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At least 919 records · Page 51

Evaluation of Physical Security Risk for Potential Implementation of FLEX using Dynamic Simulation Methods

The requirements for United States nuclear power plants to maintain a large onsite physical security force contribute to their large operational costs. The cost of maintaining the current physical security posture is approximately 10% of the overall operation and maintenance budget for commercial nuclear power plants. The goal of the Light Water Reactor Sustainability Program Physical Security Pathway is to develop tools, methods, and technologies and provide the technical basis for an optimized physical security posture. This pathway will analyze and minimize the conservatisms built into current security postures in order to reduce security costs while still ensuring adequate security and operational safety. The research performed at Idaho National Laboratory within this pathway has successfully developed a dynamic force-on-force (FOF) modeling framework using various computer simulation tools and integrated them with the dynamic assessment Event Modeling Risk Assessment using Linked Diagrams (EMRALD) tool. This document provides an overview of lessons learned in applying a dynamic computational framework that links results from a commercially available FOF simulation tool, a commercially available thermal-hydraulic tool, and EMRALD to an operating commercial nuclear power plant. This process of including plant procedures and multiple analysis results is being called Modeling and Analysis for Safety Security using Dynamic EMRALD Framework. Previous reports described how a user could integrate their plant-specific FOF models with the dynamic simulation tool EMRALD, model operator actions, integrate with probabilistic risk assessment tools, such as Computer Aided Fault Tree Analysis System or Systems Analysis Programs for Hands-on Integrated Reliability Evaluations, and with thermal-hydraulic tools, such as RELAP-5. Previous reports applied various combinations of available simulations codes with EMRALD using generic plant models to demonstrate how to perform the analysis. This report documents the results of applying the dynamic computational framework to an actual nuclear facility using their security scenarios and timelines. The purpose of this study was to verify that results achieved using generic models are similar to actual plant results and to refine our guidance of the use of the framework. Such an assessment enables further analysis, such as what-if scenarios and staff-reduction evaluation, thereby optimizing physical security at plants. NOTE: The work performed in this report is based on a generic EMRALD model with actual plant data used for the analysis. However, only the generic model and general results of the analysis are in the report. No plant’s sensitive information is discussed in this report. The discussion shows examples of insights that can be obtained from the MASS-DEF methodology.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Thermodynamics and Kinetics of Phase Transformations in Energy Materials (Final Report)

The primary goal of this program is to develop computational tools and methodology for enabling a shift from empirical trial-and-error driven materials discovery towards data and information technology driven design of materials with targeted functional properties. Both thermodynamic and kinetic factors need to be taken into account when designing new materials. Thermodynamics sets the necessary-but-not-sufficient conditions for the suitability of a particular material in a given application, while the kinetics controls the rates of microscopic processes and hence the performance in energy applications (e.g., power in energy storage, conversion efficiencies in solar cells and thermoelectrics, chemical activity in catalysis). The complexity of these phenomena makes computational design difficult, not least due to the lack of suitable theoretical methods and computational tools. To address these needs, we develop systematic, quantitatively accurate first-principles methods to address two important problems: (i) predict and optimize the thermodynamics of materials over a large composition and structure space, and (ii) model kinetic processes such as mass and heat transport in crystalline solids under non-equilibrium conditions. These tasks are addressed by combining high-throughput computation with automatic construction of accurate lattice models using mathematically rigorous methods of information theory, such as compressive sensing and Bayesian inference.

36 MATERIALS SCIENCE↗

HERON as a Tool for LWR Market Interaction in a Deregulated Market

This document reports the development of HERON (Holistic Energy Resource Optimization Network), a newly-developed RAVEN (Risk Analysis Virtual ENvironment) plugin for grid and capacity optimization, to technoeconomic analysis in a deregulated market. A short description of the HERON plugin is provided, and the release process is described. HERON as a plugin enables RAVEN to perform stochastic technoeconomic analysis of grid-energy systems in a generic approach. The primary function of HERON is to generate the complex RAVEN workflows necessary to optimize component capacities under stochastic systems. HERON is capable of analyzing systems with complex components transferring a variety of commodities, including production components and varied markets. HERON is capable of optimizing high-resolution dispatch for such systems and guiding stochastic optimization algorithms in RAVEN for finding optimal component capacities. In particular, this document demonstrates the application of HERON to systems with deregulated markets.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Jan-Dec 2021 IC Project: w20_earthquake (Yearly Report) [Slides]

Large-scale simulations were conducted using the computational tool HOSS to investigate scientific aspects of the time reversal process. The main focus was the identification of damage/defects in wellbores for relevant subsurface applications.

