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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

An Exploration of Historical Transitions with Simple Analogies and Empirical Event Rates

Various qualitative models have been suggested for major historical social and technological transitions. Many of these transitions still have puzzling aspects such as the early transition from hunter-gatherer to agriculturally-based society which required dramatically increased effort. Another puzzle is the emergence of the scientific and industrial revolution in Europe despite many previous similar discoveries in other regions. Explorations of simple models with aggregate, dynamic, and nonlinear processes might lead to insights of the unique aspects of each transition. Topics include the transitions between hunter-gatherers, agricultural societies, early civilizations, market development, capitalism, industrialization, and sustainable societies with factors of land-pressures, economies of scale, suppressed growth, and chain reactions. Many types of models could be applied to these transitions. First, basic characteristics, such as width and midpoint of the transitions, are determined by analyzing historical events contributing to the transition. However, this does give much insight into the dynamics or parameters of the transition. For more understanding, each of six transitions is explored with a simple phenomenological model. In conclusion, these simplified models do not attempt to quantitatively address the details of the actual historical mechanisms Instead analogies to more natural systems are invoked to gain insights.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Nonlinear multiobjective and dynamic real-time predictive optimization for optimal operation of baseload power plants under variable renewable energy

Considering the increase of disruptive variable renewable energy penetration into the power grid, this article focuses on the investigation of a multiobjective and dynamic real-time optimization framework to address the cycling of large-scale power plants under renewable penetration. In this framework, a parallelized particle swarm optimization step is first performed to generate feasible initial points. Then, a multiobjective and dynamic real-time optimization formulation generates optimal trajectories. Further, the benefit of predictive capability is investigated for the dynamic component, which introduces the novel nonlinear multiobjective and dynamic real-time predictive optimization approach. Two multiobjective formulations to obtain Pareto front optimal in real time are explored: the modified Tchebycheff-based weighted metric and ϵ-constraint methods. Economic and environmental objectives are considered in this study. A novel topical discussion on the intersection of dynamic real-time optimization with model predictive control is also presented. The developed framework is successfully applied to a baseload coal-fired power plant with postcombustion CO 2 capture. Results indicate that the approach can be deployed for a large-scale system if automatic differentiation, model reduction, and parallelization are adopted to improve computational tractability, with computational improvement up to 120-folds after performing these steps. Finally, market and carbon policies showed an impact on the optimal compromise between the objectives with an additional 63 ton of CO 2 captured under favorable market conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Pre-metered coating flow models with Goma 7: Workflow Tutorial

Tutorials for modeling of slot-die and slide-die coating flows with Goma 7, an open source finite element code, are presented. The tutorials cover the workflow to attaining steady state solutions for these flows, and continuation strategies for navigating the operating windows. Advanced topics of coating window prediction, automated multiparameter continuation, non-Newtonian rheology, dynamic contact line modeling, and some more solution strategies are also covered.

08 HYDROGEN↗
DOE OSTI2024

Going beyond BEM with BEM: an insight into dynamic inflow effects on floating wind turbines

Blade element momentum (BEM) theory is the backbone of many industry-standard wind turbine aerodynamic models. To be applied to a broader set of engineering problems, BEM models have been extended since their inception and now include several empirical corrections. These models have benefitted from decades of development and refinement and have been extensively used and validated, proving their adequacy in predicting aerodynamic forces of horizontal-axis wind turbine rotors in most scenarios. However, the analysis of floating offshore wind turbines (FOWTs) introduces new sets of challenges, especially if new-generation large and flexible machines are considered. In fact, due to the combined action of wind and waves and their interaction with the turbine structure and control system, these machines are subject to unsteady motion and thus unsteady inflow on the wind turbine's blades, which could put BEM models to the test. Consensus has not been reached on the accuracy limits of BEM in these conditions. This study contributes to the ongoing research on the topic by systematically comparing four different aerodynamic models, ranging from BEM to computational fluid dynamics, in an attempt to shed light on the unsteady aerodynamic phenomena that are at stake in FOWTs and whether BEM is able to model them appropriately. Simulations are performed on the UNAFLOW 1:75 scale rotor during imposed harmonic surge and pitch motion. Experimental results are available for these conditions and are used for baseline validation. The rotor is analyzed in both rated operating conditions and low wind speeds, where unsteady aerodynamic effects are expected to be more pronounced. Results show that BEM, despite its simplicity, can adequately model the aerodynamics of FOWTs in most conditions if augmented with a dynamic inflow model.

