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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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At least 901 records · Page 50

Coupled Neutronics - Thermal-Hydraulics - Thermomechanics modeling of Molten Chloride Reactor

Molten Salt Reactors (MSRs) are innovative Generation-IV nuclear reactors known for their enhanced safety features, fuel economy, and fuel cycle advancements. However, designing and studying these reactors present unique safety and modeling challenges. The Department of Energy (DOE)'s Nuclear Energy Advanced Modeling and Simulation program addresses these challenges through the development of flexible multi-fidelity, multiphysics simulation tools. This study exemplifies NEAMS tools' capabilities by modeling a chloride-based micro-MSR: Griffin for neutronics simulations, Pronghorn for thermal-hydraulics simulations, and BISON for thermomechanics simulations. These tools are integrated into a comprehensive 3D multiphysics model, successfully capturing steady-state and transient reactor operations. A loss of flow accident is examined as an illustrative example of transient behavior. Additionally, this paper contributes to demonstrating the theoretical feasibility of micro-MSR concepts, which have received less attention compared to other designs. The subsequent sections provide a brief description of the MSR concept studied, an overview of the computational tools used, and present results for both steady-state operation and a loss of flow accident.

42 - ENGINEERING↗

Charging Decision Making for Automated Electric Vehicles

Abstract: Overview/Significance With the emerging of autonomous driving and its application in electric vehicles, the charging decision making should be taken over by the vehicles. Autonomous electric vehicles will require the capability to make charging decisions according to the battery energy state, the travel demand and also the available charging infrastructure. The introduction of autonomous driving technology would remove the challenge of co-locating charging infrastructure with driver destinations and presents a driver-free method for EVs to reach nearby charging stations. This will significantly change the charging behavior of electric vehicles. EV driver will no longer need to be present at charging stations for charging actions. Automated EVs can drive to nearby charging stations to perform charging actions by themselves when necessary. Meanwhile, connected vehicles technology makes electric vehicles have the capability to sense and obtain pertinent information from nearby charging station networks and then calculate the corresponding costs and availability for charging. All these promising capabilities bring new opportunities to construct an automatic charging decision making system and improve energy efficiency of charging actions for automatic electric vehicles. Abstract: Methodology This research introduces optimization tools and case studies on charging decision making for automated electric vehicles under personal usage scenario. The designed optimization tools aim to provide charging strategies, i.e. the optimal choice of charging station outside home and the amount of charged energy, by considering constraints from personal daily itineraries and existing charging infrastructure. Abundant real world EV data is utilized to construct stochastic energy consumption prediction model under realistic driving conditions. Advanced dynamic programming technology is utilized to model and solve the potential multi-stage decision making process by considering realistic uncertainties of EV energy cost and dynamics of itinerary information. Large-scale simulation studies using Chicago itinerary data are demonstrated to illustrate energy benefits from automatic charging decision making for future autonomous EVs. Abstract: Results/Conclusions Optimal automatic charging decision making and its energy benefits have been studied for personal automated electric vehicles. A data-driven method based on large amount of real-world data and the corresponding real-time update algorithm have been proposed to construct multi-channel stochastic energy consumption prediction model. Based on the energy cost prediction, dynamic multi-stage charging decision-making models are established for optimal strategies during a daily itinerary. Derived charging strategies can minimize the monetary and energy cost of charging actions for autonomous vehicles. Simulations and case studies show the potential ability of autonomous electric vehicles to reduce the range anxiety and charging infrastructure dependency. Automatic charging decision making can mitigate the pain from electric vehicle charging necessity outside home. In conclusion, automated electric vehicles equipped with an appropriate automatic charging decision making system will help EV driver to relieve from heavy time cost of recharging, reduce the energy cost of performing charging actions and improve the energy efficiency in future electrified transportation system.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

