Search NASA⌕ Search

SEARCH · Search NASA

Results for “energy modeling tools”

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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Assessment of Process Modeling Tools for Determining Variability in Additively Manufactured Parts

The Advanced Materials and Manufacturing Technologies (AMMT) program aims to accelerate the development, qualification, demonstration, and deployment of advanced materials and manufacturing technologies to enable reliable and economical nuclear energy However, the unique aspects of additive manufacturing (AM) materials in terms of their processing history, microstructure, and properties, are a major barrier for qualification and certification of nuclear components. Much of this challenge may be attributed to component scale variations in microstructure and properties that are driven by local influences of process conditions and geometry on thermal history, melt pool dynamics, and corresponding microstructure evolution. Computational modeling tools may be helpful in this regard to aid in predicting and controlling this level of variability. The purpose of this report is to review the current state-of-the-art for process modeling with regards to metal AM. For this purpose, we consider specifically the case study of laser powder bed fusion (LPBF) processing of SS316, a family of alloys that are both commonly used in nuclear energy applications and suitable for AM processing. The report first introduces the necessary components of a process modeling workflow, followed by a review of the current status of each. At the end, application of these modeling tools to understanding variability in AM process given their current state are considered, and recommendations for future development are proposed

36 MATERIALS SCIENCE↗
DOE OSTI2022

Constraining Physical Understanding of Aerosol Loading, Biogeochemistry, and Snowmelt Hydrology from Hillslope to Watershed Scale in the East River Scientific Focus Area

The mountain snowpack is a critical component of regional hydrology, ecology, biogeochemistry, and climate in the Western US. This project leveraged the East River Scientific Focus Area (SFA), as an outdoor laboratory to address a significant gap in our understanding of the mountain snowpack; namely, how atmospheric constituent deposition on snowpack influences snow energy balance and nutrient/chemical cycling, and how snowmelt timing and intensity exerts controls on emergent biogeochemical and ecohydrologic behavior. This aligned with East River SFA goals to integrate landscape scale measurements and physical based modeling tools to improve understanding of controls on runoff production, ecohydrology, biogeochemical cycling, and land surface energy partitioning in high mountain watersheds. The project included observations of snowpack at multiple scales, measurements of snow and deposited aerosols properties, in situ time series of surface energy balance, and spatially distributed, process-based snowmelt modeling.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1993

The dynamics of hydroponic crops for simulation studies of the CELSS initial reference configurations

During the past several years, the NASA Program in Controlled Ecological Life Support Systems (CELSS) has continued apace with crop research and logistic, technological, and scientific strides. These include the CELSS Test Facility planned for the space station and its prototype Engineering Development Unit, soon to be active at Ames Research Center (as well as the advanced crop growth research chamber at Ames); the large environmental growth chambers and the planned human test bed facility at Johnson Space Center; the NSCORT at Purdue with new candidate crops and diverse research into the CELSS components; the gas exchange data for soy, potatoes, and wheat from Kennedy Space Center (KSC); and the high-precision gas exchange data for wheat from Utah State University (USU). All these developments, taken together, speak to the need for crop modeling as a means to connect the findings of the crop physiologists with the engineers designing the system. A need also exists for crop modeling to analyze and predict the gas exchange data from the various locations to maximize the scientific yield from the experiments. One fruitful approach employs what has been called the 'energy cascade'. Useful as a basis for CELSS crop growth experimental design, the energy cascade as a generic modeling approach for CELSS crops is a featured accomplishment in this report. The energy cascade is a major tool for linking CELSS crop experiments to the system design. The energy cascade presented here can help collaborations between modelers and crop experimenters to develop the most fruitful experiments for pushing the limits of crop productivity. Furthermore, crop models using the energy cascade provide a natural means to compare, feature for feature, the crop growth components between different CELSS experiments, for example, at Utah State University and Kennedy Space Center.