17 WIND ENERGY↗
DOE OSTI2016

Transport and Dynamics in Toroidal Fusion Systems

The study entitled, "Transport and Dynamics in Toroidal Fusion Systems," (TDTFS) applied analytical theory and numerical computation to investigate topics of importance to confining plasma, the fourth state of matter, with magnetic fields. A central focus of the work is how non-thermal components of the ion particle distribution affect the "sawtooth" collective oscillation in the core of the tokamak magnetic configuration. Previous experimental and analytical research had shown and described how the oscillation frequency decreases and amplitude increases, leading to "monster" or "giant" sawteeth, when the non-thermal component is increased by injecting particle beams or by exciting ions with imposed electromagnetic waves. The TDTFS study applied numerical computation to self-consistently simulate the interaction between macroscopic collective plasma dynamics and the non-thermal particles. The modeling used the NIMROD code [Sovinec, Glasser, Gianakon, et al., J. Comput. Phys. 195, 355 (2004)] with the energetic component represented by simulation particles [Kim, Parker, Sovinec, and the NIMROD Team, Comput. Phys. Commun. 164, 448 (2004)]. The computations found decreasing growth rates for the instability that drives the oscillations, but they were ultimately limited from achieving experimentally relevant parameters due to computational practicalities. Nonetheless, this effort provided valuable lessons for integrated simulation of macroscopic plasma dynamics. It also motivated an investigation of the applicability of fluid-based modeling to the ion temperature gradient instability, leading to the journal publication [Schnack, Cheng, Barnes, and Parker, Phys. Plasmas 20, 062106 (2013)]. Apart from the tokamak-specific topics, the TDTFS study also addressed topics in the basic physics of magnetized plasma and in the dynamics of the reversed-field pinch (RFP) configuration. The basic physics work contributed to a study of two-fluid effects on interchange dynamics, where "two-fluid" refers to modeling independent dynamics of electron and ion species without full kinetic effects. In collaboration with scientist Ping Zhu, who received separate support, it was found that the rule-of-thumb criteria on stabilizing interchange has caveats that depend on the plasma density and temperature profiles. This work was published in [Zhu, Schnack, Ebrahimi, et al., Phys. Rev. Lett. 101, 085005 (2008)]. An investigation of general nonlinear relaxation with fluid models was partially supported by the TDTFS study and led to the publication [Khalzov, Ebrahimi, Schnack, and Mirnov, Phys. Plasmas 19, 012111 (2012)]. Work specific to the RFP included an investigation of interchange at large plasma pressure and support for applications [for example, Scheffel, Schnack, and Mirza, Nucl. Fusion 53, 113007 (2013)] of the DEBS code [Schnack, Barnes, Mikic, Harned, and Caramana, J. Comput. Phys. 70, 330 (1987)]. Finally, the principal investigator over most of the award period, Dalton Schnack, supervised a numerical study of modeling magnetic island suppression [Jenkins, Kruger, Hegna, Schnack, and Sovinec, Phys. Plasmas 17, 12502 (2010)].

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Learning Operators for Structure-Informed Surrogate Models

This report summarizes the work performed under the author's two-year John von Neumann LDRD project, which involves the non-intrusive surrogate modeling of dynamical systems with remarkable structural properties. After a brief introduction to the topic, technical accomplishments and project metrics are reviewed including peer-reviewed publications, software releases, external presentations and colloquia, as well as organized conference sessions and minisymposia. The report concludes with a summary of ongoing projects and collaborations which utilize the results of this work.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

PACKAGE IMPACT MODELS AS A PRECURSOR TO CLADDING ANALYSIS

The evaluation of spent nuclear fuel storage casks and transportation packages under impact loading is an important safety topic that is reviewed as part of cask and package certification by the United States Nuclear Regulatory Commission. Explicit dynamic finite element models of full systems are increasingly common in industry for determining structural integrity during hypothetical drop accidents. Full cask and package model results are also used as the loading basis for single fuel pin impact models, which evaluate the response of fuel cladding under drop conditions. In this paper, a simplified package system is evaluated to illustrate several important structural dynamic phenomena, including the effect of gaps between components, the difference in local response at various points on a package during impact, and the effect of modeling various simplified representations of the basket and fuel assemblies. This paper focuses on the package impact analysis, and how loading conditions for a subsequent fuel assembly or fuel cladding analysis can be extracted.

