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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

HTGR Multiphysics Application Drivers FY26 Updates

This report summarizes FY26 progress under the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program's high-temperature gas-cooled reactor (HTGR) application driver work, covering a wide range of activities such as code validation and multi-physics code assessment. 1) A detailed SAM model of the High-Temperature Engineering Test Reactor (HTTR) was developed using a unique-block grouping approach, with an extended parallel thermal network method to capture block-to-block conduction and radiation heat transfer, and applied to steady-state simulations of the HTTR 30~MW and 9~MW cases. 2) In another activity, SAM's newly implemented multi-component gas flow model was validated against the Natural convection Shutdown heat removal Test Facility (NSTF) argon ingress experiment, correctly capturing the density-driven suppression and thermal recovery of natural circulation observed when argon is introduced into the air-cooled Reactor Cavity Cooling System (RCCS) loop. 3) For the OECD/NEA High Temperature Test Facility (HTTF) benchmark, we co-led the international benchmark activities as well as the OECD/NEA final benchmark report to be released at the end of this year. 4) Finally, the coupled Griffin-SAM modeling capability for pebble-bed HTGRs was advanced by verifying the Griffin neutronics solution against Serpent Monte Carlo for a realistic non-uniform temperature distribution, resolving several deficiencies in the SAM-to-Griffin temperature transfer scheme, and enabling distinct fuel kernel, moderator, and coolant temperatures for cross section feedback. These new features were demonstrated in a PBR load-following transient.

Lee, Alvin↗
DOE OSTI2024

Mechanistic definition and prediction of the mass exchange coefficient between rivers and hyporheic zones: The $α$ of two $Ω$s

Solute transport in interconnected rivers and hyporheic zones is typically modeled through dual-domain models where first-order solute mass transfer between the two domains, Ω R and Ω HZ , is represented by a coefficient α. The transient storage model (TSM) is an example of such an approach. In practice, α is determined by fitting the tails of solute tracer breakthrough curves using a TSM. This approach has led to ambiguity regarding α’s physical meaning and transferability. Here, in this work, we investigated the physical basis for α and tested it with virtual experiments through the fully coupled multiphysics model hyporheicFoam for the Ω R – Ω HZ system. hyporheicFoam explicitly simulated coupled flow and solute transport over a kilometer with centimeter-scale resolution. Model results were analyzed to calculate α following its theoretical definition directly. Using the determined α within a TSM enables accurate reproduction of solute transport, underscoring α’s physical relevance and precision.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A stable potential-based time-domain method for wideband elec- tromagnetic analysis

In previous research, the frequency-domain A-ϕ formulation has been validated using the finite element method for electromagnetic simulations of low-frequency and multi- scale problems, demonstrating excellent numerical accuracy, good matrix condition, and high computational efficiency. Time- domain simulations provide significant advantages for modeling wideband problems and are crucial for multiphysics applications. In this paper, the frequency-domain A-ϕ formulation is extended to the time domain. The central difference scheme is employed for temporal discretization to ensure both accuracy and stability. A numerical example is presented to demonstrate the capability of the proposed time-domain method in wideband electromagnetic analysis.

Mekonnen, Minyichil↗
NASA NTRS2015

Simulation Apps Bring Us Closer to Mars

My work with mathematical modeling and computer simulations began in earnest in 1987 when I signed on with the National Aeronautics and Space Administration, better known as NASA. At the time I was developing computer simulations to support the design of carbon dioxide (CO2) removal systems for the International Space Station (ISS) life support system. CO2 is a human metabolic waste, produced at a rate of a kilogram per day per crewmember. CO2 must be removed from the crew cabin, as it will quickly become detrimental to crew health. The systems used to remove CO2 are typically based on sorption processes, which include complex interactions of heat transfer, mass transfer, and gas flow through porous media. At this time, there were no commercial options for solving a set of coupled mathematical models such as partial differential equations (PDEs); you either force-fit the physics into a thermal analysis package or wrote your own code, complete with discretization, meshing, and solution algorithms. Unfortunately, coding CO2 removal processes from scratch did not allow an appropriate focus on the challenging yet crucial task of understanding and capturing the underlying physics via appropriate mathematical models. Configuration control was often simply ignored due to tight schedules, resulting in a code that would be quicker for a second party to rewrite than modify. In the early 2000s, I decided to move CO2 removal simulations to a platform with built-in meshing, solvers, and postprocessing capabilities, and that could solve user-defined multiphysics PDEs. The program chosen to meet these needs was COMSOL Multiphysics®. Along with freeing the engineer to focus on the underlying physics, a degree of configuration control was automatically achieved via a consistent user interface, thus allowing COMSOL users to share computer models. My team has developed simulations that are already providing a valuable debugging capability for the ISS CO2 removal system, and will provide guidance in upgrades to that system.