Volk, Tyler↗
DOE OSTI2024

Particle-based high-temperature thermochemical energy storage reactors

Solar and other renewable energy driven gas-solid thermochemical energy storage (TCES) technology is a promising solution for the next generation energy storage systems due to its high operating temperature, efficient energy conversion, ultra-long storage duration, and potential high energy density. Experimental and theoretical studies suggest that the respective gravimetric and volumetric TCES energy storage densities vary from 200 to 3000 kJ kg –1 and 1–3 GJ m –3 . Solar radiation or heat generated from electric furnaces powered by renewable electricity can be stored in the form of chemical energy through endothermic reactions, while the stored chemical energy can be converted to thermal energy via an exothermic reaction when needed. The design of highly effective reactors requires a deep understanding of materials, thermodynamics, chemical kinetics, and transport phenomena. At time of writing, TCES reactors are yet to be deployed at commercially relevant scales, leaving a substantial gap between development efforts and commercial feasibility. Therefore, this review aims to examine the state-of-the-art design and performance of particle-based TCES reactors with different reactive materials. Fundamentals related to TCES reactive materials, reaction conditions, thermodynamics and kinetics, and transport phenomena are reviewed in detail to provide a comprehensive understanding of the reactor design and operation. Five major types of TCES reactors have been comprehensively reviewed and compared, including fixed, moving, rotary, fluidized, and entrained bed reactors. Most reported prototype reactors in the literature operate at lab scale with thermal inputs below 40 kW, and scaled TCES reactors (e.g., at megawatt level) are yet to be demonstrated. The nominal reactor operating temperatures range from 300 to 1500 °C, depending on the selected chemistry, reactive material, and heat sources. To evaluate their designs, the reactors are assessed in aspects of performance, cost, and durability. Discrepancies in performance indicators of energy storage density, extent of reaction, and various energy efficiencies are highlighted. The scale-up of reactors and power block integration, which hold the key to the successful commercialization of TCES systems, are critically analyzed. Furthermore, advanced materials (both reactive materials and ceramic reactor housing materials), effective particle flow control, advanced modeling tools, and novel system design may bring significant improvement to the energy efficiency, storage density and cost competitiveness of particle-based TCES reactors.

25 ENERGY STORAGE↗
DOE OSTI2025

STREAM: A technology planning and capacity expansion model for the industrial sector

The Strategic Technology Roadmapping and Energy, Environmental, and Economic Analysis Model—STREAM—is an optimization-based modeling tool and analysis framework to assist with strategic planning and technology investments of the industrial sector. This open-source framework is written in Julia using the JuMP package, which enables users to model future “pathways” for incumbent and future production technologies, costs, fuels and energy carriers, and energy and non-energy environmental impacts from industries as they transform in pursuit of a robust and competitive manufacturing sector. The model starts with an initial stock of industrial production technologies and assets at a facility level and then determines pathways that minimize cost, subject to an array of possible constraints on demand, market shares, environmental flows, and other exogenously specified operational considerations such as capacity utilization rates or regional energy costs. Key features of the framework include flexibility to model a wide range of industries and industrial technologies/processes at varying levels of granularity, ability to perform parametric sensitivity analyses, and ability to visualize model results using visualization objects.

capacity expansion↗
DOE OSTI2024

Analysis on Evaluations of Monterey Bay Aquarium Research Institute’s Wave Energy Converter’s Field Data Using WEC-Sim and Gazebo: A Simulation Tool Comparison

Although many studies have validated wave energy converter (WEC) numerical models against scaled prototype experimental data, there remains a notable lack of validation using data from full-scale deployed WECs. This paper compares two numerical models of Monterey Bay Aquarium Research Institute’s Wave Energy Converter (MBARI-WEC), a two-body point absorber with an electro-hydraulic power take-off system (PTO). The models are implemented in WEC-Sim/Simscape and Gazebo Simulator. A statistical analysis of the models was performed, and field results were obtained to compare the models’ accuracy in predicting the RMS piston velocity, RMS motor speed, and mean electric power compared to field data for 56 observations across varying sea states. The Gazebo model demonstrated a closer agreement across all three parameters for a majority of the observations. When compared to the field data, the Gazebo and WEC-Sim models exhibited average mean electric power overestimations of 13% and 22%, respectively.

