Sample records for raven corvus corax

  1. The Effects of Site Characterization Activities on the Abundance of Ravens (Corvus corax) in the Yucca Mountain Area

    SciTech Connect (OSTI)

    P.E. Lederle

    1998-05-08T23:59:59.000Z

    In response to the Nuclear Waste Policy Act of 1982 and the Nuclear Waste Policy Amendments Act of 1987, the U.S. Department of Energy (DOE) developed and is implementing the Yucca Mountain Site Characterization Project. Raven abundance was measured from August 1991 through August 1995 along treatment and control routes to evaluate whether site characterization activities resulted in increased raven abundance at Yucca Mountain. This study fulfills the requirement set forth in the incidental take provisions of the Biological Opinion that DOE monitor the abundance of ravens at Yucca Mountain. Ravens were more abundant at Yucca Mountain than in the control area, and raven abundance in both areas increased over time. However, the magnitude of differences between Yucca Mountain and control surveys did not change over time, indicating that the increase in raven abundance observed during this study was not related to site characterization activities. Increases over time on both Yucca Mountain and control routes are consistent with increases in raven abundance in the Mojave Desert reported by the annual Breeding Bird Survey of the US. Fish and Wildlife Service. Evidence from the Desert Tortoise Monitoring Program at Yucca Mountain suggests that ravens are not a significant predator of small tortoises in this locale. Carcasses of small tortoises (less than 110 mm in length) collected during the study showed little evidence of raven predation, and 59 radiomarked hatchlings that were monitored on a regular basis were not preyed upon by ravens. Overall, no direct evidence of raven predation on tortoises was observed during this study. Small tortoises are probably encountered so infrequently by ravens that they are rarely exploited as a food source. This is likely due to the relatively low abundance of both desert tortoises and ravens in the Yucca Mountain area.

  2. Effects of Electromagnetic Fields on the Reproductive Success of American Kestrels

    E-Print Network [OSTI]

    Dawson, Russell D.

    lines and towers are beneficial to birds, pro- viding additional sites for perching, hunting of raptors and ravens (Corvus corax) nest- ing on a 500-kV transmission line was similar to or higher than

  3. Raven Technology | Open Energy Information

    Open Energy Info (EERE)

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag JumpID-f < RAPID‎ | Roadmap Jump to:bJump to: navigation, searchRaven

  4. Dynamic Event Tree Analysis Through RAVEN

    SciTech Connect (OSTI)

    A. Alfonsi; C. Rabiti; D. Mandelli; J. Cogliati; R. A. Kinoshita; A. Naviglio

    2013-09-01T23:59:59.000Z

    Conventional Event-Tree (ET) based methodologies are extensively used as tools to perform reliability and safety assessment of complex and critical engineering systems. One of the disadvantages of these methods is that timing/sequencing of events and system dynamics is not explicitly accounted for in the analysis. In order to overcome these limitations several techniques, also know as Dynamic Probabilistic Risk Assessment (D-PRA), have been developed. Monte-Carlo (MC) and Dynamic Event Tree (DET) are two of the most widely used D-PRA methodologies to perform safety assessment of Nuclear Power Plants (NPP). In the past two years, the Idaho National Laboratory (INL) has developed its own tool to perform Dynamic PRA: RAVEN (Reactor Analysis and Virtual control ENvironment). RAVEN has been designed in a high modular and pluggable way in order to enable easy integration of different programming languages (i.e., C++, Python) and coupling with other application including the ones based on the MOOSE framework, developed by INL as well. RAVEN performs two main tasks: 1) control logic driver for the new Thermo-Hydraulic code RELAP-7 and 2) post-processing tool. In the first task, RAVEN acts as a deterministic controller in which the set of control logic laws (user defined) monitors the RELAP-7 simulation and controls the activation of specific systems. Moreover, RAVEN also models stochastic events, such as components failures, and performs uncertainty quantification. Such stochastic modeling is employed by using both MC and DET algorithms. In the second task, RAVEN processes the large amount of data generated by RELAP-7 using data-mining based algorithms. This paper focuses on the first task and shows how it is possible to perform the analysis of dynamic stochastic systems using the newly developed RAVEN DET capability. As an example, the Dynamic PRA analysis, using Dynamic Event Tree, of a simplified pressurized water reactor for a Station Black-Out scenario is presented.

  5. Performing Probabilistic Risk Assessment Through RAVEN

    SciTech Connect (OSTI)

    A. Alfonsi; C. Rabiti; D. Mandelli; J. Cogliati; R. Kinoshita

    2013-06-01T23:59:59.000Z

    The Reactor Analysis and Virtual control ENviroment (RAVEN) code is a software tool that acts as the control logic driver and post-processing engine for the newly developed Thermal-Hydraulic code RELAP-7. RAVEN is now a multi-purpose Probabilistic Risk Assessment (PRA) software framework that allows dispatching different functionalities: Derive and actuate the control logic required to simulate the plant control system and operator actions (guided procedures), allowing on-line monitoring/controlling in the Phase Space Perform both Monte-Carlo sampling of random distributed events and Dynamic Event Tree based analysis Facilitate the input/output handling through a Graphical User Interface (GUI) and a post-processing data mining module

  6. DAKOTA reliability methods applied to RAVEN/RELAP-7.

    SciTech Connect (OSTI)

    Swiler, Laura Painton; Mandelli, Diego [Idaho National Laboratory, Idaho Falls, ID; Rabiti, Cristian [Idaho National Laboratory, Idaho Falls, ID; Alfonsi, Andrea [Idaho National Laboratory, Idaho Falls, ID

    2013-09-01T23:59:59.000Z

    This report summarizes the result of a NEAMS project focused on the use of reliability methods within the RAVEN and RELAP-7 software framework for assessing failure probabilities as part of probabilistic risk assessment for nuclear power plants. RAVEN is a software tool under development at the Idaho National Laboratory that acts as the control logic driver and post-processing tool for the newly developed Thermal-Hydraulic code RELAP-7. Dakota is a software tool developed at Sandia National Laboratories containing optimization, sensitivity analysis, and uncertainty quantification algorithms. Reliability methods are algorithms which transform the uncertainty problem to an optimization problem to solve for the failure probability, given uncertainty on problem inputs and a failure threshold on an output response. The goal of this work is to demonstrate the use of reliability methods in Dakota with RAVEN/RELAP-7. These capabilities are demonstrated on a demonstration of a Station Blackout analysis of a simplified Pressurized Water Reactor (PWR).