Knox, Jim↗
DOE OSTI2026

Mesh-based multiphysics coupling acceleration for fusion neutronics through clustering for fusion blanket applications

Accurate modeling of particle transport within fusion blankets is essential for predicting performance metrics such as heat deposition and the tritium breeding ratio (TBR). However, high-fidelity coupling of thermal fluids from computational fluid dynamics (CFD) to neutronics simulations often incurs significant computational costs due to the complexity of surface intersection calculations in Monte Carlo codes. This paper presents an accelerated multiphysics coupling method for neutronics that utilizes hierarchical agglomerative clustering to map complex material property distributions to a neutronics model. Implemented within the fusion reactor design and assessment (FREDA) framework, the method leverages existing Python packages to automate the creation of clustered geometries for OpenMC. The approach is demonstrated on a sector model of an ARC-class tokamak with an immersion molten salt blanket, and an simple geometry with varying isotopic concentrations. Results show that the clustering method significantly reduces computational burden without compromising fidelity, providing a foundation for agile iteration of neutronics simulations involving multiple coupled material properties.

Bae, Jin Whan [ORNL] (ORCID:0000000326548907)↗
DOE OSTI2026

Computational modeling of graphite degradation in molten salt reactors: Role of infiltration

Molten salt reactors (MSRs) often employ graphite as a moderator and reflector. An important challenge for deploying graphite in these reactors is that, due to limited experimental data, our understanding of graphite’s structural integrity in molten salt environments remains incomplete. Here, this study addresses heat generation from fuel-bearing salt that has infiltrated open pores in the graphite, driven primarily by pressure differentials. This is one of multiple identified physical and chemical mechanisms through which molten salt could potentially degrade graphite. Thermally driven stresses are quantified using the Molten-Salt Reactor Experiment (MSRE) graphite moderator elements as a case study. Finite element simulations predict stress distributions at varying infiltration levels, indicating that thermal stresses increase with higher infiltration. Rare-event simulations using the parallel subset simulation framework identify the combinations and corresponding ranges of input parameters that lead to stresses above a specified threshold. In particular, combinations involving high infiltration amounts, high power density, and low thermal conductivity tend to induce the highest stresses. Under the inputs and assumptions considered in this work, the magnitudes of the thermally driven stresses are quite low, with a very low likelihood of causing failure due to exceeding the graphite’s tensile strength. Additionally, rare-event simulations were performed for two more scenarios: a scaled-up moderator geometry and a localized hotspot in the original geometry. Both cases resulted in increased susceptibility to failure, though not to a detrimental extent. Furthermore, the combined effects of irradiation and infiltration-induced thermal stresses were evaluated. The results showed that thermal stresses from infiltration were negligible compared to those caused by irradiation. The findings of such a study are inherently component-specific, but the methodology presented here could be used for similar assessments of salt-infiltration effects in other graphite components.

36 - MATERIALS SCIENCE↗
DOE OSTI2024

Fourier-MIONet: Fourier-enhanced multiple-input neural operators for multiphase modeling of geological carbon sequestration