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Demonstration of NEAMS Multiphysics Tools for Fast Reactor Applications

The SHARP toolkit is a high-fidelity reactor simulation tool developed under the U.S. Department of Energy, Office of Nuclear Energy Advanced Modeling and Simulation (NEAMS) Campaign. SHARP toolkit is comprised of the neutronics module PROTEUS thermal hydraulics module Nek5000, and structural mechanics module Diablo. During FY17 and FY18, the PROTEUS and Nek5000 components of SHARP were applied to solve challenging sodium-cooled fast reactor (SFR) problems. In particular, selected hot channel factors (HCF) for a prototype metal-fueled SFR design (the AFR-100) were analyzed in high fidelity, and the “SHARP zooming capability” for SFRs was developed and demonstrated to reduce computational expense for full core problems in cases where detailed data is needed in selected fuel assemblies. After the previous success applying SHARP to challenging SFR problems, the focus in FY19 and FY20 expanded to additional fast reactor applications including lead cooled fast reactors (LFR) and sodium cooled fast reactors (SFR). The specific technical tasks were (1) assessment of hot channel factors for LFR, for which no data currently exists, and (2) demonstration of zooming capability in assemblies of the Versatile Test Reactor (VTR). First-of-a-kind hot channel factor (HCF) estimation for LFR with high fidelity codes (PROTEUS/Nek5000) was successfully demonstrated in this study which began in FY19 and continued in FY20. Selected HCF were computed and compared with SFR data (AFR-100, EBR-II). The findings confirm that different reactor types, design parameters and uncertainties lead to different HCFs. Careful estimation of HCF for a specific design is necessary to obtain appropriate HCFs. In addition to improvement in HCF accuracy, high fidelity tools generate data to help the designer better understand the mechanism of the impact from these uncertainties. For example, the impact of cladding thickness manufacturing tolerance resulted in non-intuitive effects in the corner pins of the LFR assembly. This procedure of computing HCF using high fidelity models shows promise and flexibility for being repeated for any arbitrary reactor of choice. Along with the application on SFR and LFR, the capability of the tools has also been matured to deal with different reactor types and designs. Progress was made towards extending the previously demonstrated SHARP zooming capability to non-fueled SFR assemblies. In particular, in FY19 a gamma transport capability was implemented in both high fidelity PROTEUS solvers in order to accurately account for heat deposition caused by gamma particles, which accounts for ~10% of total core power. Neutronics verification cases were carried out for a candidate Versatile Test Reactor (VTR) design using the new gamma transport capability in PROTEUS. Comparisons were made with continuous energy MCNP calculations and shown to agree well. The models for the full core design with heterogeneous control and fuel assemblies is in progress for PROTEUS-SN and completed with MCNP. The MCNP power distributions were transferred to Nek5000 to perform thermal hydraulic calculations of the control and fuel assembly.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Pathways to a Sustainable Aviation Ecosystem: Aviation Energy Research and Operation Simulator (AEROSim)

The National Renewable Energy Laboratory (NREL) has developed highly accessible tools for ground vehicle modeling, making it easy to quickly compare powertrains and estimate the impact of technology improvements on fuel/energy consumption, performance, cost, and battery life. With AEROSim, NREL advanced aircraft, enabling the same level of ease and versatility in comparing aircraft designs across a range of scenarios and conditions.

advanced air mobility↗
DOE OSTI2023

Computationally Efficient Control Co-Design Optimization Framework with Mixed-Fidelity Fluid and Structure Analysis: OpenTurbineCoDe (OTCD) - ARPA-E ATLANTIS Phase I Project (Final Technical Report)

The goal of the Department of Energy (DOE) Advanced Research Projects Agency-Energy (ARPA-E) Aerodynamic Turbines Lighter and Afloat with Nautical Technologies and Integrated Servo-control (ATLANTIS) Program is to develop new technologies for floating offshore wind turbines, or wind farms, using the discipline of control co-design (CCD.) In this context, our goal is to develop a computationally efficient optimization framework for design of floating offshore wind turbines. Our specific aim is to utilize high-fidelity structural, aerodynamic, aero-structural tools, and to derive control-oriented reduced- or low-order models directly from the high-fidelity tools. We proposed a mixed-fidelity modeling approach which means that we are also using low- and mid-fidelity tools when necessary. This research is conducted by a multidisciplinary team consisting of Rutgers University, University of Michigan, Brigham Young University, and the National Renewable Energy Laboratory (NREL). The computational framework, called OpenTurbineCoDe, is designed to integrate, where possible, traditional structural, aerodynamic, aeroelastic models (e.g., OpenFAST) and advanced control algorithms with higher fidelity simulation tools including Reynolds-averaged Navier–Stokes (RANS) solvers, and three-dimensional structural finite element solvers. All the high-fidelity tools used in this research provide numerically exact gradients to facilitate both efficient optimization and local linearization for control implementation.