SAM Theory Manual

The System Analysis Module (SAM) is an advanced and modern system analysis tool being developed at Argonne National Laboratory under the U.S. DOE Office of Nuclear Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. SAM development aims for advances in physical modeling, numerical methods, and software engineering to enhance its user experience and usability for reactor transient analyses. To facilitate the code development, SAM utilizes an object-oriented application framework (MOOSE), and its underlying meshing and finite-element library (libMesh) and linear and non-linear solvers (PETSc), to leverage modern advanced software environments and numerical methods. SAM focuses on modeling advanced reactor concepts such as SFRs (sodium fast reactors), LFRs (lead-cooled fast reactors), and FHRs (fluoride-salt-cooled high temperature reactors) or MSRs (molten salt reactors). These advanced concepts are distinguished from light-water reactors in their use of single-phase, low-pressure, high-temperature, and low Prandtl number (sodium and lead) coolants. As a new code development, the initial effort has been focused on modeling and simulation capabilities of heat transfer and single-phase fluid dynamics responses in Sodium-cooled Fast Reactor (SFR) systems. The system-level simulation capabilities of fluid flow and heat transfer in general engineering systems and typical SFRs have been verified and validated. This document provides the theoretical and technical basis of the code to help users understand the underlying physical models (such as governing equations, closure models, and component models), system modeling approaches, numerical discretization and solution methods, and the overall capabilities in SAM. As the code is still under ongoing development, this SAM Theory Manual will be updated periodically to keep it consistent with the state of the development.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

New Virtual Test Bed Capabilities: Virtual DOME Model and New Updates to Repository

The Department of Energy (DOE) Office of Nuclear Energy National Reactor Innovation Center accelerates the deployment of novel reactor concepts by establishing both physical and virtual spaces for building and testing various components, systems, and complete pilot plants. The Virtual Test Bed represents the virtual arm of the National Reactor Innovation Center and is a joint effort with the DOE Nuclear Energy Advanced Modeling and Simulation Program. The Virtual Test Bed mission is to accelerate the deployment of advanced reactors by facilitating the adoption of cutting-edge DOE advanced modeling and simulation tools to design, evaluate, and license reactors. This is primarily achieved by storing example challenge problems in an externally available repository and by developing models to fill the M&S gaps needed for potential demonstrators. Activities conducted this fiscal year focused on developing of a Demonstration of Microreactor Experiments shield model to help accelerate the confirmatory analysis required for the reactor demonstration. This model and workflow will allow developers to leverage advanced modeling and simulation tools to ensure their reactor demonstration concept will meet dose requirements and that the surrounding shield will stay within concrete temperature limits during steady-state and transient operation conditions. An initial model has been developed to evaluate the temperature distribution in the concrete shield during steady-state operation, including neutron and gamma heating effects. Various modeling strategies have been examined to understand their applicability and limitations with different reactor designs to make the workflow as reactor-agnostic as possible and computationally effective to maximize its usability. In addition to describing the Demonstration of Microreactor Experiments shield model and associated results, this report summarizes other accomplishments regarding repository maintenance and improvement and new external models hosted on the repository.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

(U) Ristra Next Generation Code Report

LANL’s Weapons Physics management (ADX) and ASC program office have defined a strategy for exascale-class application codes that follows two supportive, and mutually risk-mitigating paths: evolution for established codes (with a strong pedigree within the user community) based upon existing programming paradigms (MPI+X); and Ristra (formerly known as NGC), a high-risk/high-reward push for a next-generation multi-physics, multi-scale simulation toolkit based on emerging advanced programming systems (with an initial focus on data-flow task-based models exemplified by Legion [5]). Development along these paths is supported by the ATDM, IC, and CSSE elements of the ASC program, with the resulting codes forming a common ecosystem, and with algorithm and code exchange between them anticipated. Furthermore, solution of some of the more challenging problems of the future will require a federation of codes working together, using established-pedigree codes in partnership with new capabilities as they come on line. The role of Ristra as the high-risk/high-reward path for LANL’s codes is fully consistent with its role in the Advanced Technology Development and Mitigation (ATDM) sub-program of ASC (see Appendix C), in particular its emphasis on evolving ASC capabilities through novel programming models and data management technologies.

97 MATHEMATICS AND COMPUTING↗

Quasielastic lepton-nucleus scattering and the correlated Fermi gas model

The neutrino research program in the coming decades will require improved precision. A major source of uncertainty is the interaction of neutrinos with nuclei that serve as targets for such experiments. Broadly speaking, this interaction often depends, e.g., for charge-current quasielastic scattering, on the combination of “nucleon physics,” expressed by form factors, and “nuclear physics,” expressed by a nuclear model. It is important to get a good handle on both. We present a fully analytic implementation of the correlated Fermi gas model for electron-nucleus and charge-current quasielastic neutrino-nucleus scattering. The implementation is used to compare separately form factors and nuclear model effects for both electron-carbon and neutrino-carbon scattering data. Published by the American Physical Society 2025