58 GEOSCIENCES↗

Technical Report

MEST has developed Materials Navigator, a machine-learning software tool, to extract/combine data from disparate sources of materials information, which can be used to make suggestions for new directions of search and discovery of materials. The goal is to create a flexible software which can help materials science researchers quickly focus on a small group of promising materials and conduct fewer and less expensive experiments for maximum impact. Materials domains of interest for the Materials Navigator include solid state electrolytes for batteries, materials for fuel cells, photovoltaics, caloric cooling materials, and permanent magnets. Our solution is useful to materials researchers in academics and industry. To date, the MEST team has already developed a prototype of the Materials Navigator, which can be used to visualize a large number of materials compounds in their “descriptor space” where materials properties are encoded in machine learning based quantities. We have used Materials Navigator to make a list of potential new materials for batteries. It has also led to the experimental discovery of a new tantalum oxide superconductor.

36 MATERIALS SCIENCE↗

Development of a Pipe Crawler Inspection Tool for Fossil Energy Power Plants

This document presents the final report of the research activity completed during the four years of the project and includes the major challenges and accomplishments. The report presents specific details of the engineering processes and methodologies used to develop the robotic crawler and complete the project milestones. In particular, the report includes sections that address the problem statement, background, development of crawler modules, bench scale testing, simulation development and full scale testing. The report concludes with a discussion on potential paths forward and concluding remarks.

20 FOSSIL-FUELED POWER PLANTS↗

Image Analysis as a Tool for Satellite-Earth Propagation Studies

We present a progress report on a useful new method to assess propagation problems for outdoor mobile Earth-satellite paths. The method, Photogrammetric Satellite Service Prediction (PSSP) is based on the determination of Land Mobile Satellite Systems (LMSS) service attributes at the locations of static or mobile LMSS service users by evaluating fisheye images of their environment. This paper gives an overview of the new method and its products.

Akturan, Riza↗

Cosmogenic Radionuclides in Hot Desert Chondrites with Low C-14 Activities: A Progress Report

Terrestrial ages of meteorites from hot deserts provide an important tool to estimate meteorite fluxes to the Earth. Most desert meteorites have terrestrial ages less than 40 ky, but a few achondrites from the Sahara region were recently shown to have significantly higher ages, up to approx. 100 ky. In general, C-14 (half-life = 5730 y) is the most suited radionuclide to determine terrestrial ages for desert meteorites. However for meteorites with ages greater than 35 ky, the concentration of cosmogenic C-14 has decreased to a level at which it becomes difficult to distinguish between cosmogenic C-14 and terrestrial contamination. These meteorites may therefore be much older than 35 ky. We selected chondrites with low C-14 activities (less than or equal to 2 dpm/kg) for measurements of the concentrations of cosmogenic Cl-36 (half-life= 3.01 x 10 (exp 5) y) and Ca-41 (half-life= 1.04 x 10 (exp 5) y) in the metal phase. Since the ratio of Ca-14/Cl-36 in the metal phase of chondrites is relatively constant and well known, the measured ratio is a direct measure of the terrestrial age. A major problem is that most or sometimes all of the metal in these old "hot desert" meteorites has been oxidized to hydrated Fe-Ni-oxides. Therefore, we also measured the concentrations of Be-10, Al-26 and Cl-36 in the stony phase in order to constrain the terrestrial age as much as possible.

Welten, Kees↗

Calibration of MAMBA and CRUD Sources Using Full-Core CTF+MAMBA

This report outlines a process for the deterministic calibration of MAMBA using the computational toolkit Dakota. The tools and processes for deterministic calibration have been built and are laid out in this report. While completing this milestone, issues emerged with MAMBA that resulted in delays. The consequences for these difficulties to the calibration process are briefly discussed. The report concludes with an outline of a path forward for Bayesian calibration. The Bayesian calibration will be performed next year. This process was laid out by Benjamin Collins, Robert Salko, and Adam Hetzler.