  7. RAVEN, a New Software for Dynamic Risk Analysis

    SciTech Connect (OSTI)

    Cristian Rabiti; Andrea Alfonsi; Joshua Cogliati; Diego Mandelli; Robert Kinoshita

    2014-06-01T23:59:59.000Z

    RAVEN is a generic software driver to perform parametric and probabilistic analysis of code simulating complex systems. Initially developed to provide dynamic risk analysis capabilities to the RELAP-7 code [1] is currently being generalized with the addition of Application Programming Interfaces (APIs). These interfaces are used to extend RAVEN capabilities to any software as long as all the parameters that need to be perturbed are accessible by inputs files or directly via python interfaces. RAVEN is capable to investigate the system response probing the input space using Monte Carlo, grid strategies, or Latin Hyper Cube schemes, but its strength is its focus toward system feature discovery like limit surfaces separating regions of the input space leading to system failure using dynamic supervised learning techniques. The paper will present an overview of the software capabilities and their implementation schemes followed by same application examples.

  8. Implementation of Stochastic Polynomials Approach in the RAVEN Code

    SciTech Connect (OSTI)

    Cristian Rabiti; Paul Talbot; Andrea Alfonsi; Diego Mandelli; Joshua Cogliati

    2013-10-01T23:59:59.000Z

    RAVEN, under the support of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, has been tasked to provide the necessary software and algorithms to enable the application of the conceptual framework developed by the Risk Informed Safety Margin Characterization (RISMC) [1] path. RISMC is one of the paths defined under the Light Water Reactor Sustainability (LWRS) DOE program.

  9. RAVEN and Dynamic Probabilistic Risk Assessment: Software overview

    SciTech Connect (OSTI)

    Andrea Alfonsi; Cristian Rabiti; Diego Mandelli; Joshua Cogliati; Robert Kinoshita; Antonio Naviglio

    2014-06-01T23:59:59.000Z

    RAVEN is a generic software framework to perform parametric and probabilistic analysis based on the response of complex system codes. The initial development was aimed to provide dynamic risk analysis capabilities to the Thermo-Hydraulic code RELAP-7 [], currently under development at the Idaho National Laboratory. Although the initial goal has been fully accomplished, RAVEN is now a multi-purpose probabilistic and uncertainty quantification platform, capable to agnostically communicate with any system code. This agnosticism has been employed by providing Application Programming Interfaces (APIs). These interfaces are used to allow RAVEN to interact with any code as long as all the parameters that need to be perturbed are accessible by inputs files or via python interfaces. RAVEN is capable to investigate the system response, investigating the input space using Monte Carlo, Grid, or Latin Hyper Cube sampling schemes, but its strength is focused toward system feature discovery, such as limit surfaces, separating regions of the input space leading to system failure, using dynamic supervised learning techniques. The paper presents an overview of the software capabilities and their implementation schemes followed by some application examples.

  10. RAVEN: Dynamic Event Tree Approach Level III Milestone

    SciTech Connect (OSTI)

    Andrea Alfonsi; Cristian Rabiti; Diego Mandelli; Joshua Cogliati; Robert Kinoshita

    2013-07-01T23:59:59.000Z

    Conventional Event-Tree (ET) based methodologies are extensively used as tools to perform reliability and safety assessment of complex and critical engineering systems. One of the disadvantages of these methods is that timing/sequencing of events and system dynamics are not explicitly accounted for in the analysis. In order to overcome these limitations several techniques, also know as Dynamic Probabilistic Risk Assessment (DPRA), have been developed. Monte-Carlo (MC) and Dynamic Event Tree (DET) are two of the most widely used D-PRA methodologies to perform safety assessment of Nuclear Power Plants (NPP). In the past two years, the Idaho National Laboratory (INL) has developed its own tool to perform Dynamic PRA: RAVEN (Reactor Analysis and Virtual control ENvironment). RAVEN has been designed to perform two main tasks: 1) control logic driver for the new Thermo-Hydraulic code RELAP-7 and 2) post-processing tool. In the first task, RAVEN acts as a deterministic controller in which the set of control logic laws (user defined) monitors the RELAP-7 simulation and controls the activation of specific systems. Moreover, the control logic infrastructure is used to model stochastic events, such as components failures, and perform uncertainty propagation. Such stochastic modeling is deployed using both MC and DET algorithms. In the second task, RAVEN processes the large amount of data generated by RELAP-7 using data-mining based algorithms. This report focuses on the analysis of dynamic stochastic systems using the newly developed RAVEN DET capability. As an example, a DPRA analysis, using DET, of a simplified pressurized water reactor for a Station Black-Out (SBO) scenario is presented.

  11. REACTOR ANALYSIS AND VIRTUAL CONTROL ENVIRONMENT (RAVEN) FY12 REPORT

    SciTech Connect (OSTI)

    Cristian Rabiti; Andrea Alfonsi; Joshua Cogliati; Diego Mandelli; Robert Kinoshita

    2012-09-01T23:59:59.000Z

    RAVEN is a complex software tool that will have tasks spanning from being the RELAP-7 user interface, to using RELAP-7 to perform Risk Informed Safety Characterization (RISMC), and to controlling RELAP-7 calculation execution. The goal of this document is to: 1. Highlight the functional requirements of the different tasks of RAVEN 2. Identify shared functions that could be aggregate in modules so to obtain a minimal software redundancy and maximize software utilization. RAVEN is in fact a software framework that will allow exploiting the following functionalities: • Derive and actuate the control logic required to: o Simulate the plant control system o Simulate the operator (procedure guided) actions o Perform Monte Carlo sampling of random distributed events o Perform event three based analysis • Provide a GUI to: o Input a plant description to RELAP-7 (component, control variable, control parameters) o Concurrent monitoring of Control Parameters o Concurrent alteration of control parameters • Provide Post Processing data mining capability based on o Dimensionality reduction o Cardinality reduction In this document it will be shown how an appropriate mathematical formulation of the control logic and probabilistic analysis leads to have most of the software infrastructure leveraged between the two main tasks. Further, this document will go through the development accomplished this year, including simulation results, and priorities for the next years development

  12. Raven IITM: Open Platform for Surgical Robotics Research H. Hawkeye King1

    E-Print Network [OSTI]

    Rosen, Jacob

    of Cartesian motion and grasping [6]. A unique feature of the tool is a wrist design that eliminates cableRaven IITM: Open Platform for Surgical Robotics Research H. Hawkeye King1 , Lei Cheng1 , Philip In this paper we present a new platform for surgical robotics research: the Raven IITM. The goal of this work

  13. MATHEMATICAL FRAMEWORK FOR THE ANALYSIS OF DYNAMC STOCHASTIC SYSTEMS WITH THE RAVEN CODE

    SciTech Connect (OSTI)

    C. Rabiti; D. Mandelli; J. Cogliati; R. Kinoshita

    2013-05-01T23:59:59.000Z

    RAVEN (Reactor Analysis and Virtual control Environment) is a software code under development at Idaho National Laboratory aimed at performing probabilistic risk assessment and uncertainty quantification using RELAP-7, for which it acts also as a simulation controller. In this paper we will present the equations characterizing a dynamic stochastic system and we will then discuss the behavior of each stochastic term and how it is accounted for in the RAVEN software design. Moreover we will present preliminary results of the implementation.