Geologic carbon sequestration (GCS) is a safety-critical technology that aims to reduce the amount of carbon dioxide in the atmosphere, which also places high demands on reliability. Multiphase flow in porous media is essential to understand CO 2 migration and pressure fields in the subsurface associated with GCS. However, numerical simulation for such problems in 4D is computationally challenging and expensive, due to the multiphysics and multiscale nature of the highly nonlinear governing partial differential equations (PDEs). It prevents us from considering multiple subsurface scenarios and conducting real-time optimization. Here, we develop a Fourier-enhanced multiple-input neural operator (Fourier-MIONet) to learn the solution operator of the problem of multiphase flow in porous media. Fourier-MIONet utilizes the recently developed framework of the multiple-input deep neural operators (MIONet) and incorporates the Fourier neural operator (FNO) in the network architecture. Once Fourier-MIONet is trained, it can predict the evolution of saturation and pressure of the multiphase flow under various reservoir conditions, such as permeability and porosity heterogeneity, anisotropy, injection configurations, and multiphase flow properties. Compared to the enhanced FNO (U-FNO), the proposed Fourier-MIONet has 90% fewer unknown parameters, and it can be trained in significantly less time (about 3.5 times faster) with much lower CPU memory (<15%) and GPU memory (<35%) requirements, to achieve similar prediction accuracy. In addition to the lower computational cost, Fourier-MIONet can be trained with only 6 snapshots of time to predict the PDE solutions for 30 years. Furthermore, we observed that Fourier-MIONet can maintain good accuracy when predicting out-of-distribution (OOD) data. The excellent generalizability of Fourier-MIONet is enabled by its adherence to the physical principle that the solution to a PDE is continuous over time. Furthermore, the developed Fourier-MIONet makes it possible to solve the long-time evolution of geological carbon sequestration in a large-scale three-dimensional space accurately and efficiently.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Multiphysics Co-Optimization Design and Analysis of Double-Side Cooled Silicon Carbide-Based Power Module: Preprint

With the rapid growth of Electric Vehicles (EVs) and Hybrid Electric Vehicles (HEVs), much more rigorous design targets have been set for automotive power electronics, including high power density, high reliability, and low cost. Novel power module and inverter technologies based on wide bandgap (WEG) semiconductors have been developed to meet these design targets, while providing optimal power semiconductor operating temperature and promising thermomechanical performance. Compared with conventional cooling techniques which are normally applied only on one side of power module, double-side cooling approach is now believed to be the solution to enable high power density and low thermal resistance of WEG semiconductor-based power electronics. In this work, we develop a three-phase power module that is double-sided cooled using dielectric fluid jet impingement. In each phase, four silicon carbide (SiC) power semiconductors are bonded to copper busbars without electrical insulation layers. A finite element analysis (FEA) model is created for thermal and thermomechanical analysis. Based on FEA modeling results, we select particular dimensions for a parametric study to optimize thermal and mechanical performance. Using a multi-objective genetic algorithm (MOGA)-based optimization method, we have minimized the maximum junction temperature and thermal stresses within the power module. The multiphysics co-optimization approach has enabled an efficient design process of power modules with greatly reduced computational cost, as compared to conventional processes that rely on exhaustive numerical simulations and iterations.

ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2017

Virtual Design of a 4-Bed Molecular Sieve for Exploration

Simulations of six new 4-Bed Molecular Sieve configurations have been performed using a COMSOL (COMSOL Multiphysics - commercial software) model. The preliminary results show that reductions in desiccant bed size and sorbent bed size when compared to the International Space Station configuration are feasible while still yielding a process that handles at least 4.0 kilograms a day CO2. The results also show that changes to the CO2 sorbent are likewise feasible. Decreasing the bed sizes was found to have very little negative effect on the adsorption process; breakthrough of CO2 in the sorbent bed was observed for two of the configurations, but a small degree of CO2 breakthrough is acceptable, and water breakthrough in the desiccant beds was not observed. Both configurations for which CO2 breakthrough was observed still yield relatively high CO2 efficiency, and future investigations will focus on bed size in order to find the optimum configuration.

Giesy, Timothy J.↗
DOE OSTI2024

BISON Simulated and Experimental Fission Product Release Comparisons from Reradiated AGR-3/4 Compacts During High Temperature Heating Tests

The fuel performance modeling code BISON was used to predict the release of fission products iodine-131 (131I), xenon-133 (133Xe), and krypton-85 (85Kr) from four re-irradiated AGR-3/4 fuel compacts containing tristructural isotropic (TRISO) coated particles during high-temperature isothermal heating tests. The AGR-3/4 fuel compacts were irradiated in the Advanced Test Reactor (ATR) as part of the third and fourth series of planned experiments to support the Advanced Gas Reactor (AGR) Program. They were subsequently stored and re-irradiated in the Neutron Radiography (NRAD) reactor for approximately five days and then stored for another five to eight days before being subjected to isothermal heating tests in the Fuel Accident Condition Simulation (FACS furnace) for 200 to 300 hours at temperatures between 1000°C and 1600°C to evaluate fission product release at elevated temperatures. New nuclide-specific fission product source term models for the three nuclides of interest were developed using the reactor multiphysics code Griffin and implemented into BISON to support this work. The new source term models were incorporated into coupled compact- and particle-scale BISON simulations, which predict spatially- and temporally-resolved radionuclide generation, radioactive decay, transport, and release throughout the entire irradiation history, including the initial ATR irradiation, NRAD re-irradiations, FACS heating tests, and intermediate periods spent in storage. The experimentally measured fission product release from the heating tests were compared to modeling release predictions calculated by BISON to evaluate how well the code compares to experimental results. Overall, the experimental measured and BISON predicted comparative release results varied but generally agreed to within 5 particle equivalents. Comparative release results identified general observations to take into consideration to help refine future models and reduce uncertainties associated with both the measurement results and predictive results. This includes developing new uranium oxycarbide (UCO) specific kernel diffusivities for the three isotopes examined to more accurately reflect the material properties of the fuel form. Deriving new diffusivities will aid in producing a more informed BISON model

