGLEMENT ON THE DRAG AND POWER OUTPUT OF  

E-Print Network [OSTI]

THE EFFECTS OF NET ENTANGLEMENT ON THE DRAG AND POWER OUTPUT OF A CALIFORNIA SEA LION, ZAWPHUS of entangled northern fur 'Scordino. J., and R. Fisher. 1983. Invelltigations on fur seal entanglement in net of plastic litter on beaches of several Alaskan islands. Using the number of net fragments found on shore

492

Development of Regional Wind Resource and Wind Plant Output Datasets for the Hawaiian Islands  

SciTech Connect (OSTI)

In March 2009, AWS Truepower was engaged by the National Renewable Energy Laboratory (NREL) to develop a set of wind resource and plant output data for the Hawaiian Islands. The objective of this project was to expand the methods and techniques employed in the Eastern Wind Integration and Transmission Study (EWITS) to include the state of Hawaii.

Manobianco, J.; Alonge, C.; Frank, J.; Brower, M.

2010-07-01T23:59:59.000Z

493

On the Impact of Partial Shading on PV Output Power DEZSO SERA YAHIA BAGHZOUZ  

E-Print Network [OSTI]

On the Impact of Partial Shading on PV Output Power DEZSO SERA YAHIA BAGHZOUZ Institute of Energy the inflation adjusted cost of PV energy has declined by roughly by a factor of 2 over the same time period [3 power capability. However, the relative amount of such degradation in energy production cannot

Sera, Dezso

494

A comparison between raw EPS output, (modied) BMA and extended LR using ECMWF EPS precipitation reforecasts  

E-Print Network [OSTI]

A comparison between raw EPS output, (modied) BMA and extended LR using ECMWF EPS precipitation (EPS). 2. Data sets, statistical methods and predictand denitions The data sets used in this study [1 and precipitation data from a reforecasting exper- iment with the ECMWF EPS system. Figure 1: BMA-tted pdf of 24-h

Schmeits, Maurice

495

Increasing the output of a Littman-type laser by use of an intracavity Faraday rotator  

E-Print Network [OSTI]

are readily available at a variety of wavelengths from the red to the near infrared. They require their advantages. The sim- pler of the two designs is the Littrow scheme. In this arrangement a reflection grating. The zeroth- order grating reflection is used as the output coupler to extract light from the cavity. Light

Hart, Gus

496

Work output of planetary atmospheric engines: dissipation in clouds and rain  

E-Print Network [OSTI]

not provide enough work to lift the condensate against gravity. INDEX TERMS: 0343 Atmospheric Composition as the original function of steam engines was to lift water, a principal output of the atmospheric heat engine (the average surface temperature of 288K) and ÁT $38K, the difference between T and the effective

Lorenz, Ralph D.

497

SHORT TERM PREDICTIONS FOR THE POWER OUTPUT OF ENSEMBLES OF WIND TURBINES AND PV-GENERATORS  

E-Print Network [OSTI]

SHORT TERM PREDICTIONS FOR THE POWER OUTPUT OF ENSEMBLES OF WIND TURBINES AND PV-GENERATORS Hans. For the conventional power park, the power production of the wind turbines presents a fluctuating 'negative load PRODUCTION OF WIND TURBINES For the forecast of the power production of wind turbines two approaches may

Heinemann, Detlev

498

The sound power output of a monopole source in a cylindrical pipe containing area discontinuities  

E-Print Network [OSTI]

The sound power output of a monopole source in a cylindrical pipe containing area discontinuities W placed close to a pipe discontinuity. It is found that while the sound power of a monopole source in free pipe is constant in the plane wave region. A sharp increase in sound power is then seen to occur when

Boyer, Edmond

499

Nuclear norm system identification with missing inputs and outputs Zhang Liua,  

E-Print Network [OSTI]

Nuclear norm system identification with missing inputs and outputs Zhang Liua, , Anders Hanssonb,1 formulation and uses the nuclear norm heuristic for structured low-rank matrix approximation, with the missing of the alternating direc- tion method of multipliers (ADMM) to solve regularized or non-regularized nuclear norm

Vandenberghe, Lieven

500

Closed-loop identification via output fast sampling Jiandong Wang a  

E-Print Network [OSTI]

Closed-loop identification via output fast sampling Jiandong Wang a , Tongwen Chen a,*, Biao Huang6G 2V4 b Department of Chemical and Materials Engineering, University of Alberta, Edmonton, AB identifiable? The so-called fast-sampling direct approach provides a positive answer. It removes a traditional

Wang, Jiandong