Klymyshyn, Nicholas A.↗
DOE OSTI2015

Update: structural uncertainty of used nuclear fuel in dry storage canisters

The Structural Uncertainty research task uses numerical modeling to help close knowledge gaps associated with extended dry storage of used nuclear fuel. Modeling helps to predict the expected range of mechanical loading on used nuclear fuel and dry storage system components, which is needed to help guide materials research. Knowledge of expected loads helps the materials researchers prioritize their research and focus only on the relevant material degradation phenomena that can have an effect on the ability of dry storage systems to function. The loads considered in this task are DSC tip-over, handling drops of the multipurpose fuel canister, and seismic loading of DSC systems while situated on the concrete pad of a storage facility. This document is a progress report that describes the work that was performed in fiscal year 2015. The work is a broad task that considers a number of physical phenomena and uses sophisticated LS-DYNA finite element models to predict used fuel and DSC system response to dynamic loads. Due to the broad list of topics and limited budgets, the topics of this task are prioritized at the beginning of the year and the priorities are subject to revision throughout the year as the Pacific Northwest National Laboratory team collaborates with other members of the Used Fuel Disposition Campaign. This year, three topics were investigated: options for modeling cladding in LS-DYNA, the effect of cladding thinning in the tip-over load case, and stress corrosion cracking in multipurpose canister welds. In each of these cases, significant progress was made. This report details the work that was done and identifies areas where more work is needed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2018

Uncovering universal rules governing the selectivity of the archetypal DNA glycosylase TDG

Thymine DNA glycosylase (TDG) is a pivotal enzyme with dual roles in both genome maintenance and epigenetic regulation. TDG is involved in cytosine demethylation at CpG sites in DNA. Here we have used molecular modeling to delineate the lesion search and DNA base interrogation mechanisms of TDG. First, we examined the capacity of TDG to interrogate not only DNA substrates with 5-carboxyl cytosine modifications but also G:T mismatches and nonmismatched (A:T) base pairs using classical and accelerated molecular dynamics. To determine the kinetics, we constructed Markov state models. Base interrogation was found to be highly stochastic and proceeded through insertion of an arginine-containing loop into the DNA minor groove to transiently disrupt Watson–Crick pairing. Next, we employed chain-of-replicas path-sampling methodologies to compute minimum free energy paths for TDG base extrusion. We identified the key intermediates imparting selectivity and determined effective free energy profiles for the lesion search and base extrusion into the TDG active site. Here, our results show that DNA sculpting, dynamic glycosylase interactions, and stabilizing contacts collectively provide a powerful mechanism for the detection and discrimination of modified bases and epigenetic marks in DNA.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Structure and Dynamics of Domains in Ferroelectric Nanostructures – Phase-Field Modeling (Final Technical Report)