42 ENGINEERING↗

Monitoring River Basin Development and Variation in Water Resources in Transboundary Imjin River in North and South Korea Using Remote Sensing

This paper presents methods of monitoring river basin development and water variability for the transboundary river in North and South Korea. River basin development, such as dams and water infrastructure in transboundary rivers, can be a potential factor of tensions between upstream and downstream countries since dams constructed upstream can adversely affect downstream riparians. However, because most of the information related to North Korea has been limited to the public, the information about dams constructed and their locations were inaccurate in many previous studies. In addition, water resources in transboundary rivers can be exploited as a political tool. Specifically, due to the unexpected water release from the Hwanggang Dam, upstream of the transboundary Imjin River in North and South Korea, six South Koreans died on 6 September 2009. The Imjin River can be used as a political tool by North Korea, and seven events were reported as water conflicts in the Imjin River from 2001 to 2016. In this paper, firstly, we have updated the information about the dams constructed over the Imjin River in North Korea using multi-temporal images with a high spatial resolution (15-30 cm) obtained from Google Earth. Secondly, we analyzed inter- and intra-water variability over the Hwanggang Reservoir using open-source images obtained from the Global Surface Water Explorer. We found a considerable change in water surface variability before and after 2008, which might result from the construction of the Hwanggang Dam. Thirdly, in order to further investigate intra-annual water variability, we present a method monitoring water storage changes of the Hwanggang Reservoir using the area-elevation curve (AEC), which was derived from multi-sensor Synthetic Aperture Radar (SAR) images (Sentinel-1A and -1B) and the Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM). Since many previous studies for estimating water storage change have depended on satellite altimetry dataset and optical images for deriving AEC, the method adopted in this study is the only application for such inaccessible areas since no altimetry ground track exists for the Hwanggang Reservoir and because clouds can block the study area for wet seasons. Moreover, this study has newly proven that unexpected water release can occur in dry seasons because the water storage in the Hwanggang Reservoir can be high enough to conduct a release that can be used as a geopolitical tool. Using our method, potential risks can be mitigated, not in response to a water release, but based on pre-event water storage changes in the Hwanggang Reservoir.

Kim, Donghwan↗

Evaluation of Containment and Geomechanical Risks at Integrated Mid-Content Stacked Carbon Storage Hub Sites

The U.S. Department of Energy is leading the development of CCS through collaborative projects and programs to not only develop and demonstrate the technology but to also quantify the risks and provide tools that site operators can use to develop a site-specific understanding of their risk to enable successful project operations. This report summarizes results and findings from the application of risk-assessment tools to an industrial-scale Geologic Carbon Storage (GCS) project. Specifically, we applied the National Risk Assessment Partnership’s (NRAP) Open Integrated Assessment Model (NRAP-Open-IAM) and State of Stress Assessment Tool (SOSAT) to two candidate sites being considered for storage by the Integrated Midcontinent Stacked Carbon Storage Hub (IMSCS-Hub) project team. These sites, Sleepy Hollow Field in Nebraska and Patterson Field in Kansas, have historical oil and gas production and thus are attractive candidates to store the 50 million metric tons (Mt), which is the CarbonSAFE objective. Because these sites have historical operations, they have a significant number of existing wells that pose a risk for well leakage. Additionally, the storage formations will undergo significant pore pressure perturbation (i.e., increase due to CO 2 injection). Hence, we have selected the two NRAP tools best suited to study the risks associated with well leakage and geomechanical risks. The objective of the study was not only to assess the risk at the site, but to also improve the NRAP tools through application using real site data on an ongoing project.