17 WIND ENERGY↗
DOE OSTI2022

Stochastic agent-based model for predicting turbine-scale raptor movements during updraft-subsidized directional flights

Rapid expansion of wind energy development across the world has highlighted the need to better understand turbine-caused avian mortality. The risk to golden eagles (Aquila chrysaetos) is of particular concern due to their small population size and conservation status. Golden eagles subsidize their flight in part by soaring in orographic updrafts, which can place them in conflict with wind turbines utilizing the same low-altitude wind resource. Understanding the behavior of soaring raptors in varying atmospheric conditions can therefore be relevant to predicting and mitigating their risk of collision. We present a predictive movement model that simulates individual paths of golden eagles during directional flight (such as migration) that is subsidized by orographic updraft. We modeled eagles in a 50 km by 50 km study area in Wyoming containing three wind power plants with documented golden eagle collisions with turbines. The movement model is applicable to any region where ground elevation is known at turbine scale (50 m) and wind conditions are known at facility scale (3 km). For a given set of atmospheric conditions, the model simulates movements of thousands of orographic soaring eagles to produce a density map quantifying the relative probability of eagle presence. We validated the simulated tracks with GPS telemetry data showing four directional tracks made by golden eagles transiting through the area in 2019 and 2020. For each eagle track, validation was performed using the ratio of the model-simulated eagle presence likelihood with uniform eagle presence and the presence computed using directed random-walk movements. We found that the predictive performance of the model was significantly better (likelihood ratio 1) for low-altitude movements than high-altitude movements that can involve thermal-soaring. We employed the model to produce seasonal presence maps for migrating golden eagles. We found significant turbine-level variations in eagle presence between northerly and southerly migration routes through the study area. Overall, the proposed model offers a generalizable, probabilistic, and predictive tool to assist wind energy developers, ecologists, wildlife managers, and industry consultants in estimating the potential for conflict between soaring birds and wind turbines, thereby reducing the need for site-specific data on golden eagle movements.

17 WIND ENERGY↗
NASA NTRS2009

Spinoff 2009

Topics covered include: Image-Capture Devices Extend Medicine's Reach; Medical Devices Assess, Treat Balance Disorders; NASA Bioreactors Advance Disease Treatments; Robotics Algorithms Provide Nutritional Guidelines; "Anti-Gravity" Treadmills Speed Rehabilitation; Crew Management Processes Revitalize Patient Care; Hubble Systems Optimize Hospital Schedules; Web-based Programs Assess Cognitive Fitness; Electrolyte Concentrates Treat Dehydration; Tools Lighten Designs, Maintain Structural Integrity; Insulating Foams Save Money, Increase Safety; Polyimide Resins Resist Extreme Temperatures; Sensors Locate Radio Interference; Surface Operations Systems Improve Airport Efficiency; Nontoxic Resins Advance Aerospace Manufacturing; Sensors Provide Early Warning of Biological Threats; Robot Saves Soldier's Lives Overseas (MarcBot); Apollo-Era Life Raft Saves Hundreds of Sailors; Circuits Enhance Scientific Instruments and Safety Devices; Tough Textiles Protect Payloads and Public Safety Officers; Forecasting Tools Point to Fishing Hotspots; Air Purifiers Eliminate Pathogens, Preserve Food; Fabrics Protect Sensitive Skin from UV Rays; Phase Change Fabrics Control Temperature; Tiny Devices Project Sharp, Colorful Images; Star-Mapping Tools Enable Tracking of Endangered Animals; Nanofiber Filters Eliminate Contaminants; Modeling Innovations Advance Wind Energy Industry; Thermal Insulation Strips Conserve Energy; Satellite Respondent Buoys Identify Ocean Debris; Mobile Instruments Measure Atmospheric Pollutants; Cloud Imagers Offer New Details on Earth's Health; Antennas Lower Cost of Satellite Access; Feature Detection Systems Enhance Satellite Imagery; Chlorophyll Meters Aid Plant Nutrient Management; Telemetry Boards Interpret Rocket, Airplane Engine Data; Programs Automate Complex Operations Monitoring; Software Tools Streamline Project Management; Modeling Languages Refine Vehicle Design; Radio Relays Improve Wireless Products; Advanced Sensors Boost Optical Communication, Imaging; Tensile Fabrics Enhance Architecture Around the World; Robust Light Filters Support Powerful Imaging Devices; Thermoelectric Devices Cool, Power Electronics; Innovative Tools Advance Revolutionary Weld Technique; Methods Reduce Cost, Enhance Quality of Nanotubes; Gauging Systems Monitor Cryogenic Liquids; Voltage Sensors Monitor Harmful Static; and Compact Instruments Measure Heat Potential.