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Aeroelastic Modelling of Large Wind Turbines: Towards a Unified OpenFAST-SEAHOWL Approach

In recent years, the scale of wind turbines has significantly increased to maximize energy capture for a given site (particularly offshore), presenting new challenges in terms of structural design and dynamics. As towers grow taller and blades grow longer, flexion and torsion of the latter have a non-negligible impact on the behavior and performance of the turbine in terms of overall loads, power production, and control. When representing large-scale wind turbines numerically to capture these important effects, particular attention must therefore be given to the level of fidelity for representing each structural component, as well as the coupling scheme used between them to keep simulations accurate, stable, and efficient. To address this issue, we combine here the two following tools: (1) OpenFAST, the reference whole-turbine simulation tool from NREL with standalone modules covering each physics and the choice between loose coupling and a new tight coupling scheme for structural dynamics, and (2) SEAHOWL, the whole-turbine simulation tool from TotalEnergies with monolithic coupling of structural dynamics through Project Chrono and partitioned coupling for multiphysics interactions.

17 WIND ENERGY↗
DOE OSTI2026

Development and Application of High-Fidelity Models for Heterogeneous CO2 Frost Formation

Carbon America has developed a cryogenic carbon capture technology ("FrostCC") that separates CO2 from point source emissions by solidifying it at cold temperatures through preferential desublimation. Cooling is achieved through a series of interlinked compression, heat exchange, and expansion operations. In the current system, frosting of CO2 happens in heat exchangers, followed by CO2 recovery in a separate extraction step. In this work, multiphysics computational fluid dynamics (CFD) models are developed and validated for compressible and low Mach flows to simulate the formation of solid CO2 in flue gas flowing in a heat exchanger geometry. The models track the mass transfer rate of CO2 from gas phase to solid phase, heat released from desublimation, and the evolution of the solid CO2 layer. Simulations are used to answer scientific questions related to the angle of heat exchanger pipes, where buoyancy effects from flow velocity and pipe orientation influence CO2 frosting. Results show that upwardly angled pipes produce notably different flow structures compared to horizontal or vertical configurations, and that carbon capture efficiency correlates with buoyancy effects for pipe angles within plus or minus 23 degrees of horizontal.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Species Transport Framework Development in SAM for System-Level Tritium Source Term Analysis

The SAM code is under development as a modern system-level modeling and simulation tool for advanced non–light water reactor safety analyses, with recent efforts to add capabilities to evaluate radiological source term risks in these novel reactor concepts. By leveraging the established system-level multiphysics thermal-hydraulic models in SAM, a framework for tightly coupled species transport modeling has been integrated into the code for engineering-scale source term evaluation. This species transport framework was first applied to the simulation of tritium, which is a well-known source term in conventional light water reactors. Tritium poses a unique risk in salt-cooled reactors, especially those with lithium-bearing salts such as the fluoride salt–cooled high-temperature reactor (FHR) concept, as tritium is generated in the salt coolant in significant quantities due to neutron interactions. A compounding factor is the increased mobility of tritium at high temperatures, which is able to permeate through metals while also potentially being retained in graphite pebbles and structures. Engineering-scale models for the tritium transport pathways in a FHR have been developed using the new species transport framework in SAM. The capabilities are assessed through analytical verification problems and validated with data from a graphite retention experiment. In conclusion, the system-level model is demonstrated by performing an initial estimate of baseline tritium generation and flows in a generic reference SAM FHR model, setting a foundation for future studies of source term transient analysis with the potential for further multiscale and multiphysics integration.

