Search NASA⌕ Search

SEARCH · Search NASA

Results for “multiphysics tool”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Demonstration and Verification of Thermo-Mechanical Bowing in a Limited Free-Bow SFR Concept Using MOOSE

Core bowing due to thermal gradients and irradiation induced swelling and creep introduces significant reactivity feedback effects in liquid metal-cooled fast spectrum reactors. During startup, normal operations, and transient events, differential thermal and flux gradients cause expansion, creep, and swelling, which results in bowing in preferential directions depending on local material properties and load-pad and restraint-ring design. The bowing phenomenon produces negative reactivity during accident conditions provided the restraint system has been properly designed to optimally guide the deformation outwards in the active core region. Under the Department of Energy Nuclear Energy Advanced Modeling and Simulation program, a Multiphysics Object Oriented Simulation Environment (MOOSE)-based multiphysics approach to model core bowing is being developed. The present work expands on previous modeling of simpler International Atomic Energy Agency (IAEA) verification problems with these tools by modeling IAEA Verification Problem 4, which involves a symmetric sector of a reactor core with ducted assemblies undergoing differential thermal expansion due to thermal gradients bowing outward with duct-to-duct contact. This model is available on the National Reactor Innovation Center Virtual Test Bed repository. This example was verified against benchmark participant results, which includes bowing deformation evaluation and duct-to-duct interactions at load pads with mechanical contact.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

New developments and verification of fusion blanket simulation capabilities in the MOOSE framework

Multiphysics modeling capabilities have a crucial role to play in the accelerated deployment of fusion energy. To that end, we developed new multiphysics fusion blanket simulation capabilities in the Multiphysics Object-Oriented Simulation Environment (MOOSE). Firstly, we expanded on the existing capabilities of the previously published work, by coupling 3D tritium transport modeling capabilities using the Tritium Migration Analysis Program, version 8 (TMAP8) to an existing tool including thermal hydraulics, fully three-dimensional (3D) heat transfer, and loosely coupled neutronics analysis. Secondly, we performed a thorough verification of the new capabilities and increased testing code coverage to meet MOOSE’s software quality standards. The MOOSE framework follows a strict software quality assurance plan to be Nuclear Quality Assurance, Level 1 compliant. The new multiphysics fusion blanket simulation capabilities are now held to the same standard. Thirdly, to demonstrate MOOSE’s new fusion blanket modeling capabilities, we performed a fully integrated, multiphysics simulation of a 3D solid ceramic breeder blanket design. This proof-of-concept simulation provides the temperature and tritium distribution across the blanket. In conclusion, the combined efforts towards software quality and the development of multiphysics coupling capabilities provide an effective and reliable framework for modeling solid ceramic fusion blankets using MOOSE.

modeling and simulation↗
DOE OSTI2021

Sockeye: A One-Dimensional, Two-Phase, Compressible Flow Heat Pipe Application

Sockeye is a heat pipe analysis application based on the Multiphysics Object-Oriented Simulation Environment (MOOSE) finite element framework. The primary purpose of Sockeye is to provide a transient heat pipe simulation tool to be used in the analysis of nuclear microreactor designs. Sockeye provides the capability to perform one-dimensional, two-phase, compressible flow simulation of a heat pipe working fluid and two-dimensional, axisymmetric heat conduction for the heat pipe cladding and its surroundings. Sockeye is demonstrated against analytical solutions and experimental data from the SAFE-30 heat pipe module test.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Integrating Immersive Visualization in Molten-Salt Reactor Waste Management for Experimental Design and Planning

Molten-salt reactors (MSRs) represent a promising solution for next-generation nuclear energy, offering advantages in safety, fuel efficiency, and waste minimization. However, their liquid-fueled design presents unique challenges for spent fuel management, making post-shutdown waste characterization essential for developing effective strategies. Despite this need, there is a notable absence of visualization platforms specifically tailored to the unique characteristics and analytical requirements of MSR waste management. Existing tools in the nuclear industry are primarily designed for reactor operations or generic data exploration and lack both integration with MSR-specific multiphysics frameworks and the ability to simultaneously visualize time-dependent thermal fields, chemical composition evolution, and radiation distribution patterns. To address these limitations, this paper presents an immersive virtual reality (VR) visualization platform that processes and displays high-fidelity multiphysics simulation output from the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework in real-time, using Unity. The platform visualizes MSR waste characteristics such as nuclide decay, salt cooling, and corrosion by using Exodus II output data and running on a VR headset. It includes a user-friendly interface with features such as visibility toggling, cross-sectional slicing, and time-series animation for exploring simulation data. These capabilities support experimental design, stakeholder engagement, and public communication by making complex reactor behavior more accessible and understandable. By enhancing spatial reasoning and reducing cognitive load, this immersive environment fosters more effective communication and decision-making in MSR waste management.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Useability and Optimization Improvements in MOOSE