Source record↗
NASA NTRS1996

Design of a Mode Conversion Ultrasonic Motor for Position Control

The many useful characteristics of ultrasonic motors, such as high holding torques, and high torque at low speeds, have made them the subject of increasing interest. In addition, several of their characteristics make them attractive for aerospace applications: they have a torque to weight ratio, and they require neither gearing mechanisms nor lubrication. Moreover, they create negligible magnetic fields, and conversely, they are not affected by external magnetic fields. Ultrasonic motors based on bolt-tightened structures offer simplicity and high stress capability. They use the inverse piezoelectric effect in the stator to produce vibrational energy, which is transferred to the rotor by friction. We designed a bolt-tightened ultrasonic motor using numerical modelling tools (finite element and electromechanical circuit analyses), creating an equivalent circuit model that takes into account the electromechanical energy conversion in the stator and the contact between the stator and the rotor. Analysis of the circuit gives insight into the behavior of the motor and allows its performance to be calculated. Two prototypes of the motor were built; their transient responses and other quantities, such as starting torque, were measured. In this paper, we discuss the numerical and the experimental results, and demonstrate the usefulness of numerical analysis in designing ultrasonic motors and estimating their performance.

LeLetty, Ronan↗
DOE OSTI2022

Framework For Optimization Of Resources And Economics Ecosystem

The Framework for Optimization of ResourCes and Economics is a collection of software tools, models, and datasets acquired and developed under the Integrated Energy Systems (IES) program to enable analysis of technical and economic viability of myriad IES configurations. FORCE is the consolidating interface and data repository for all the IES toolsets ranging from macro technoeconomic analysis to transient process modeling and experimental validation for integrated energy systems.

Frick, KonorL↗
DOE OSTI2020

ORBIT: Offshore Renewables Balance-of-System and Installation Tool

This report describes the Offshore Renewables Balance-of-system Installation Tool ("ORBIT"), a new model developed by the National Renewable Energy Laboratory (NREL) to evaluate the balance-of-system (BOS) costs associated with offshore wind projects. In the context of wind energy projects BOS costs encompass all expenses required to construct a project other than the capital expenditures (CapEx) of the turbines and towers, including the procurement costs for all other components (such as substructures, cables, and electrical infrastructure), offshore and land-based construction costs, port costs, site surveying fees, permitting fees, and leasing fees are all categorized as BOS costs. BOS costs significantly contribute to the levelized cost of energy (LCOE) for offshore wind, typically comprising over 50\% of the CapEx for a fixed-bottom offshore wind project and 60\% for a floating project. In addition, technology solutions and installation methods vary drastically between projects as they are impacted by factors such as vessel availability, geographic considerations and site geotechnical conditions. These effects require a model with appropriate fidelity to understand how these costs scale as turbine rating increases and the offshore wind supply chain, particularly offshore construction vessels, is expanded. For offshore wind, cost savings attributed to increased turbine rating are primarily realized through BOS procurement and project installation as fewer substructures and less cable are required. BOS costs represent both a modeling challenge, as well as an opportunity, for project developers to optimize solutions to reduce costs. It is critical to understand how these costs are affected by novel technologies, innovative installation processes, and operational constraints in order identify meaningful cost reductions for offshore wind energy.