  14. A Paen to Sanguinity (a song) by RavenKelVamp

    E-Print Network [OSTI]

    2007-02-16T23:59:59.000Z

    Grey Bard wrote in mdmfans, 2007-02-16 00:12:00 A Paen to Sanguinity (a song) by RavenKelVamp Metanote: Dammit. Not two months in this fandom and I'm writing crackfilk in the persona of a swoony vampire lover. Why is this my life...

  15. RAVEN AS A TOOL FOR DYNAMIC PROBABILISTIC RISK ASSESSMENT: SOFTWARE OVERVIEW

    SciTech Connect (OSTI)

    Alfonsi Andrea; Mandelli Diego; Rabiti Cristian; Joshua Cogliati; Robert Kinoshita

    2013-05-01T23:59:59.000Z

    RAVEN is a software tool under development at the Idaho National Laboratory (INL) that acts as the control logic driver and post-processing tool for the newly developed Thermo-Hydraylic code RELAP- 7. The scope of this paper is to show the software structure of RAVEN and its utilization in connection with RELAP-7. A short overview of the mathematical framework behind the code is presented along with its main capabilities such as on-line controlling/monitoring and Monte-Carlo sampling. A demo of a Station Black Out PRA analysis of a simplified Pressurized Water Reactor (PWR) model is shown in order to demonstrate the Monte-Carlo and clustering capabilities.

  16. RAVEN: a GUI and an Artificial Intelligence Engine in a Dynamic PRA Framework

    SciTech Connect (OSTI)

    C. Rabiti; D. Mandelli; A. Alfonsi; J. Cogliati; R. Kinoshita; D. Gaston; R. Martineau; C. Curtis

    2013-06-01T23:59:59.000Z

    Increases in computational power and pressure for more accurate simulations and estimations of accident scenario consequences are driving the need for Dynamic Probabilistic Risk Assessment (PRA) [1] of very complex models. While more sophisticated algorithms and computational power address the back end of this challenge, the front end is still handled by engineers that need to extract meaningful information from the large amount of data and build these complex models. Compounding this problem is the difficulty in knowledge transfer and retention, and the increasing speed of software development. The above-described issues would have negatively impacted deployment of the new high fidelity plant simulator RELAP-7 (Reactor Excursion and Leak Analysis Program) at Idaho National Laboratory. Therefore, RAVEN that was initially focused to be the plant controller for RELAP-7 will help mitigate future RELAP-7 software engineering risks. In order to accomplish this task, Reactor Analysis and Virtual Control Environment (RAVEN) has been designed to provide an easy to use Graphical User Interface (GUI) for building plant models and to leverage artificial intelligence algorithms in order to reduce computational time, improve results, and help the user to identify the behavioral pattern of the Nuclear Power Plants (NPPs). In this paper we will present the GUI implementation and its current capability status. We will also introduce the support vector machine algorithms and show our evaluation of their potentiality in increasing the accuracy and reducing the computational costs of PRA analysis. In this evaluation we will refer to preliminary studies performed under the Risk Informed Safety Margins Characterization (RISMC) project of the Light Water Reactors Sustainability (LWRS) campaign [3]. RISMC simulation needs and algorithm testing are currently used as a guidance to prioritize RAVEN developments relevant to PRA.

  17. Methodology for the Incorporation of Passive Component Aging Modeling into the RAVEN/ RELAP-7 Environment

    SciTech Connect (OSTI)

    Mandelli, Diego; Rabiti, Cristian; Cogliati, Joshua; Alfonsi, Andrea; Askin Guler; Tunc Aldemir

    2014-11-01T23:59:59.000Z

    Passive system, structure and components (SSCs) will degrade over their operation life and this degradation may cause to reduction in the safety margins of a nuclear power plant. In traditional probabilistic risk assessment (PRA) using the event-tree/fault-tree methodology, passive SSC failure rates are generally based on generic plant failure data and the true state of a specific plant is not reflected realistically. To address aging effects of passive SSCs in the traditional PRA methodology [1] does consider physics based models that account for the operating conditions in the plant, however, [1] does not include effects of surveillance/inspection. This paper represents an overall methodology for the incorporation of aging modeling of passive components into the RAVEN/RELAP-7 environment which provides a framework for performing dynamic PRA. Dynamic PRA allows consideration of both epistemic and aleatory uncertainties (including those associated with maintenance activities) in a consistent phenomenological and probabilistic framework and is often needed when there is complex process/hardware/software/firmware/ human interaction [2]. Dynamic PRA has gained attention recently due to difficulties in the traditional PRA modeling of aging effects of passive components using physics based models and also in the modeling of digital instrumentation and control systems. RAVEN (Reactor Analysis and Virtual control Environment) [3] is a software package under development at the Idaho National Laboratory (INL) as an online control logic driver and post-processing tool. It is coupled to the plant transient code RELAP-7 (Reactor Excursion and Leak Analysis Program) also currently under development at INL [3], as well as RELAP 5 [4]. The overall methodology aims to: • Address multiple aging mechanisms involving large number of components in a computational feasible manner where sequencing of events is conditioned on the physical conditions predicted in a simulation environment such as RELAP-7. • Identify the risk-significant passive components, their failure modes and anticipated rates of degradation • Incorporate surveillance and maintenance activities and their effects into the plant state and into component aging progress. • Asses aging affects in a dynamic simulation environment 1. C. L. SMITH, V. N. SHAH, T. KAO, G. APOSTOLAKIS, “Incorporating Ageing Effects into Probabilistic Risk Assessment –A Feasibility Study Utilizing Reliability Physics Models,” NUREG/CR-5632, USNRC, (2001). 2. T. ALDEMIR, “A Survey of Dynamic Methodologies for Probabilistic Safety Assessment of Nuclear Power Plants, Annals of Nuclear Energy, 52, 113-124, (2013). 3. C. RABITI, A. ALFONSI, J. COGLIATI, D. MANDELLI and R. KINOSHITA “Reactor Analysis and Virtual Control Environment (RAVEN) FY12 Report,” INL/EXT-12-27351, (2012). 4. D. ANDERS et.al, "RELAP-7 Level 2 Milestone Report: Demonstration of a Steady State Single Phase PWR Simulation with RELAP-7," INL/EXT-12-25924, (2012).