Bhattacharya, Bhubanjyoti (ORCID:000000032238321X)↗

Sockeye Heat Pipe Analysis Code Verification and Validation

Some of the most promising microreactor designs currently under development utilize heat pipe technology to transfer heat from the reactor core to the secondary side heat exchanger, due to the technology’s compactness, efficiency, passivity, and reliability. Sockeye is an engineering-scale heat pipe tool developed under the Nuclear Energy Advanced Modeling and Simulation Program to be used for the design and safety analysis of microreactors. Sockeye’s core capability lies in a 1D, two-phase, compressible flow model, used to simulate the working fluid inside the heat pipe. Sockeye is built on the Multiphysics Object-Oriented Simulation Environment framework, which allows for seamless multiphysics coupling with other Nuclear Energy Advanced Modeling and Simulation tools and can thus be used in a full-scale simulation of a microreactor assembly, which can include hundreds of heat pipes. This paper presents some initial verification and validation assessments performed for Sockeye. We demonstrate good agreement between Sockeye’s numerical results and steady-state analytic solutions for velocity and pressure drop, with differences attributable to the underlying assumptions made by the analytic solutions. We also show that Sockeye reproduces analytic predictions of key operational limits, such as the capillary limit and the sonic limit. Finally, we compare Sockeye results to experimental data for the SAFE-30 heat pipe module test.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

BEPAM Model Code and CABBI Simulation Results for "Assessing the Returns to Land and Greenhouse Gas Savings from Producing Energy Crops on Conservation Reserve Program Land"

This dataset contains BEPAM model code and input data to the replicate the results for "Assessing the Returns to Land and Greenhouse Gas Savings from Producing Energy Crops on Conservation Reserve Program Land." The dataset consists of: (1) The replication codes and data for the BEPAM model. The code file is named as output_0213-2020_Complete_daycent-agversion-[rental payment level]%_[biomass price].gms. (BEPAM-CRP model-Sep2020.zip) (2) Simulation results from the BEPAM model (BEPAM_Simulation_Results.csv) * Item (1) is in GAMS format. Item (2) is in text format.

biomass price↗

Estimating the Drivers of the Cost of Saved Electricity in Utility Customer-Funded Energy Efficiency Programs

Energy efficiency programs funded by utility customers provide an electricity resource in most U.S. states, but their scale and cost of saving electricity varies significantly by state. In this paper, we explore the drivers of the cost of saved electricity in these programs with an econometric model and nearly a decade of data reported by efficiency program administrators. We found strong evidence for economies of scale and weak evidence for diseconomies of scale, which suggests that states with low levels of efficiency savings relative to retail sales can increase the size of their efficiency programs without large increases to the cost of saved electricity. We discuss examples of energy efficiency forecasting and potential modeling in light our econometric analysis and identify methodological improvements relevant to utilities and grid operators. This paper provides insights into the economics of customer-funded efficiency programs that will support regulators, utilities, and policymakers to utilize energy efficiency as a resource.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Measurements of Decay and Snapback in Nb₃Sn Accelerator Magnets at Fermilab

In recent years, Fermilab has been executing an inten-sive R&D program on Nb₃Sn accelerator magnets. This program has included dipole and quadrupole models and demonstrators for various programs and projects, including the HL-LHC accelerator upgrade project. A systematic study of the field decay and snapback during the injection portion of a simulated accelerator cycle was executed at the Fermilab Magnet Test Facility. This paper summarizes the recent measurements of the MQXFS1 short quadrupole model and discusses the results of some previously measured Nb₃Sn magnets at CERN

43 PARTICLE ACCELERATORS↗

Refining perovskite structures to pair distribution function data using collective Glazer modes as a basis

Structural modelling of octahedral tilts in perovskites is typically carried out using the symmetry constraints of the resulting space group. In most cases, this introduces more degrees of freedom than those strictly necessary to describe only the octahedral tilts. It can therefore be a challenge to disentangle the octahedral tilts from other structural distortions such as cation displacements and octahedral distortions. This paper reports the development of constraints for modelling pure octahedral tilts and implementation of the constraints in diffpy-CMI, a powerful package to analyse pair distribution function (PDF) data. The model in the program allows features in the PDF that come from rigid tilts to be separated from non-rigid relaxations, providing an intuitive picture of the tilting. The model has many fewer refinable variables than the unconstrained space group fits and provides robust and stable refinements of the tilt components. It further demonstrates the use of the model on the canonical tilted perovskite CaTiO 3 which has the known Glazer tilt system α + β – β – . The Glazer model fits comparably to the corresponding space-group model Pnma below r = 14 Å and becomes progressively worse than the space-group model at higher r due to non-rigid distortions in the real material.