17 WIND ENERGY↗
DOE OSTI2023

INL Report: Multiphysics Modeling and Simulation of Deimos, an Advanced Reactor Experiment

When designing a novel reactor, nuclear experiments are essential to validate the predictive capability of modeling/simulation tools and to justify the investment of a full-scale prototype. Being able to accurately predict temperature reactivity coefficients is of high importance to reactor designers as it impacts the safety and performance of the system. Deimos is a proposed graphite-moderated, beryllium-reflected, high assay low-enriched uranium (HALEU) tri-structural isotropic (TRISO) fueled experiment for NCERC. Deimos is a valuable experiment for validating the predictive performance of modeling and simulation tools since it comprises a relatively thermal energy spectrum with 84% thermal neutrons causing fission, 15% epithermal neutrons causing fission, and 1% fast neutrons causing fission. Additionally, by electrically heating the experiment, reactivity can be validated at various temperatures. Deimos will serve as a testbed for future advanced reactor concepts.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Physics-based modeling and information-theoretic sensor and settings selection for tool wear detection in precision machining

Precision machining of metals is an energy intensive process with applications and impacts across the manufacturing industry. The energy efficiency, product yield, and maintenance of the precision machine require a digital twin that can assist with prognostics and health management. In this report a physics-based model is developed and validated against face milling data, and then used for the timely and precise inference of machining faults that cannot be measured directly. Computer numerical control (CNC) measurements of power and force are used through this physics-based machining model to predict deviations of the outputs of power consumption and cutting forces during normal operation. A model-based fault detection and isolation methodology is applied to determine the optimal (traditional and available) sensor suite and the test settings (admissible input values) that improve the inference of tool wear in face milling. The optimal sensor suite and input test settings are obtained by solving a mixed integer non-linear program that optimizes information-theoretic metrics relevant to the detection and isolation of tool wear from steady-state or transient machining measurements. Dynamic time warping and k—NN classification are then used to validate the robustness of the optimal design for fault detection test design, including the optimal sensor suite.

42 ENGINEERING↗
NASA NTRS1981

An optimization model for energy generation and distribution in a dynamic facility

An analytical model is described using linear programming for the optimum generation and distribution of energy demands among competing energy resources and different economic criteria. The model, which will be used as a general engineering tool in the analysis of the Deep Space Network ground facility, considers several essential decisions for better design and operation. The decisions sought for the particular energy application include: the optimum time to build an assembly of elements, inclusion of a storage medium of some type, and the size or capacity of the elements that will minimize the total life-cycle cost over a given number of years. The model, which is structured in multiple time divisions, employ the decomposition principle for large-size matrices, the branch-and-bound method in mixed-integer programming, and the revised simplex technique for efficient and economic computer use.

Lansing, F. L.↗
DOE OSTI2024

High-Fidelity Multiphysics Modeling of a Heat Pipe Microreactor Using BlueCrab

Researchers who are actively developing nuclear microreactors are planning to employ innovative designs and features using traditional commercial modeling tools that may be inadequate for their design and licensing activities. The codes developed under the U.S. Department of Energy Office of Nuclear Energy Advanced Modeling and Simulation (NEAMS) program provide flexibility in terms of geometry modeling and multiphysics coupling and are particularly well suited for modeling novel microreactor concepts. To test the maturity of these codes, this paper introduces a conceptual heat pipe microreactor (HP-MR) designed to gather various technologies of interest to microreactor developers such as control drums, heat pipes, and hydride moderators. Here, the objective of this effort is to demonstrate NEAMS tools capability to perform high-fidelity multiphysics simulations, using coupled neutronics (via the Griffin code), heat conduction (via the BISON code), heat pipe modeling (via the Sockeye code), and hydrogen redistribution in hydride metal moderator (via the SWIFT code). Codes are coupled in-memory through the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework, which permits flexible multiphysics data transfer schemes. The analysis confirmed two key aspects of the HP-MR concept: (1) its ability to follow the power load requested from the heat pipe and (2) its ability to avoid heat pipe cascading failure unless designed with high power close to operating failure limits of its heat pipes. The developed computational model was distributed publicly on the Virtual Test Bed for training purposes to accelerate adoption by industry and to provide a high-fidelity multiphysics solution for benchmarking against other tools. Additional multiphysics analyses including other transients and coupled physics were identified as necessary future work, together with a focus on validating multiphysics behavior against experiments.

Microreactor↗