  18. Light Water Reactor Sustainability Program Support and Modeling for the Boiling Water Reactor Station Black Out Case Study Using RELAP and RAVEN

    SciTech Connect (OSTI)

    Diego Mandelli; Curtis Smith; Thomas Riley; John Schroeder; Cristian Rabiti; Aldrea Alfonsi; Joe Nielsen; Dan Maljovec; Bie Wang; Valerio Pascucci

    2013-09-01T23:59:59.000Z

    The existing fleet of nuclear power plants is in the process of extending its lifetime and increasing the power generated. In order to evaluate the impact of these two factors on the safety of the plant, the Risk Informed Safety Margin Characterization (RISMC) project aims to provide insight to decision makers through a series of simulations of the plant dynamics for different initial conditions (e.g., probabilistic analysis and uncertainty quantification). This report focuses, in particular, on the impact of power uprate on the safety of a boiled water reactor system. The case study considered is a loss of off-site power followed by the loss of diesel generators, i.e., a station black out (SBO) event. Analysis is performed by using a thermo-hydraulic code, i.e. RELAP-5, and a stochastic analysis tool currently under development at INL, i.e. RAVEN. Starting from the event tree models contained in SAPHIRE, we built the input file for RELAP-5 that models in great detail system dynamics under SBO conditions. We also interfaced RAVEN with RELAP-5 so that it would be possible to run multiple RELAP-5 simulation runs by changing specific keywords of the input file. We both employed classical statistical tools, i.e. Monte-Carlo, and more advanced machine learning based algorithms to perform uncertainty quantification in order to quantify changes in system performance and limitations as a consequence of power uprate. We also employed advanced data analysis and visualization tools that helped us to correlate simulation outcome such as maximum core temperature with a set of input uncertain parameters. Results obtained gave a detailed overview of the issues associated to power uprate for a SBO accident scenario. We were able to quantify how timing of safety related events were impacted by a higher reactor core power. Such insights can provide useful material to the decision makers to perform risk-infomed safety margins management.

  19. letters to nature 70 NATURE |VOL 390 |6 NOVEMBER 1997

    E-Print Network [OSTI]

    Laurent, Gilles

    letters to nature 70 NATURE |VOL 390 |6 NOVEMBER 1997 Received 11 June; accepted 11 August 1997. 1 and energy cost of flight in the white-necked raven, Corvus cryptoleucus. J. Exp. Biol. 103, 121­130 (1983, W. & Nachtigall, W. Pigeon flight in a wind tunnel. II. Gas exchange and power requirements. J. Comp

  20. Brain Parasite in White-Necked Raven

    E-Print Network [OSTI]

    Austin Paul Smith Journal:  Condor Volume:  10 Issue:  2 (March-April) Section:  From Field and Study Year:  1908 Pages:  92

  1. Raven Biofuels International Corporation | Open Energy Information

    Open Energy Info (EERE)

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro Industries Pvt Ltd Jump to: navigation, search Name:RanciaRappahannockCounty, Montana:

  2. RavenBrick LLC | Open Energy Information

    Open Energy Info (EERE)

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro Industries Pvt Ltd Jump to: navigation, search Name:RanciaRappahannockCounty,

  3. Power Pole Casualties Among Raptors and Ravens an Northwestern Chihuahua, Mexico

    E-Print Network [OSTI]

    Jean-Luc E. Cartron, Gail L. Garber, Carol Finley, Christopher Rustay, Ron Kellermueller, Mary Pat Day, Patricia Manzano-Fisher, Scott H. Stoleson ...

  4. RAVEN as Control Logic and Probabilistic Risk Assessment Driver for RELAP-7

    SciTech Connect (OSTI)

    C. Rabiti; A. Alfonsi; D. Mandelli; J. Cogliati; R. Martineau

    2012-11-01T23:59:59.000Z

    The Next Generation of System Analysis Code (NGSAC) [1] aims to model and simulate the Nuclear Power Plant (NPP) thermo-hydraulic behavior with high level of accuracy. In this respect, Idaho National Laboratory (INL) is developing a NGSAC (known as RELAP-7) which will allow to model NPP responses for a set of accident scenarios (e.g., loss of off-site power).

  5. affecting clinical results: Topics by E-print Network

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

    Michigan State University, MI, USA INTRODUCTION Global biodiversity continues along a trajectory of the most biodiversity-rich countries in the world (Liu and Raven, 2010;...

  6. Ibis (2006), 148, 174178 2006 The Authors

    E-Print Network [OSTI]

    Machery, Edouard

    2006-01-01T23:59:59.000Z

    ? Short communication mtDNA of Canary Island RavensJ. M. Baker & K. E. OmlandShort communication Canary. It is restricted to the Canary Islands and Morocco and can be distinguished by its size and `oily' plumage gloss (Madge & Burn 1994). This study focuses on the island populations, which we term the `Canary Island Raven

  7. HumanWildlife Conflicts 1(2):224234, Fall 2007 Efficacy of CPTH-treated egg baits for

    E-Print Network [OSTI]

    ), lambing sites (Larsen and Dietrich 1970), rangelands (Knight 1984), and linear right-of-ways of electric. 2004). Ravens often use electrical transmission towers, highway overpasses, and railroad trestles power transmission lines (Knight and Kawashima 1993). Raven abundance has tripled in the past 40 years

  8. Host conservatism, host shifts and diversification across three trophic levels in two Neotropical forests

    E-Print Network [OSTI]

    Papaj, Daniel

    adaptive radiations (Ehrlich & Raven, 1964; Sch- luter, 2000). Evidence for the importance of major host. The moth­plant associations in particular are characterized by small radiations of moths associated

  9. Host conservatism, host shifts and diversification across three trophic levels in two Neotropical forests

    E-Print Network [OSTI]

    Feldman, Chris R

    adaptive radiations (Ehrlich & Raven, 1964; Sch- luter, 2000). Evidence for the importance of major host are characterized by small radiations of moths associated with unique host plants in the same geographic area (i

  10. Obedience Robins of Accomack: 17th-century strategies for success 

    E-Print Network [OSTI]

    Wilheit, Mary Catherine

    1997-01-01T23:59:59.000Z

    the most harmless, are now become so ravenous, that they begin to devour men, waste fields, and depopulate houses, if not whole Townships, as one merrily hath written. "' Richard (I) Robins's 1582 will' which established a pattern of inheritance...

  11. Execration Ritual

    E-Print Network [OSTI]

    Muhlestein, Kerry

    2008-01-01T23:59:59.000Z

    valuable discussions of wax as an object of manipulation inChristopher 1993 Molten wax, spilt wine, and mutilatedÉlisabeth. Raven, Maarten 1983 Wax in Egyptian magic and

  12. SOUTH CARIBOO 2007 Williams Lake

    E-Print Network [OSTI]

    Northern British Columbia, University of

    Program Kelly Bryan Raven Bursary Sarah Doucet UNBC Scholars Program Blake Forde UNBC Scholars Program Nations Scholarship, CanWest Global Communications Undergraduate Bursary Ben Vinje Gary Johnson Memorial

  13. Virus constructed iron phosphate lithium ion batteries in unmanned aircraft systems

    E-Print Network [OSTI]

    Kolesnikov-Lindsey, Rachel

    FePO? lithium ion batteries that have cathodes constructed by viruses are scaled up in size to examine potential for use as an auxiliary battery in the Raven to power the payload equipment. These batteries are assembled ...