36 MATERIALS SCIENCE↗

Simulations of the High Temperature Test Facility using SAM

Under the support from the U.S. Department of Energy Office of Nuclear Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, an effort is being pursued to support the modeling and simulation needs of high-temperature gas-cooled reactor (HTGR) technology development. There is a particular need for advanced modeling and simulation methods and tools to predict thermal-fluid behavior in the nuclear reactor primary system during safety-related transients. This report focuses on one such activity related to HTGR: developing a model of the High Temperature Test Facility (HTTF) at Oregon State University using the system-level code SAM, and using the model to understand thermal response behavior in the facility. Note this activity is coordinated with the DOE-NE’s Advanced Reactor Technology Gas-Cooled Reactor Program

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Compare Mechanistic Predictions for Doped UO 2 Mechanical Response and Other Properties with Empirical Models and Experimental Measurements

The U.S. Department of Energy’s Nuclear Energy Advanced Modeling and Simulation program develops predictive capabilities using computational methods for the analysis and design of advanced reactor and fuel cycle systems. This program has been supporting the development of BISON, a high-fidelity, high resolution fuel performance tool at the engineering scale. As part of its development, additional modeling capabilities and improvements have been developed for relevant fuel forms. In this work, a fuel creep deformation model for Cr-doped fuel has been implemented into BISON, along with improvements to the empirical UO 2 fuel creep model based on experimental data and improvements to the radial power factor calculation for doped fuels. This work allows for more accurate simulation analyses for both UO 2 and doped-UO 2 fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Multiscale Electricity Modeling for Evaluating Carbon Capture and Sequestration Technologies (MEME-CCS)

This effort employs and adapts a rigorous multiscale electricity modeling platform at the National Renewable Energy Laboratory (NREL) to evaluate carbon capture and sequestration (CCS) and negative emissions technologies (NET) from the ARPA-E FLECCS program. NREL's modeling platform includes the Regional Energy Deployment System (ReEDS) electric sector capacity expansion model, which projects future electricity generation mixes at sub-state-level resolution that are downscaled to the unit-level to enable hourly, zonal or nodal electricity production cost modeling in the PLEXOS model. The ReEDS-PLEXOS modeling suite is well-established for examining electric sector futures with high renewable energy penetrations, energy storage, electrification, and distributed generation. The key advancement proposed herein utilizes collaboration with CCS experts at the University of Wyoming (U.WY) and the FLECCS technology development teams to create innovative methods for representing CCS and NET in the ReEDS and PLEXOS models. Expanded technology options and new operational parameterizations are integrated into these models to allow an unprecedented combination of scope and resolution for exploring the future of CCS and NET. The resulting capabilities permit wide-ranging scenario analysis to assess CCS and NET deployment under alternative scenarios of CO2 prices and competitiveness of flexible CCS and NET technologies. We demonstrate sample deployment and operational outcomes to show how these models are being used to assess the future potential for FLECCS technologies and their impacts on the U.S. electricity system. These products will help an emerging CCS/NET industry in the United States by providing economics-driven guidance to technology developers while informing policy and investment decisions in the public and private sectors.

capacity expansion↗

NSR&D Program Fiscal Year 2015 Funded Research Stochastic Modeling of Radioactive Material Releases Final Report