Domain pattern formation is one of the most common phenomena in nature and is a topic of immense interest in many fields ranging from materials science and physics to chemistry and biology. This DOE sponsored research project explored the basic science concerning the thermodynamic stability of mesoscale polarization domain patterns and their temporal evolution mechanisms during formation and subsequent switching in ferroelectric nanostructures and heterostructures. The project employed the computational phase-field method in combination of microelasticity and electrostatic theories. The research was carried out in close collaboration with a number of experimental groups who used High Resolution Transmission Electron Microscopy (HRTEM), in situ TEM with Scanning Probe Microscopy (SPM), or Piezoresponse Force Microscopy (PFM) to characterize the domain structures and dynamics of ferroelectric thin films and heterostructures and who grow high-quality ferroelectric and multiferroic thin films using advanced growth techniques such as Molecular Beam Epitaxy (MBE), Pulsed Laser Deposition (PLLD), and sputtering. The research efforts of the project help establish the phase-field method as the most powerful method for understanding and predicting domain structures in ferroelectric thin films and nanostructures. The findings of the project led to the basic understanding of stability and switching mechanisms of ferroelectric domains under different mechanical boundary conditions and under either homogeneous capacitor configurations or local fields using metallic probes as electrodes and the emergence of charged domain walls during domain switching. The project predicted the spatial length scales, temperature ranges, and electromechanical conditions for different polar states in heterostructures and guided the discovery of both transient and stable novel polarization states containing vortex lattices in oxide superlattices. The project resulted in 134 journal publications and 6 PhD theses with all the PhD graduates currently working in either academia or industry within the United States. The basic understanding on the stability of mesoscale polar states and pattern evolution achieved by the project improved our ability to control and engineer properties of ferroelectric thin films and heterostructures for potential applications in nanoscale electronic devices.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Forecasting influenza-like illness dynamics for military populations using neural networks and social media

This work is the first to take advantage of recurrent neural networks to predict influenza-like-illness (ILI) dynamics from various linguistic signals extracted from social media data. Unlike other approaches that rely on timeseries analysis of historical ILI data [1, 2] and the state-of-the-art machine learning models [3, 4], we build and evaluate the predictive power of Long Short Term Memory (LSTMs) architectures capable of nowcasting (predicting in \real-time") and forecasting (predicting the future) ILI dynamics in the 2011 { 2014 influenza seasons. To build our models we integrate information people post in social media e.g., topics, stylistic and syntactic patterns, emotions and opinions, and communication behavior. We then quantitatively evaluate the predictive power of different social media signals and contrast the performance of the-state-of-the-art regression models with neural networks. Finally, we combine ILI and social media signals to build joint neural network models for ILI dynamics prediction. Unlike the majority of the existing work, we specifically focus on developing models for local rather than national ILI surveillance [1], specifically for military rather than general populations [3] in 26 U.S. and six international locations. Our approach demonstrates several advantages: (a) Neural network models learned from social media data yield the best performance compared to previously used regression models. (b) Previously under-explored language and communication behavior features are more predictive of ILI dynamics than syntactic and stylistic signals expressed in social media. (c) Neural network models learned exclusively from social media signals yield comparable or better performance to the models learned from ILI historical data, thus, signals from social media can be potentially used to accurately forecast ILI dynamics for the regions where ILI historical data is not available. (d) Neural network models learned from combined ILI and social media signals significantly outperform models that rely solely on ILI historical data, which adds to a great potential of alternative public sources for ILI dynamics prediction. (e) Location-specific models outperform previously used location-independent models e.g., U.S. only. (f) Prediction results significantly vary across geolocations depending on the amount of social media data available and ILI activity patterns.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Summer Workshops on Climate Change Impacts and Integrated Assessment of Climate Change (Final Technical Report)

This grant supported a long sequence of summer workshops in Snowmass, Colorado that began in 1996. The last workshop in this sequence was held in the summer of 2016. This annual event was a centerpiece in the Department of Energy’s support for the creation and maintenance of a community of practice in integrated multi-sector dynamics research and modeling. These workshops brought together key members of the multi-sector dynamics modeling community with other researchers engaged in relevant research on multi-sector (energy, water, land, etc., dynamics) research to participate in discussions of cutting-edge research topics and develop collaborative approaches for addressing open research challenges. This grant provided funds to leverage BER and other federal research investments in the development of appropriate multi-sector dynamics modeling methods by expanding interactions and promoting collaborations between the community of researchers engaged in this research and those involved in other energy and environmental systems research programs. This process is augmented through various outreach activities including periodic presentations and web-based and other internet-based methods for disseminating key scientific findings and to otherwise engage broader participation in pre- and post-workshop discussions and information exchange. The main goals of the summer workshop series were to: Build and support an integrated multi-sector dynamics (iMSD)research community of practice; Infuse best-in-class science into iMSD research activities; Exchange international iMSD research perspectives and information; Accelerate research integration among the iMSD, the sectoral impacts, and earth and environmental systems modeling communities; Develop collaborative scientific perspectives on significant iMSD research challenges; Build collaborations in addressing the challenges; and Develop processes to share information more broadly within the iMSD and the associated family of research communities. The funding provided for this workshop series has helped the energy and environmental systems modeling research community in general - and the multi-sector dynamics research community in particular - make progress on addressing these and other significant research and community building challenges.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Development and Assessment of CTFFuel