  14. Scuttlebutt Volume 1, No. 3

    E-Print Network [OSTI]

    2007-01-01T23:59:59.000Z

    Awards Contents: 1. From the Bridge. 2. Announcing the 2006, Southern Cross, Chapter Awards 4. From The Raven?s Writing Desk - Editorial 4. Attention All Hands - From the XOs Desk Operations 5. Academy courses and new members 6. Ops news, Change... of Command, Academy 7. Club 360, Star Trek: Legacy Tactical/Security 8. Away Team Report: FirstContact Convention 9. Region 11 Convention Listing Communications 10. The "Re-Mastered" Star Trek Q & A Engineering 12 Star Trek Technology - Well Ahead...

  15. Comparative study of nitrogen assimilation in woodland J. Pearson, E.C.M. Clough J.L. Kershaw

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    to acid rain a particular tree spe- cies might be. A low capacity for leaf nitro- gen assimilation may, Such pools might repre- sent an important buffering capacity in relation to acid rain inputs (Raven, 1988). #12;Certainly, of the broad leaf trees, it seems that recent reports for acid rain damage are becoming

  16. NEAMSUpdate Quarterly report for July September 2013 Published December 2013

    E-Print Network [OSTI]

    Kemner, Ken

    capa- bilities to model metallic and oxide fuels for sodium fast reactors (SFRs), TRISO-coated particle fission gas behavior, fuel cracking, and nucleation (page 3). } SHARP performed a multiphysics simulation cross-section libraries (page 5). } The Reactor Analysis and Virtual Control Environment (RAVEN

  17. Laboratory tests on cruise data sample

    E-Print Network [OSTI]

    hauckii Algal Bloom in Fishery, China Inorganic Carbon Acquisition by Eukaryotic Cell: Diatoms Raven J. A. et al, Phil. Trans. R. Soc. B 2008 Inorganic Carbon Acquisition by Prokaryotic Cell: Cyanobacteria Nutrient-Poor Waters (Oligotrophic) Nutrient- Rich Waters (Eutrophic) CCMs Down Regulation for carbon

  18. Inn vati ns at EECS: Techn l gy f r a gl bal future

    E-Print Network [OSTI]

    California at Irvine, University of

    with Resiliency and Efficiency Lab) & BWRC (Berkeley Wireless Research Center) · Customized 3D Printed Implants - Peter Bailis, AMPLab (Algorithms, Machines, and People Laboratory) · Raven: An Energy Wireless Research Center) & E3S (Center for Energy Efficient Electronics Science) · Occupant Detection

  19. References R-3 Note: In this report we refer to a number of documents (e.g., plans, reports) that are intended for

    E-Print Network [OSTI]

    Pennycook, Steve

    . Operational Monitoring Plan for the High Flux Isotope Reactor Site: Final Design. Oak Ridge National-012529/1. BWXT Y-12, LLC, Oak Ridge, Tennessee. Chan, P. K., G. P. O'Hara, and A. W. Hayes. 1982. "Principles and Methods for Acute and Subchronic Toxicity." Principles and Methods of Toxicology. Raven Press, New York

  20. References R-3 Note: In this report we refer to a number of documents (e.g., plans, reports) that are intended for internal

    E-Print Network [OSTI]

    Pennycook, Steve

    . 2008. Summary of Groundwater Monitoring Activities at the High Flux Isotope Reactor Site: Final Report and Applied Meteorology 25, 1088­99. Chan, P. K., G. P. O'Hara, and A. W. Hayes. 1982. "Principles and Methods for Acute and Subchronic Toxicity." Principles and Methods of Toxicology. Raven Press, New York. DOE. 1989

  1. MIT and the Aerospace Industry MIT Industry Brief

    E-Print Network [OSTI]

    Ceder, Gerbrand

    is RAVEN (Real-time indoor Autonomous Vehicle test ENviron- ment), a unique experimental facility that uses · Human-vehicle interactions / systems · Space vehicles and robotics · Energy use, environmental impact in combustion systems, supersonic impinging jets, and blade tonals in underwater vehicles; active

  2. Abstract The grey top-shell, Gibbula cineraria is a common member of temperate to cold water kelp forest

    E-Print Network [OSTI]

    Schöne, Bernd R.

    Abstract The grey top-shell, Gibbula cineraria is a common member of temperate to cold water kelp and potential paleoenvironmental proxy for kelp forest habitats, its longevity has been significantly) Introduction High-latitude kelp forests, dominated by the brown seaweed, Laminaria sp. (Lu¨ning 1990; Raven et

  3. WRITTEN TESTIMONY OF RICHARD A. FEELY, Ph.D.

    E-Print Network [OSTI]

    personal area of research is the study of the oceanic carbon cycle and its impact on marine organisms. I Acidification Due to Increasing Atmospheric Carbon Dioxide" (Raven et al., 2005) and the recent U.S. report" (Kleypas et al., 2006). Ocean Acidification Over the past 200 years the release of carbon dioxide (CO2

  4. nAture methods | VOL.11 NO.6 | JUNE2014 | 657 molecular biologists routinely clone genetic constructs from

    E-Print Network [OSTI]

    Cai, Long

    constructs from dnA segments and formulate plans to assemble them. however, manual assembly planning and allows users to apply experimental outcomes to redesign assembly plans interactively. We used raven Evan Appleton1,2, Jenhan Tao3, Traci Haddock2 & Douglas Densmore1,2,4 binary assembly methods typically

  5. Botanical Journal of the Linnean Society, 2002, 138, 297303. With 1 figure INTRODUCTION

    E-Print Network [OSTI]

    Banuet, Alfonso Valiente

    the Cretaceous (Raven, 1973). The increase of aridity due to climatic change during the Tertiary period reduced a non-mediterranean, tropical climate (Valiente-Banuet et al., 1998) and it is distri- buted at 1700 characters that have been thought to converge under a Mediterranean climate (Barbour & © 2002 The Linnean

  6. References R-3 Adams, S. M., C. C. Brandt, S. W. Christensen, D. S. Cicerone, M. S. Greeley, Jr., W. R. Hill, M. S. Huston,

    E-Print Network [OSTI]

    Pennycook, Steve

    Airborne Radioactive Materials in Nuclear Facilities, ANSI N13.1-1969 R (1969), American National Standards, Oak Ridge Tennessee, DOE/OR/01-1858&D1, Bechtel Jacobs Co. LLC, Oak Ridge, Tenn. BJC 2000b of Toxicology, Raven Press, New York. DOE 1988a. External Dose-Rate Conversion Factors for Calculation of Dose

  7. From%laggard%to%leader:%% Explaining%offshore%wind%developments%in%

    E-Print Network [OSTI]