The Multiphysics Object-Oriented Simulation Environment (MOOSE) framework is a foundational capability used by the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program to create over 15 different simulation tools for advanced nuclear reactors. Due to this broad use, improvements to the framework in support of modeling and simulation goals are critical to the program. These improvements can take many forms, including optimization, improved user experience, streamlined application programming interfaces (APIs), parallelism, and new capabilities. The work transcribed in this report was conducted in direct support of the simulation tools and has already been deployed or will be deployed in the coming months. The capabilities were implemented in the same order as they are covered in this report: increased support of face variables, arbitrary spatial and temporal evaluation of material properties, and the addition of a triangular meshing library in libMesh.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Multiphysics Analysis of the MSRE Experiment Using Griffin-SAM Coupled Code System

Molten salt reactors (MSRs) with flowing fuel have the unique feature of utilizing the fuel salt for heat generation and extraction at the same time since the fuel salt is circulating through the whole primary loop of the reactor. This movement of the fuel salt results in a partial decay of the delayed neutron precursors (DNPs) outside the core and corresponding redistribution in the active core region. To capture this phenomenon accurately, neutronics and thermal hydraulics computational tools need to be modified to handle the movement of the DNPs and their decay. Idaho and Argonne National Laboratories are actively working on developing neutronics and thermal hydraulics tools to model MSRs with flowing fuel. The neutronics code Griffin and the thermal hydraulics code SAM were extended to handle flowing fuel with the drift of the DNPs under the MOOSE framework. In this work, a simplified Multiphysics model of the Molten Salt Reactor Experiment (MSRE) is developed and utilized to perform steady-state and transient analyses. The MSRE experiments were designed to show the impact of the DNPs losses on core reactivity. The following section provides a description of the MSRE experiment with the core main parameters used to develop the model. Then, the developed Multiphysics model of the MSRE is presented. Finally, steady-state verification tests and unprotected loss of flow transient tests are discussed followed by a summary and conclusions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

NEAMS Technical Area Support in MOOSE

The Multiphysics Object-Oriented Simulation Environment (MOOSE) framework is a foundational capability used by the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program to create over 15 different simulation tools for advanced nuclear reactors. Due to this ubiquity, improvements to the framework in support of modeling and simulation goals are critical to the program. These improvements can take many forms, including optimization, improved user experience, streamlined application programming interfaces (APIs), parallelism, and new capabilities. The work transcribed in this report was conducted in direct support of the simulation tools and has already been deployed. The capabilities outlined in this report include a factor of 10^4 improvement in dependency resolution speed, sorting of user objects, ability to compute residuals and Jacobians together, transfer fixes, support for the mortar method in finite volume discretizations, addition of generalized advection schemes for fluid simulations, 10^2 speedup in some Griffin simulations due to a new matrix-only solve type, and much more.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Improvements in High Temperature Gas Cooled Reactor Modeling Capabilities in the Pronghorn Code

This report details the improvement of pebble bed reactor modeling capabilities in the Pronghorn code in fiscal year 2022. The following accomplishments are reported: Deployment of weakly compressible finite volume formulation to the HTR- PM reference plan model; Enable modeling of stagnant gas gaps in the finite volume formulation; Enable using all Pronghorn correlations available in the finite element version in the finite volume version; Modeling of decay heat in pebble bed reactors; Simplifying the input for multiphysics equilibrium core calculations and significant reduction of execution time; Implementation of advanced correlations developed by the Center of Excellence for Thermal-Fluids Applications in Nuclear Energy . In addition, this report includes a development plan for Pronghorn and associated NEAMS tools for prismatic gas-cooled reactors.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Usability and Optimization Improvements in MOOSE