54 ENVIRONMENTAL SCIENCES↗

GPM Timeline Inhibits For IT Processing

The Safety Inhibit Timeline Tool was created as one approach to capturing and understanding inhibits and controls from IT through launch. Global Precipitation Measurement (GPM) Mission, which launched from Japan in March 2014, was a joint mission under a partnership between the National Aeronautics and Space Administration (NASA) and the Japan Aerospace Exploration Agency (JAXA). GPM was one of the first NASA Goddard in-house programs that extensively used software controls. Using this tool during the GPM buildup allowed a thorough review of inhibit and safety critical software design for hazardous subsystems such as the high gain antenna boom, solar array, and instrument deployments, transmitter turn-on, propulsion system release, and instrument radar turn-on. The GPM safety team developed a methodology to document software safety as part of the standard hazard report. As a result of this process, a new tool safety inhibit timeline was created for management of inhibits and their controls during spacecraft buildup and testing during IT at GSFC and at the launch range in Japan. The Safety Inhibit Timeline Tool was a pathfinder approach for reviewing software that controls the electrical inhibits. The Safety Inhibit Timeline Tool strengthens the Safety Analysts understanding of the removal of inhibits during the IT process with safety critical software. With this tool, the Safety Analyst can confirm proper safe configuration of a spacecraft during each IT test, track inhibit and software configuration changes, and assess software criticality. In addition to understanding inhibits and controls during IT, the tool allows the Safety Analyst to better communicate to engineers and management the changes in inhibit states with each phase of hardware and software testing and the impact of safety risks. Lessons learned from participating in the GPM campaign at NASA and JAXA will be discussed during this session.

Inhibits↗

New simulation capability for gamma ray mirror experiments

This report provides a description of the simulation toolkit developed at Lawrence Livermore National Laboratory to support the design of nuclear safeguards experiments using grazing incidence multilayer mirrors in the energy band of uranium (U) and plutonium (Pu) emission lines. This effort was motivated by the data analysis of a scoping experiment at the Irradiated Fuels Examination Facility (IFEL) at Oak Ridge National Laboratory in FY13 and of a benchmark experiment at the Idaho National Laboratory (INL) in FY14 that highlighted the need for predictive tools built around a ray-tracing capability. This report presents the simulation toolkit and relevant results such as the simulated spectra for TMI, MOX, and ATM106 fuel rods based on spent fuel models provided by Los Alamos National Laboratory and for a virgin high 240 Pu-content fuel plate, as well as models of the IFEL and INL experiments implemented in the ray tracing tool. The beam position and height were validated against the INL ~60 keV americium data. Examples of alternate configurations of the optics or experimental set-up illustrate the future use of the simulation suite to guide the next IFEL experimental campaign.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Soda Pop: A Time-Series Clustering, Alarming and Disease Forecasting Application

To introduce Soda Pop, an R/Shiny application designed to be a disease agnostic time-series clustering, alarming, and forecasting tool to assist in disease surveillance “triage, analysis and reporting” workflows within the Biosurveillance Ecosystem (BSVE). In this poster, we highlight the new capabilities that are brought to the BSVE by Soda Pop with an emphasis on the impact of methodological decisions. The Biosurveillance Ecosystem (BSVE) is a biological and chemical threat surveillance system sponsored by the Defense Threat Reduction Agency (DTRA). BSVE is intended to be user-friendly, multi-agency, cooperative, modular and threat agnostic platform for biosurveillance. In BSVE, a web-based workbench presents the analyst with applications (apps) developed by various DTRA funded researchers, which are deployed on-demand in the cloud(e.g., Amazon Web Services). These apps aim to address emerging needs and refine capabilities to enable early warning of chemical and biological threats for multiple users across local, state, and federal agencies. Soda Pop is an app developed by Pacific Northwest National Laboratory (PNNL) to meet the current needs of the BSVE for early warning and detection of disease outbreaks. Aimed for use bya diverse set of analysts, the application is agnostic to data source and spatial scale enabling it to be generalizable across many diseases and locations. To achieve this, we placed a particular emphasis on clustering and alerting of disease signals within Soda Pop without strong prior assumptions on the nature of observed diseased counts. Although designed to be agnostic to the data source, Soda Pop was initially developed and tested on data summarizing Influenza-Like Illness in military hospitals from collaboration with the Armed Forces Health Surveillance Branch. Currently, the data incorporated also includes the CDC’s National Notifiable Diseases Surveillance System(NNDSS) tables and the WHO’s Influenza A/B Influenza Data(Flunet). These data sources are now present in BSVE’s Postgres data storage for direct access. Soda Pop is designed to automate time-series tasks of data summarization, exploration, clustering, alarming and forecasting. Built as an R/Shiny application, Soda Pop is founded on the powerful statistical tool R.. Where applicable, Soda Pop facilitates nonparametric seasonal decomposition of time-series; hierarchical agglomerative clustering across reporting areas and between diseases within reporting areas; and a variety of alarming techniques including Exponential Weighted Moving Average alarms and Early Aberration Detection. Soda Pop embeds these techniques within a user-interface designed to enhance an analyst’s understanding of emerging trends in their data and enables the inclusion of its graphical elements into their dossier for further tracking and reporting. The ultimate goal of this software is to facilitate the discovery of unknown disease signals along with increasing the speed of detection of unusual patterns within these signals. Soda Pop organizes common statistical disease surveillance tasks in a manner integrated with BSVE data source inputs and outputs. The app analyzes time-series disease data and supports a robust set of clustering and alarming routines that avoid strong assumptions on the nature of observed disease counts. This attribute allows for flexibility in the data source, spatial scale, and disease types making it useful to a wide range of analysts.