This milestone report documents an approach that seeks to develop a standalone fuel solver to simulate steady-state and transient thermo-mechanical responses of light-water reactor fuel rods and assess its temperature predictions against analytical solutions, and a well-known and validated fuel performance code. This manuscript focuses on five major topics: (1) development of the CTFFuel, (2) discussion of the newly implemented fuel deformation models in dynamic gap conductance model of CTFFuel, (3) enabling the dynamic gap conductance model in VERA-CS, (4) verification of the solid conduction solution and comparison of the CTFFuel with respect to the workhorse code, CTF, and (5) benchmark of the thermal conductivity degradation using the burnup dependent fuel thermal conductivity models and benchmark of the fuel centerline temperature using the dynamic gap conductance model with Halden measurements and FRAPCON-4.0 simulation results. CTFFuel temperature predictions are compared to predictions from FRAPCON-4.0 for UO 2 , UO 2 +Gd 2 O 3 and MOX fuels through reactor’s life. The main motivation is to understand discrepancies between CTFFuel and FRAPCON-4.0’s temperature predictions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

cerf: A Python package to evaluate the feasibility and costs of power plant siting for alternative futures

Long-term electric power sector planning and capacity expansion is a key area of interest to stakeholders across a wide range of organizations because it helps in making informed decisions about investments in infrastructure within the context of potential future vulnerabilities under various natural and human stressors. Future power plant siting costs will depend on a number of factors including the characteristics of the electricity capacity expansion and electricity demand (e.g., fuel mix of future electric power capacity, and the magnitude and geographic distribution of electricity demand growth) as well as the geographic location of power plants. Electricity technology capacity expansion plans modeled to represent alternate future conditions meeting a set of scenario assumptions are traditionally compared against historical trends which may not be consistent with current and future conditions. We present the `cerf` Python package (a.k.a., the Capacity Expansion Regional Feasibility model) which helps evaluate the feasibility and structure of future, scenario-driven electricity capacity expansion plans by siting power plants in areas that have been deemed the least cost option while considering dynamic future conditions. We can use `cerf` to gain insight to research topics such as: 1) under what conditions future projected electricity expansion plans from models such as GCAM-USA are possible to achieve, 2) where and which on-the-ground barriers to siting (e.g., protected areas, cooling water availability) may influence our ability to achieve certain expansions, and 3) how electricity infrastructure build-outs and value may evolve into the future when considering locational marginal pricing (LMP) based on the supply and demand of electricity from a grid operations model.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Learning Global Proliferation Expertise Evolution Using AI-Driven Analytics and Public Information

Detecting and anticipating global proliferation expertise and capability evolution from unstructured, noisy, and incomplete public data streams is a highly desired, but extremely challenging task. Here, in this article, we present our pioneering data-driven approach to support the non-proliferation mission to detect and explain the evolution of proliferation expertise and capability development globally from terabytes of publicly available information (PAI), focusing on our knowledge extraction pipeline and descriptive analytics. We first discuss how we fuse nine open-source data streams, including multilingual data, to convert 4 TB of unstructured data to structured knowledge and encode dynamically evolving proliferation expertise representations—content and context graphs. For this, we rely on natural language processing (NLP) and deep learning (DL) models to perform information extraction, topic modeling, and distributed text representation (aka embedding) learning. We then present interactive, usable, and explainable descriptive analytics to refine domain knowledge and present it in a human-understandable form. Finally, we introduce future work avenues that will leverage our dynamic knowledge representations and descriptive analytics to enable predictive and prescriptive inferences to achieve real-time domain understanding and contextual reasoning about global proliferation expertise and capability evolution.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2024

Light Water Reactor Sustainability Program: Use of Time Distributions to Predict Operator Procedure Performance in Dynamic Human Reliability Analysis

The Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) framework affords software capable of conducting human reliability analysis (HRA) using a dynamic approach built around operating procedures (OPs) from nuclear power plants (NPPs). Previous HUNTER reports document the development of this software tool, the coupling of HUNTER to the simulator code, the collection of operator performance data by using simulators to calibrate HUNTER models, and linking HUNTER to probabilistic risk assessment (PRA) software. The present report largely addresses two topics. The first is a new function in HUNTER called the HUNTER Procedure Performance Predictor (P3). HUNTER P3 uses HUNTER’s built in Monte Carlo tools featuring human performance variability to identify potential error traps in procedures. The second topic is time distribution analysis to generate time inputs for dynamic HRA. The current analysis was performed to investigate time distributions for task primitives, which are the minimum task unit of analysis used in dynamic HRA modeling. Using the time distribution data, the elapsed time for human actions in an extended loss of AC power (ELAP) scenario is then investigated. Time data and prediction are essential for modeling procedure performance.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Deep Underground Neutrino Experiment (DUNE) Near Detector Conceptual Design Report

The Deep Underground Neutrino Experiment (DUNE) is an international, world-class experiment aimed at exploring fundamental questions about the universe that are at the forefront of astrophysics and particle physics research. DUNE will study questions pertaining to the preponderance of matter over antimatter in the early universe, the dynamics of supernovae, the subtleties of neutrino interaction physics, and a number of beyond the Standard Model topics accessible in a powerful neutrino beam. A critical component of the DUNE physics program involves the study of changes in a powerful beam of neutrinos, i.e., neutrino oscillations, as the neutrinos propagate a long distance. The experiment consists of a near detector, sited close to the source of the beam, and a far detector, sited along the beam at a large distance. This document, the DUNE Near Detector Conceptual Design Report (CDR), describes the design of the DUNE near detector and the science program that drives the design and technology choices. The goals and requirements underlying the design, along with projected performance are given. It serves as a starting point for a more detailed design that will be described in future documents.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

An Evaluation of The Dynamic Physical Security Risk Assessment Methodology for Fleet-Wide Applications

The requirements for U.S. nuclear power plants to maintain a large onsite physical security force contribute to their high 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 (LWRS) program’s physical security pathway is to develop tools, methods, and technologies and provide the technical basis for an optimized physical security posture. The conservatisms built into current security postures may be analyzed and minimized to reduce security costs while still ensuring adequate security and operational safety. The research performed at Idaho National Laboratory within LWRS program’s physical security pathway has successfully developed a dynamic force-on-force modeling framework using various computer simulation tools and integrating them with the dynamic assessment Event Modeling Risk Assessment using Linked Diagrams (EMRALD) tool. This integrated process for physical security analysis is named Modeling and Analysis for Safety Security using Dynamic EMRALD Framework (MASS-DEF). This document provides an update on the progress in applying the MASS-DEF process to an operating commercial nuclear power plant as well as additional industry feedback regarding use of the tool for other physical security risk-informed topics. This report is only a summary of the progress and does not contain specific modeling results as those contain sensitive security information. Previous reports described how a user could integrate their plant-specific force-on-force models with the dynamic simulation tool EMRALD, model operator actions, and integrate with probabilistic risk assessment tools, such as CAFTA (Computer Aided Fault Tree Analysis System) or SAPHIRE (Systems Analysis Programs for Hands-on Integrated Reliability Evaluations), and with thermal-hydraulic tools, such as RELAP-5 or MAAP. Previous reports applied various combinations of available simulations codes with EMRALD using generic plant models to demonstrate how to perform the analysis. This report is an update the progress of applying the dynamic computational framework to an actual nuclear facility using their security scenarios and timelines. This report also provides an update to the procedural guidance for the MASS-DEF process and an overview of the generic models available for use by utilities. This report does not contain any plant’s sensitive information and/or safeguards information. This study’s purpose was to verify that the results achieved using generic models are similar to actual plant results and refine our guidance on the use of the framework. This assessment enables further analysis, such as what-if scenarios and staff-reduction evaluation, thereby optimizing physical security at plants.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