Nonreactor nuclear facilities operating under the approval authority of the U.S. Department of Energy use unmitigated hazard evaluations to determine if potential radiological doses associated with design basis events challenge or exceed dose evaluation guidelines. Unmitigated design basis events that sufficiently challenge dose evaluation guidelines or exceed the guidelines for members of the public or workers, merit selection of safety structures, systems, or components or other controls to prevent or mitigate the hazard. Idaho State University, in collaboration with Idaho National Laboratory, has developed a portable and simple to use software application called SODA (Stochastic Objective Decision-Aide) that stochastically calculates the radiation dose distribution associated with hypothetical radiological material release scenarios. Rather than producing a point estimate of the dose, SODA produces a dose distribution result to allow a deeper understanding of the dose potential. SODA allows users to select the distribution type and parameter values for all of the input variables used to perform the dose calculation. Users can also specify custom distributions through a user defined distribution option. SODA then randomly samples each distribution input variable and calculates the overall resulting dose distribution. In cases where an input variable distribution is unknown, a traditional single point value can be used. SODA, developed using the MATLAB coding framework, has a graphical user interface and can be installed on both Windows and Mac computers. SODA is a standalone software application and does not require MATLAB to function. SODA provides improved risk understanding leading to better informed decision making associated with establishing nuclear facility material-at-risk limits and safety structure, system, or component selection. It is important to note that SODA does not replace or compete with codes such as MACCS or RSAC; rather it is viewed as an easy to use supplemental tool to help improve risk understanding and support better informed decisions. The SODA development project was funded through a grant from the DOE Nuclear Safety Research and Development Program.

42 ENGINEERING↗

Coupled aero-hydro-geotech real-time hybrid simulation of offshore wind turbine monopile structures

Real-time hybrid simulation (RTHS) divides a structural system into an analytical and experimental substructure. The former is based on a well-established analytical model while the latter consists of a physical model in the laboratory, for which there is not a well-established analytical model. This paper extends real-time hybrid simulation to monopile-type Offshore Wind Turbines (OWTs) to enable the investigation of their behavior considering the response of pile foundations under operational and more severe conditions. The embedded foundation and surrounding soil of the OWT are modeled physically in a soil box in the laboratory while the remaining parts of the system and loading are modeled analytically. The program OpenFAST, developed by the National Renewable Energy Laboratory (NREL), is linked to the RTHS coordinator to determine the hydrodynamic and aerodynamic loads acting on the OWT, along with modeling the dynamics of the electric power generation equipment and associated controller for the OWT. The RTHS framework along with its initial implementation and validation are described in this paper. RTHSs of a 5 MW OWT subjected to operational and more severe conditions are performed to experimentally validate the framework. The framework offers a realistic approach to investigate the behavior of OWT structures supported on monopiles. Furthermore, this approach accounts for the coupled response of the OWT structure with its foundation, while experimentally capturing the nonlinearities of the soil-foundation interaction in real-time.

17 WIND ENERGY↗

BISON Capability to Account for Dopant Sensitivity in Relevant UO 2 Material Models

The U.S. Department of Energy’s Nuclear Energy Advanced Modeling and Simulation program aims to develop predictive capabilities using computational methods for the analysis and design of advanced reactor and fuel cycle systems. This program has been supporting the development of BISON, a high-fidelity and high-resolution fuel performance tool at the engineering scale. Incorporation of more physics-based models in BISON for the accident tolerant fuel applications motivated this study. This document details integration of new modeling capabilities in BISON, including: a tensile strength model for uranium dioxide (UO 2 ) fuel to incorporate the microstructural effects (e.g., grain size, fabrication pore size, and porosity), and atomistic-informed creep model for UO 2 fuel that is developed by Los Alamos National Laboratory. Sensitivity analyses are conducted on these models separately as well as a two-dimensional full rod application under normal operating conditions. Lastly, these new modeling capabilities in BISON are exercised in Halden IFA-677.1 and IFA-716.1 assessment cases.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Extension of Virtual Test Bed Advanced Modeling and Simulation Capabilities for Fusion Energy

The National Reactor Innovation Center (NRIC) was established to accelerate the deployment of novel reactor concepts. This is achieved by providing physical and virtual spaces for building and testing reactor experiments. The Virtual Test Bed (VTB) represents the virtual counterpart to the physical test beds. It is a collaboration with the Department of Energy’s (DOE) Nuclear Energy Advanced Modeling and Simulation (NEAMS) program with the mission to accelerate the deployment of advanced reactors by facilitating the adoption of advanced modeling and simulation (M&S) tools developed by the DOE. This mission has been carried out by the VTB since 2020 by hosting and featuring dozens of advanced fission nuclear reactor models developed by national laboratories and academia. The charter of the NRIC’s definition of advanced reactors also includes fusion nuclear reactors. As the tools developed by the NEAMS program are increasingly used for modeling fusion energy devices, there is an increasing need to host fusion reactor models on the VTB repository. The VTB will be extended in 2024 to support fusion energy modeling and simulation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