SAM↗
DOE OSTI2025

Modelling the brittle failure of graphite induced by the controlled impact of runaway electrons in DIII-D

The thermo-mechanical response of an ATJ graphite sample to controlled runaway electron (RE) dissipation, realized in DIII-D, is modelled with a novel work-flow that features the RE orbit code KORC, the Monte Carlo particle transport code Geant4 and the finite element multiphysics software COMSOL. KORC provides the RE striking positions and momenta, Geant4 calculates the volumetric energy deposition and COMSOL simulates the thermoelastic response. Brittle failure is predicted according to the maximum normal stress criterion, which is suitable for ATJ graphite owing to its linear elastic behavior up to fracture and its isotropic mechanical properties. Measurements of the conducted energy, damage topology, explosion timing and blown-off material volume, impose a number of empirical constraints that suffice to distinguish between different RE impact scenarios and to identify RE parameters which provide the best match to the observations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

WHA Sphere Impacting RHA Plate: Modeling Brittle Behavior in Metal Alloys

Brittle behavior of metal alloys is often critical to modeling ballistic impact and penetration. The ALEGRA multiphysics finite element software incorporates calibrated models for the equation of state, elasticity, yield stress, plasticity and fracture, but simulations do not always capture expected metal fracture. Here we report concerted efforts to do so for one important case where experiments clearly show shear fractures: a tungsten sphere impacting a steel plate at various angles. Our best simulations show fractures that are qualitatively similar to experiments, but there are significant differences in quantitative metrics. Specifically, velocities of tracers used to quantify simulated plug parameters consistently fall short of measured plug velocities. Also, simulated plugs break apart more than expected from experimental evidence. We attribute these shortfalls to the lack of an explicit shear fracture mechanism in the material models, leading to over-estimated resistance to plug formation and movement.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Optimization of direct air capture processes using reactive transport models of adsorption-desorption cycles

In this study, we develop and implement a reactive transport model in COMSOL Multiphysics® to address the challenges of direct air carbon capture. The model is validated against experimental data and used to simulate the cyclic steady state of the adsorption-desorption process. The optimization of this model is achieved through advanced trust-region methods integrated with Gaussian Processes. Key decision variables, including adsorption and desorption times, desorption temperature and pressure, input velocity, bed porosity, column length, and radius were optimized to minimize the capture cost. After optimization, a sensitivity analysis revealed the complex interplay between the decision variables and their effect on the specific energy and cost of removing the CO 2 . We optimized the capture cost while taking into account the trade-off between energy consumption and productivity. The resulting minimum capture cost was determined to be 265.2 $/t-CO 2 , which aligns with expected values reported in the literature. Numerical results suggest the effectiveness of the optimization strategies applied, and underscore the importance of simultaneous decision variable selection in improving the performance in direct air capture processes. We also extend the modeling approach to a 2D axisymmetric model to better visualize CO₂ uptake and temperature profiles, revealing significant radial gradients during the regeneration step. As a main drawback, this enhanced model comes with a computational cost approximately 40 times higher than that of the 1D model.

Adsorption-desorption process↗
DOE OSTI2025

Design Optimization of a Criticality Experiment for the Molten Chloride Reactor Experiment Facility

Neutronics simulations of Molten Chloride Fast Reactors have quantifiable biases that arise from nuclear data, modeling choices, or numerical methods. The multiphysics nature of molten salt reactors makes it challenging to disentangle neutronics modeling biases from biases originating from other physical phenomena. In comparison to a mock-up reactor, criticality experiments can specifically assess the neutronics modeling bias while limiting multiphysics effects. The criticality experiment must be neutronically representative of the full-scale reactor to be valuable. Here, in this paper, we describe the design of a criticality experiment to validate only the neutronics of TerraPower’s Molten Chloride Reactor Experiment (MCRE) and its criticality safety upset scenarios. The proposed experiment uses different chlorine-containing materials to maximize its similarity to the MCRE. The design process uses a constrained Bayesian optimization algorithm to investigate different objective functions that use covariance information for 35 Cl nuclear data. The experiments could reduce the nuclear data–induced uncertainty in k eff of the MCRE from 2161 to 886 pcm. They would also increase the upper subcritical limit of the MCRE criticality safety upset scenario from 0.94101 to 0.94476 when using the WHISPER analysis framework.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