The Multiphysics Object-Oriented Simulation Environment (MOOSE) framework is a foundational capability used by the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program to create over 15 different simulation tools for advanced nuclear reactors. Due to MOOSE’s broad use, improvements to the framework in support of modeling and simulation goals are critical to the program. Such improvements can take many forms, including optimization, improved user experience, streamlined application programming interfaces (APIs), parallelism, and new capabilities. The work described in this report was conducted in direct support of the simulation tools and has already been deployed. The capabilities were implemented in the same order as they are covered in this report: multiple nonlinear systems in the same input file, implementation of generic field transfers and other transfer system enhancements, support for stateful material property redistribution for adaptivity and distributed meshes, and dynamic linking and loading of individually compiled applications. These four additions are fundamental capabilities that will be leveraged by many NEAMS applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

BISON: A Flexible Code for Advanced Simulation of the Performance of Multiple Nuclear Fuel Forms [Slides]

As fuel vendors and designers pursue the development of advanced reactors or the increase in burnup limits for existing reactors, advanced computational tools are necessary to understand the fuel performance. BISON, a fuel performance code developed primarily at Idaho National Laboratory, which is built upon the Multiphysics Object-Oriented Simulation Environment (MOOSE), provides capabilities to analyze multiple nuclear fuel forms in a wide variety of dimensions. Since its inception, BISON has been used to investigate the performance of light-water reactor fuel rods, accident tolerant fuel concepts, metallic and mixed-oxide (MOX) fuels for fast reactors, plate fuels for research reactors, and tri-structural isotropic (TRISO) fuel particles. This talk will provide a history of BISON, highlights of major development milestones, tributes to key contributors, and applications of its use to various fuel forms in one-, two-, and three-dimensions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Coupled Multiphysics Primary Loop Simulations of the Mk1-FHR in the Virtual Test Bed

To support advanced reactor demonstrations, the Virtual Test Bed (VTB) [1] repository hosts a wide range of challenge problems for showcasing modeling and simulation capabil- ities in support of advanced reactor demonstrations. This document presents a coupled multiphysics model of the Mark 1 pebble-bed fluoride-salt-cooled high-temperature reactor (PB-FHR). The analysis leverages NEAMS tools (Griffin [2], SAM [3], Pronghorn [4], and the MOOSE [5] heat con- duction module) for core neutronics, thermal hydraulics of the core and primary loop, and multiscale fuel performance simulations. The analysis was entirely created by coupling standalone simulations of the reactor that were previously available on the VTB. All input files and documentation de- veloped for this example are available on the VTB website: mooseframework.inl.gov/ virtual_test_bed/ . This model was featured in the National Reactor Innovation Cen- ter Tech Talk presented in December 2021.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Marmot V2

MARMOT is a robust numerical tool for mesoscale modeling of fuel performance developed under the NEAMS Fuels technical area to predict the coevolution of microstructure and properties in fuel and cladding materials. MARMOT accomplishes this using the phase field method coupled with finite strain mechanics and heat conduction. MARMOT is based on the open source Multiphysics Object-Oriented Simulation Environment (MOOSE) and solves the coupled partial differential equations defining the physics using the finite element method. MARMOT is being developed in order to facilitate the development of improved materials models for fuel performance, but it is also being developed as a powerful tool in and of itself for the simulation of mesoscale fuel performance.

Aagesen, LarryK.↗
DOE OSTI2017

FY17 Status Report on NEAMS Neutronics Activities

Under the U.S. DOE NEAMS program, the high-fidelity neutronics code system has been developed to support the multiphysics modeling and simulation capability named SHARP. The neutronics code system includes the high-fidelity neutronics code PROTEUS, the cross section library and preprocessing tools, the multigroup cross section generation code MC2-3, the in-house meshing generation tool, the perturbation and sensitivity analysis code PERSENT, and post-processing tools. The main objectives of the NEAMS neutronics activities in FY17 are to continue development of an advanced nodal solver in PROTEUS for use in nuclear reactor design and analysis projects, implement a simplified sub-channel based thermal-hydraulic (T/H) capability into PROTEUS to efficiently compute the thermal feedback, improve the performance of PROTEUS-MOCEX using numerical acceleration and code optimization, improve the cross section generation tools including MC2-3, and continue to perform verification and validation tests for PROTEUS.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Multi-physics Preconditioning for Thermally Activated Batteries