    Sussex, University of

    From%laggard%to%leader:%% Explaining%offshore%wind%developments%in% the%UK% Florian!laggard!to!leader:!Explaining! offshore!wind!developments!in!the!UK! Florian Kern1* , Adrian Smith1 , Chris Shaw1 , Rob Raven2 and Bram for publication in Energy Policy, 19 Feb 2014 Abstract Offshore wind technology has recently undergone rapid

  8. Comparison of benzene hexachloride formulated from high and low gamma concentrates for cotton aphid control 

    E-Print Network [OSTI]

    Raven, Klaus Gustav

    1957-01-01T23:59:59.000Z

    by KLAUS GUSTAV RAVEN Approved as to style and content by: (Chairman of Committee) (Head f Department) May 1957 ACKNOWLEDGEMENTS The writer would like to express his sincere appreciation to Dr. D. F. Martin for his constant encouragement and aid... technical material. Several processes have bees developed to soncentrate the gamsa isomer, Host processes are based on tha differential solubility of the ismsars in organic solvents. The solubility may be increased by vary- ing tha temperature...

  9. 2-Stage Melting in 2 Dimensions - Te/mo(110) 

    E-Print Network [OSTI]

    STOLZENBERG, M.; Lyuksyutov, Igor F.; BAUER, E.

    1993-01-01T23:59:59.000Z

    Arsenate and Arsenite Retention and Release in Oxide and Sulfide Dominated Systems Principal Investigator: Richard H. Loeppert Co-Investigators: Amita Jain Klaus Raven Jianlin Wang Soil & Crop Sciences Dept. Texas A&M University College Station, TX... of the specific reagents. Selective extractions also give clues concern- ing the role that suspected biological agents may have on the mobilization and uptake of arsenic. Selective extractions were performed on both oxidized and reduced sediments. Selective...

  10. Visiting hours: the second-person address in critical theory and creative practice 

    E-Print Network [OSTI]

    Peterson, Scott David

    1988-01-01T23:59:59.000Z

    ) but also for postmodern readers, to snap them out of the fog created by the changes in language and society. Kitch, the unseen (except in one brief scene) narrator is my vehicle--my metafictionist and fabulator. The Russian Formalist term "scar... in the castle, don't you'!" "A king2" "No, " she shakes her head, long raven tresses waving "A wizard? A knight7 A dragon2" "No, honey. Why, it's the home of the girl who will be your own true love. " "Aw, mom. I love you!" "You' re so sweet! I'm sure you...

  11. Quapaw Vocabulary

    E-Print Network [OSTI]

    Rankin, Robert L.

    1982-01-01T23:59:59.000Z

    . ITQhi football (AG). apple tree (CS). crov!, raven.kkaxe kkattapp:i 133 Il'li sun mikka raccoon (BS). (stress?) ~sanegro (neologism). lit. black coon. v. also istaxe sa star (MR, CS) • a, an, one. female (AG). wa]in.i rot white woman Il'litcihi (?) sun...). waxeka (JOD) nislke whiskey (OM). lit . bad l·rater cloud (CS). nitte buttocks (OM,CS). country, land (MS). N n ear(s) (CS). nitte gaZi (OM) . nitte cx:ll.si nitte. (OM) (?) toilet paper V. nitte trousers. v. also nittyujisi n~ttastette mule (BS). lit...

  12. RawSolar | Open Energy Information

    Open Energy Info (EERE)

    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 onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag JumpID-f < RAPID‎ | Roadmap Jump to:bJump to: navigation, searchRavenRawSolar

  13. Rearing of boll weevils on artificial diets

    E-Print Network [OSTI]

    Raven B., Klaus Gustav

    1959-01-01T23:59:59.000Z

    OF PHILOSOPHY AINIGOF BLWL VSTRC DIiTseOr taORoRnRNb REARING OF BOLL WEEVILS ON ARTIFICIAL DIETS A Dissertation by Klaus Gustav Raven B. Approved aa to style and content by: ^ C L ^ ? 'airman of Conmittee Hear of Department August 1959 yEK AU...Cs GIiosCNsq ra qrGOrnnsq MSOsC RC S GRnIOrRa RE HReeSn ERC 8SCrRIG psCrRqG RE Oros SG raqreSOsqK 5SK A8sCSNs aIoisC RE sNNG gSOegsq SEOsC raeIiSOrRa psCrRqG RE ?( Saq ?? gRICG ra Ogs ? OsGOG MrOg ? nrzIrqG SG raqreSOsqK WiK A8sCSNs aIoisC RE sNNG g...

  14. Verification of g-factors for lead monofluoride ground state, PbF

    E-Print Network [OSTI]

    Skripnikov, L V; Titov, A V; Mawhorter, R J; Baum, A L; Sears, T J; Grabow, J -U

    2015-01-01T23:59:59.000Z

    We report the results of our theoretical study and analysis of earlier experimental data for the g-factor tensor components of the ground $^2\\Pi_{1/2}$ state of free PbF radical. The values obtained both within the relativistic coupled-cluster method combined with the generalized relativistic effective core potential approach and with our fit of the experimental data from [R.J. Mawhorter, B.S. Murphy, A.L. Baum, T.J. Sears, T. Yang, P.M. Rupasinghe, C.P. McRaven, N.E. Shafer-Ray, L.D. Alphei, J.-U. Grabow, Phys. Rev. A 84, 022508 (2011); A. Baum, B.S. thesis, Pomona College, 2011]. The obtained results agree very well with each other but contradict the previous fit performed in the cited works. Our final prediction for g-factors is $G_{\\parallel}= 0.081(5)$, $G_{\\perp}=-0.27(1)$.

  15. Risk-Informed Safety Margin Characterization Methods Development Work

    SciTech Connect (OSTI)

    Smith, Curtis L; Ma, Zhegang; Tom Riley; Mandelli, Diego; Nielsen, Joseph W; Alfonsi, Andrea; Rabiti, Cristian

    2014-09-01T23:59:59.000Z

    This report summarizes the research activity developed during the Fiscal year 2014 within the Risk Informed Safety Margin and Characterization (RISMC) pathway within the Light Water Reactor Sustainability (LWRS) campaign. This research activity is complementary to the one presented in the INL/EXT-??? report which shows advances Probabilistic Risk Assessment Analysis using RAVEN and RELAP-7 in conjunction to novel flooding simulation tools. Here we present several analyses that prove the values of the RISMC approach in order to assess risk associated to nuclear power plants (NPPs). We focus on simulation based PRA which, in contrast to classical PRA, heavily employs system simulator codes. Firstly we compare, these two types of analyses, classical and RISMC, for a Boiling water reactor (BWR) station black out (SBO) initiating event. Secondly we present an extended BWR SBO analysis using RAVEN and RELAP-5 which address the comments and suggestions received about he original analysis presented in INL/EXT-???. This time we focus more on the stochastic analysis such probability of core damage and on the determination of the most risk-relevant factors. We also show some preliminary results regarding the comparison between RELAP5-3D and the new code RELAP-7 for a simplified Pressurized Water Reactors system. Lastly we present some conceptual ideas regarding the possibility to extended the RISMC capabilities from an off-line tool (i.e., as PRA analysis tool) to an online-tool. In this new configuration, RISMC capabilities can be used to assist and inform reactor operator during real accident scenarios.