97 MATHEMATICS AND COMPUTING↗

E-Labs - Learning with Authentic Data

the success teachers have had providing an opportunity for students to: • Organize and conduct authentic research. • Experience the environment of scientific collaborations. • Possibly make real contributions to a burgeoning scientific field. We've created projects that are problem-based, student driven and technology dependent. Students reach beyond classroom walls to explore data with other students and experts and share results, publishing original work to a worldwide audience. Students can discover and extend the research of other students, modeling the processes of modern, large-scale research projects. From start to finish e-Labs are student-led, teacher-guided projects. Students need only a Web browser to access computing techniques employed by professional researchers. A Project Map with milestones allows students to set the research plan rather than follow a step-by-step process common in other online projects. Most importantly, e-Labs build the learning experience around the students' own questions and let them use the very tools that scientists use. Students contribute to and access shared data, most derived from professional research databases. They use common analysis tools, store their work and use metadata to discover, replicate and confirm the research of others. This is where real scientific collaboration begins. Using online tools, students correspond with other research groups, post comments and questions, prepare summary reports, and in general participate in the part of scientific research that is often left out of classroom experiments. Teaching tools such as student and teacher logbooks, pre- and post-tests and an assessment rubric aligned with learner outcomes help teachers guide student work. Constraints on interface designs and administrative tools such as registration databases give teachers the "one-stop-shopping" they seek for multiple e-Labs. Teaching and administrative tools also allow us to track usage and assess the impact on student learning.

Bardeen, Marjorie G.↗

Program ELM: A tool for rapid thermal-hydraulic analysis of solid-core nuclear rocket fuel elements

This report reviews the state of the art of thermal-hydraulic analysis codes and presents a new code, Program ELM, for analysis of fuel elements. ELM is a concise computational tool for modeling the steady-state thermal-hydraulics of propellant flow through fuel element coolant channels in a nuclear thermal rocket reactor with axial coolant passages. The program was developed as a tool to swiftly evaluate various heat transfer coefficient and friction factor correlations generated for turbulent pipe flow with heat addition which have been used in previous programs. Thus, a consistent comparison of these correlations was performed, as well as a comparison with data from the NRX reactor experiments from the Nuclear Engine for Rocket Vehicle Applications (NERVA) project. This report describes the ELM Program algorithm, input/output, and validation efforts and provides a listing of the code.

Walton, James T.↗

Open Source Suite for Advanced Synchrophasor Analysis

The report presents the results of the development of the open-source suite of applications for synchrophasor analysis. The suite includes several software tools for oscillation analysis, power plant model validation, and frequency response analysis using synchrophasor measurements. All tools are based on the common framework and data sources. The developed tools have been used by different electrical utilities for synchrophasor analysis. The report includes several use cases based on the actual system PMU data.

20 FOSSIL-FUELED POWER PLANTS↗