Thermal batteries, also known as molten-salt batteries, are single-use reserve power systems activated by pyrotechnic heat generation, which transitions the solid electrolyte into a molten state. The simulation of these batteries relies on multiphysics modeling to evaluate performance and behavior under various conditions. This paper presents advancements in scalable preconditioning strategies for the Thermally Activated Battery Simulator (TABS) tool, enabling efficient solutions to the coupled electrochemical systems that dominate computational costs in thermal battery simulations. We propose a hierarchical block Gauss-Seidel preconditioner implemented through the Teko package in Trilinos, which effectively addresses the challenges posed by tightly coupled physics, including charge transport, porous flow, and species diffusion. The preconditioner leverages scalable subblock solvers, including smoothed aggregation algebraic multigrid (SA-AMG) methods and domain-decomposition techniques, to achieve robust convergence and parallel scalability. Strong and weak scaling studies demonstrate the solver’s ability to handle problem sizes up to 51.3 million degrees of freedom on 2048 processors, achieving near sub-second setup and solve times for the end-to-end electrochemical solve. These advancements significantly improve the computational efficiency and turnaround time of thermal battery simulations, paving the way for higher-resolution models and enabling the transition from 2D axisymmetric to full 3D simulations.

25 ENERGY STORAGE↗
DOE OSTI2023

Fast and accurate reduced-order modeling of a MOOSE-based additive manufacturing model with operator learning

One predominant challenge in additive manufacturing (AM) is to achieve specific material properties by manipulating manufacturing process parameters during the runtime. Such manipulation tends to increase the computational load imposed on existing simulation tools employed in AM. The goal of the present work is to construct a fast and accurate reduced-order model (ROM) for an AM model developed within the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, ultimately reducing the time/cost of AM control and optimization processes. Our adoption of the operator learning (OL) approach enabled us to learn a family of differential equations produced by altering process variables in the laser’s Gaussian point heat source. More specifically, we used the Fourier neural operator (FNO) and deep operator network (DeepONet) to develop ROMs for time-dependent responses. Furthermore, we benchmarked the performance of these OL methods against a conventional deep neural network (DNN)-based ROM. Ultimately, we found that OL methods offer comparable performance and, in terms of accuracy and generalizability, even outperform DNN at predicting scalar model responses. The DNN-based ROM afforded the fastest training time. Furthermore, all the ROMs were faster than the original MOOSE model yet still provided accurate predictions. FNO had a smaller mean prediction error than DeepONet, with a larger variance for time-dependent responses. Unlike DNN, both FNO and DeepONet were able to simulate time series data without the need for dimensionality reduction techniques. Finally, the present work can help facilitate the AM optimization process by enabling faster execution of simulation tools while still preserving evaluation accuracy.

36 MATERIALS SCIENCE↗
DOE OSTI2022

User-oriented Improvements in the MOOSE Framework in Support of Multiphysics Simulation

The Multiphysics Object-Oriented Simulation Environment (MOOSE) framework is a foundational capability used by the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program to create over 15 different simulation tools for advanced nuclear reactors. Due to this ubiquity, improvements to the framework in support of modeling and simulation goals are critical to the program. These improvements can take many forms, including optimization, improved user experience, streamlined application programming interfaces (APIs), parallelism, and new capabilities. The work transcribed in this report was conducted in direct support of the simulation tools and has already been deployed or will be deployed in the coming months. The capabilities were implemented in the same order as they are covered in this report: chainable execution objects or executors, support for transfers between same-level applications in a coupling scheme, support for boundary/subdomain restricted transfers, support for transfers between applications with different coordinate or unit systems, support for MOOSE applications in the NEAMS Workbench, deployment of the MOOSE application of the Idaho National Laboratory (INL) high-performance computing (HPC) OnDemand platform, the addition of a triangular meshing library in libMesh, and increased support of face variables.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Modeling framework for multiphysics-multiscale behavior of Si–C composite anode

To achieve the urgent requirement for high energy density in lithium-ion batteries, Si-C composite anode has been spotlighted as one of the most promising alternatives for next-generation batteries. Additionally, a comprehensive computational model is indispensable in the developing process of the excellent performance of anode material due to the low-realizability, inconvenience, and high-cost of experiments. Herein, a simultaneous multiphysics-multiscale model aiming at the Si-C composite anode was developed. This model was then used to study the effects of Si percentage, mechanical constraint and charging rate in terms of electrochemical and mechanical performances. A better design to achieve high capacity was proposed based on the computational results. Results provide a powerful tool in the design, development, and evaluation of high energy density lithium-ion batteries.

25 ENERGY STORAGE↗