  16. Intensity-modulated radiation therapy (IMRT) dosimetry of the head and neck: A comparison of treatment plans using linear accelerator-based IMRT and helical tomotherapy

    SciTech Connect (OSTI)

    Sheng Ke [Department of Radiation Oncology, University of Virginia, Charlottesville, VA (United States)]. E-mail: ks2mc@virginia.edu; Molloy, Janelle A. [Department of Radiation Oncology, University of Virginia, Charlottesville, VA (United States); Department of Radiation Oncology, Mayo Clinic, Rochester, MN (United States); Read, Paul W. [Department of Radiation Oncology, University of Virginia, Charlottesville, VA (United States)

    2006-07-01T23:59:59.000Z

    Purpose: To date, most intensity-modulated radiation therapy (IMRT) delivery has occurred using linear accelerators (linacs), although helical tomotherapy has become commercially available. To quantify the dosimetric difference, we compared linac-based and helical tomotherapy-based treatment plans for IMRT of the oropharynx. Methods and Materials: We compared the dosimetry findings of 10 patients who had oropharyngeal carcinoma. Five patients each had cancers in the base of the tongue and tonsil. Each plan was independently optimized using either the CORVUS planning system (Nomos Corporation, Sewickly, PA), commissioned for a Varian 2300 CD linear accelerator (Varian Medical Systems, Palo Alto, CA) with 1-cm multileaf collimator leaves, or helical tomotherapy. The resulting treatment plans were evaluated by comparing the dose-volume histograms, equivalent uniform dose (EUD), dose uniformity, and normal tissue complication probabilities. Results: Helical tomotherapy plans showed improvement of critical structure avoidance and target dose uniformity for all patients. The average equivalent uniform dose reduction for organs at risk (OARs) surrounding the base of tongue and the tonsil were 17.4% and 27.14% respectively. An 80% reduction in normal tissue complication probabilities for the parotid glands was observed in the tomotherapy plans relative to the linac-based plans. The standard deviation of the planning target volume dose was reduced by 71%. In our clinic, we use the combined dose-volume histograms for each class of plans as a reference goal for helical tomotherapy treatment planning optimization. Conclusions: Helical tomotherapy provides improved dose homogeneity and normal structure dose compared with linac-based IMRT in the treatment of oropharyngeal carcinoma resulting in a reduced risk for complications from focal hotspots within the planning target volume and for the adjacent parotid glands.

  17. Spatio-angular Minimum-variance Tomographic Controller for Multi-Object Adaptive Optics systems

    E-Print Network [OSTI]

    Correia, Carlos M; Veran, Jean-Pierre; Andersen, David; Lardiere, Olivier; Bradley, Colin

    2015-01-01T23:59:59.000Z

    Multi-object astronomical adaptive-optics (MOAO) is now a mature wide-field observation mode to enlarge the adaptive-optics-corrected field in a few specific locations over tens of arc-minutes. The work-scope provided by open-loop tomography and pupil conjugation is amenable to a spatio-angular Linear-Quadratic Gaussian (SA-LQG) formulation aiming to provide enhanced correction across the field with improved performance over static reconstruction methods and less stringent computational complexity scaling laws. Starting from our previous work [1], we use stochastic time-progression models coupled to approximate sparse measurement operators to outline a suitable SA-LQG formulation capable of delivering near optimal correction. Under the spatio-angular framework the wave-fronts are never explicitly estimated in the volume,providing considerable computational savings on 10m-class telescopes and beyond. We find that for Raven, a 10m-class MOAO system with two science channels, the SA-LQG improves the limiting mag...

  18. Baseline avian use and behavior at the CARES wind plant site, Klickitat County, Washington

    SciTech Connect (OSTI)

    Erickson, W.P.; Johnson, G.D.; Strickland, M.D.; Kronner, K.; Becker, P.S.; Orloff, S.

    2000-01-03T23:59:59.000Z

    This report presents a literature review on avian-wind turbine interactions and the results of a one-year avian baseline study conducted in 1998 at the proposed Conservation and Renewable Energy System (CARES) wind development site in Klickitat County, Washington. Avian use of the site ranged from 1.11/survey in the winter to 5.69/survey in the spring. Average use by passerines in the study plots ranged from 1.15 minutes/survey in the winter to 40.98 minutes/survey in the spring. Raptors spent much less time within plots than other groups, ranging from 0.05 minutes/survey in the winter to 0.77 minutes/survey during the fall. Thirteen percent of all flying birds were within the rotor-swept height (25 to 75 m); 41.6% of all raptors were flying at this height. Raptors with the greatest potential turbine exposure are red-tailed hawks and golden eagles. Passerines with the highest turbine exposure are common ravens, American robins, and horned larks. Spatial use data for the site indicate that avian use tends to be concentrated near the rim, indicating that placing turbines away from the rim may reduce risk. Avian use data at the CARES site indicate that if a wind plant is constructed in the future, avian mortality would likely be relatively low.

  19. ANALYSIS OF PWR SBO CAUSED BY EXTERNAL FLOODING USING THE RISMC TOOLKIT

    SciTech Connect (OSTI)

    Mandelli, Diego; Smith, Curtis; Prescott, Steven; Alfonsi, Andrea; Rabiti, Cristian; Cogliati, Joshua; Kinoshita, Robert

    2014-08-01T23:59:59.000Z

    The existing fleet of nuclear power plants is in the process of extending its lifetime and increasing the power generated from these plants via power uprates. In order to evaluate the impacts of these two factors on the safety of the plant, the Risk Informed Safety Margin Characterization project aims to provide insights to decision makers through a series of simulations of the plant dynamics for different initial conditions (e.g., probabilistic analysis and uncertainty quantification). This paper focuses on the impacts of power uprate on the safety margin of a boiling water reactor for a flooding induced station black-out event. Analysis is performed by using a combination of thermal-hydraulic codes and a stochastic analysis tool currently under development at the Idaho National Laboratory, i.e. RAVEN. We employed both classical statistical tools, i.e. Monte-Carlo, and more advanced machine learning based algorithms to perform uncertainty quantification in order to quantify changes in system performance and limitations as a consequence of power uprate. Results obtained give a detailed investigation of the issues associated with a plant power uprate including the effects of station black-out accident scenarios. We were able to quantify how the timing of specific events was impacted by a higher nominal reactor core power. Such safety insights can provide useful information to the decision makers to perform risk informed margins management.

  20. Overview of New Tools to Perform Safety Analysis: BWR Station Black Out Test Case

    SciTech Connect (OSTI)

    D. Mandelli; C. Smith; T. Riley; J. Nielsen; J. Schroeder; C. Rabiti; A. Alfonsi; Cogliati; R. Kinoshita; V. Pasucci; B. Wang; D. Maljovec

    2014-06-01T23:59:59.000Z

    Dynamic Probabilistic Risk Assessment (DPRA) methodologies couple system simulator codes (e.g., RELAP, MELCOR) with simulation controller codes (e.g., RAVEN, ADAPT). While system simulator codes accurately model system dynamics deterministically, simulation controller codes introduce both deterministic (e.g., system control logic, operating procedures) and stochastic (e.g., component failures, parameter uncertainties) elements into the simulation. Typically, a DPRA is performed by: 1) sampling values of a set of parameters from the uncertainty space of interest (using the simulation controller codes), and 2) simulating the system behavior for that specific set of parameter values (using the system simulator codes). For complex systems, one of the major challenges in using DPRA methodologies is to analyze the large amount of information (i.e., large number of scenarios ) generated, where clustering techniques are typically employed to allow users to better organize and interpret the data. In this paper, we focus on the analysis of a nuclear simulation dataset that is part of the Risk Informed Safety Margin Characterization (RISMC) Boiling Water Reactor (BWR) station blackout (SBO) case study. We apply a software tool that provides the domain experts with an interactive analysis and visualization environment for understanding the structures of such high-dimensional nuclear simulation datasets. Our tool encodes traditional and topology-based clustering techniques, where the latter partitions the data points into clusters based on their uniform gradient flow behavior. We demonstrate through our case study that both types of clustering techniques complement each other in bringing enhanced structural understanding of the data.

  1. Effects of Transcranial Direct Current Stimulation (tDCS) on Human Memory.

    SciTech Connect (OSTI)

    Matzen, Laura E.; Trumbo, Michael Christopher Stefan

    2014-10-01T23:59:59.000Z

    Training a person in a new knowledge base or skill set is extremely time consuming and costly, particularly in highly specialized domains such as the military and the intelligence community. Recent research in cognitive neuroscience has suggested that a technique called transcranial direct current stimulation (tDCS) has the potential to revolutionize training by enabling learners to acquire new skills faster, more efficiently, and more robustly (Bullard et al., 2011). In this project, we tested the effects of tDCS on two types of memory performance that are critical for learning new skills: associative memory and working memory. Associative memory is memory for the relationship between two items or events. It forms the foundation of all episodic memories, so enhancing associative memory could provide substantial benefits to the speed and robustness of learning new information. We tested the effects of tDCS on associative memory, using a real-world associative memory task: remembering the links between faces and names. Working memory refers to the amount of information that can be held in mind and processed at one time, and it forms the basis for all higher-level cognitive processing. We investigated the degree of transfer between various working memory tasks (the N-back task as a measure of verbal working memory, the rotation-span task as a measure of visuospatial working memory, and Raven's progressive matrices as a measure of fluid intelligence) in order to determine if tDCS-induced facilitation of performance is task-specific or general.

  2. Medium Truck Duty Cycle Data from Real-World Driving Environments: Project Interim Report

    SciTech Connect (OSTI)

    Franzese, Oscar [ORNL; Lascurain, Mary Beth [ORNL; Capps, Gary J [ORNL

    2011-01-01T23:59:59.000Z

    Since the early part of the 20th century, the US trucking industry has provided a safe and economical means of moving commodities across the country. At the present time, nearly 80% of the US domestic freight movement involves the use of trucks. The US Department of Energy (DOE) is spearheading a number of research efforts to improve heavy vehicle fuel efficiencies. This includes research in engine technologies (including hybrid and fuel cell technologies), lightweight materials, advanced fuels, and parasitic loss reductions. In addition, DOE is developing advanced tools and models to support heavy vehicle truck research, and is leading the 21st Century Truck Partnership whose stretch goals involve a reduction by 50% of the fuel consumption of heavy vehicles on a ton-mile basis. This Medium Truck Duty Cycle (MTDC) Project is a critical element in DOE s vision for improved heavy vehicle energy efficiency and is unique in that there is no other national database of characteristic duty cycles for medium trucks. It involves the collection of real-world data for various situational characteristics (rural/urban, freeway/arterial, congested/free-flowing, good/bad weather, etc.) and looks at the unique nature of medium trucks drive cycles (stop-and-go delivery, power takeoff, idle time, short-radius trips), to provide a rich source of data that can contribute to the development of new tools for fuel efficiency and modeling, provide DOE a sound basis upon which to make technology investment decisions, and provide a national archive of real-world-based medium-truck operational data to support heavy vehicle energy efficiency research. The MTDC project involves a two-part field operational test (FOT). For the Part-1 FOT, three vehicles, each from two vocations (urban transit and dry-box delivery) were instrumented for one year of data collection. The Part-2 FOT will involve the towing/recovery and utility vocations. The vehicles participating in the MTDC project are doing so through gratis partnerships in return for early access to the results of this study. Partnerships such as these are critical to FOTs in which real-world data is being collected. In Part 1 of the project, Oak Ridge National Laboratory(ORNL) established partnerships with the H.T. Hackney Company, one of the largest wholesale distributors in the country, distributing products to 21 states; and with the Knoxville Area Transit (KAT), the City of Knoxville s transit system, operating services across the city of Knoxville and parts of Knox co. These partnerships and agreements provided ORNL access to three Class-7 2005/2007 International day-cab tractors, model 8600, which regularly haul 28 ft pup trailers (H.T. Hackney Co) and three Class-7 2005 Optima LF-34 buses (KAT), for collection of duty cycle data. In addition, ORNL has collaborated with the Federal Motor Carrier Safety Administration (FMCSA) to determine if there were possible synergies between this duty cycle data collection effort and FMCSA s need to learn more about the operation and duty cycles of the second-largest fuel consuming commercial vehicle category in the US. FMCSA s primary interest was in collecting safety data relative to the driver, carrier, and vehicle. In order to collect the duty cycle and safety-related data, ORNL developed a data acquisition and wireless communication system that was placed on each test vehicle. Each signal recorded in this FOT was collected by means of one of the instruments incorporated into each data acquisition system (DAS). Native signals were obtained directly from the vehicle s J1939 and J1708 data buses. A VBOX II Lite collected Global Positioning System related information including speed, acceleration, and spatial location information at a rate of 5 Hz, and communicated this data via the CAN (J1939) protocol. The Air-Weigh LoadMaxx, a self-weighing system which determines the vehicle s gross weight by means of pressure transducers and posts the weight to the vehicle s J1939 data bus, was used to collect vehicle payload information. A cellular modem, the Raven X