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DOE OSTI2025

Modeling and Simulation of Fuel Dispersal During the Loss-of-Coolant Accident

This document is the compilation of the milestone portion to a larger end of project NEUP report. The executive summary of the modeling portion is provided below: In the event of cladding rupture during a postulated LOCA in a pressurized water reactor, fuel particles, along with fission gases, can be expelled into the reactor core from the fractured fuel rod, a phenomenon referred to as fuel dispersal. The initial stage of fuel dispersal is strongly influenced by the high-pressure ejection of fuel fragments, the size and geometry of the ruptured cladding, and the depressurization history of the fuel rod during the postulated LOCA transient. Depending on the location of the burst orifice relative to the quench front, the dispersal event represents an intricate three-phase flow and heat transfer phenomenon, where high-temperature fuel particles carried by the fission gases interact with the coolant within the narrow subchannels of the fuel assemblies, inducing localized phase change. Given the unique multiphysics nature of this phenomena, the current study develops a dedicated computational framework to predict the mass distribution and cooling of dispersing fuel particles, facilitating post-accident assessment and management of the fuel assemblies. Considering the scale of nuclear reactor applications, a continuum three-fluid model is proposed for simulating the transport of solids within the reactor core. With high-temperature fuel fragments within the liquid media, nucleation sites inducing phase changes are dispersed within the flow domain. Coupled with the fact that the transient dispersal event occurs on different time scales than other three-phase flow applications, this study derives a time-averaged three-fluid flow model without losing generality. The assumptions regarding the continuum treatment of the solid phase and the modeling of fuel dispersal behavior are incorporated to simplify the governing equations and derive applicable closure relations. The computational validation of the model was conducted using adiabatic experimental results obtained from ongoing research at Oregon State University, focusing on characterizing fuel dispersal behavior during simulated LOCA conditions. Settlement characteristics of the solids, quantified by the probability distribution of equivalent particles, closely matched the probability density functions reported in experimental studies. The transport of fuel particles within a scaled 5 × 5 lattice of a pressurized-water reactor rod bundle geometry was modeled through a two-fluid Eulerian framework. The required boundary conditions were evaluated from the fuel performance code BISON in a postulated large-break LOCA scenario. The modeling framework considered solid fuel particles as granular matter, interacting with the gaseous dry steam phase and fission gases through the governing interfacial momentum exchange between the participating fluids. The simulation results provided the volume fraction of the solids obtained at the bottom surface of the enclosing tank geometry. Postulated LOCA leading to fuel dispersal phenomena involves the strong coupling between fuel thermomechanics, cladding deformation, thermal-hydraulics, and fuel particle transport. Incorporation of such a strong coupling in numerical simulation is performed by coupling the multiphysics solvers. In the case of fuel dispersal, a strong coupled simulation can be performed by coupling the BISON code for fuel performance, the TRACE code for system-level thermal hydraulics, and fuel particle transport in Multiphysics Object-Oriented Simulation Environment (MOOSE). For such intricate infrastructure, the MOOSE Framework eases the data transfer between codes. The recent version of MOOSE has incorporated the Navier-Stokes module for the fluid flow. An exploratory exercise was done to gain familiarity with finite volume capabilities in the MOOSE framework to incorporate the Spalart-Allmaras (SA) turbulence model. New finite-volume and auxiliary kernels were introduced to assemble the SA transport equation, compute turbulent viscosity, and evaluate wall distance and diagnostic turbulence terms, fully integrated with existing Navier-Stokes modules. A turbulent lid-driven cavity at a Reynolds number of approximately 10,000 is used for verification. MOOSE shows the robust solver convergence and produces the turbulent features. But it underpredicts the velocity profile and turbulent quantities, emphasizing the need to develop improved SA near-wall treatments (e.g., low-Re corrections or wall functions) as a key direction for future work.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

NEML2: An efficient and modular multiphysics constitutive modeling library for hybrid computing environments

This paper presents NEML2, an open-source, high-performance library developed for constitutive material modeling, designed to support the flexible and modular development of models for complex material behavior. Building on the foundational structure of its predecessor, NEML, the NEML2 library introduces significant improvements, including enhanced vectorization, automatic differentiation, and seamless integration with PyTorch, facilitating the application of machine learning techniques in material simulations. NEML2 provides a C++ backend with Python bindings, enabling users to create custom material models that can be executed efficiently on both CPU and GPU platforms. The library also supports coupling with Multiphysics simulation frameworks like MOOSE, making it suitable for realistic simulations involving coupled physical processes. Rigorous quality assurance through unit and regression testing ensures the reliability of results, while the extensible, user-friendly design encourages collaboration and reproducibility across the scientific community. This paper provides an overview of NEML2’s architecture, core features, and applications, highlighting its impact on accelerating material qualification and advancing computational methods in materials science.

GPU↗

NASA NTRSDate not supplied

Coupled Reactor and Engine Nuclear Thermal Propulsion Modeling Methodology

The design and development process of a Nuclear Thermal Propulsion (NTP) system requires extensive multiphysics modeling to couple the neutron physics and thermal feedback effects to determine the reactor’s power shape. Propulsion system performance codes utilize this power shape to determine NTP key performance parameters. While the power shape is heavily dependent on the temperature profile and geometry of the reactor, many analyses either assume a constant power shape, or use neutronics analysis to determine a power shape for a specific reactor configuration. The development of a coupling interface for a propulsion system performance code and a Monte Carlo neutron transport code (OpenMC) allows for the reactor power shape to be calculated in an iteration loop. The interface utilizes a file share system to transfer geometry dimensions, temperatures, and material identifiers to OpenMC, which is used to perform a neutron transport simulation of a design like the government Testing Reference Design reactor. The interface is then able to post-process the results from OpenMC and use the same file share system to share a power shape and other important neutron transport parameters to the system performance code. Initial results show that neglecting the changes to power shape when comparing reactor configurations can yield inaccurate results. Furthermore, utilizing propellants other than hydrogen gas can cause significant changes to the power shape, and thus, the thermal performance of a specific reactor design. This methodology is being expanded to allow for multiple families of NTP reactors to be analyzed, including block moderator, particle bed, and NERVA-derived reactors.

multiphysics coupling↗

NASA NTRSDate not supplied

Coupled Reactor and Engine Nuclear Thermal Propulsion Modeling Methodology

multiphysics coupling↗

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 OSTI2021

Designing a Zn–Ag Catalyst Matrix and Electrolyzer System for CO 2 Conversion to CO and Beyond

CO 2 emissions can be transformed into high-added-value commodities through CO 2 electrocatalysis; however, efficient low-cost electrocatalysts are needed for global scale-up. Inspired by other emerging technologies, the authors report the development of a gas diffusion electrode containing highly dispersed Ag sites in a low-cost Zn matrix. Here, this catalyst shows unprecedented Ag mass activity for CO production: –614 mA cm –2 at 0.17 mg of Ag. Subsequent electrolyte engineering demonstrates that halide anions can further improve stability and activity of the Zn–Ag catalyst, outperforming pure Ag and Au. Membrane electrode assemblies are constructed and coupled to a microbial process that converts the CO to acetate and ethanol. Combined, these concepts present pathways to design catalysts and systems for CO 2 conversion toward sought-after products.

36 MATERIALS SCIENCE↗

DOE OSTI2023

A state-of-the-art review of experimental and computational studies of granular materials: Properties, advances, challenges, and future directions

Modeling of heterogeneous materials and media is a problem of fundamental importance to a wide class of phenomena and systems, ranging from condensed matter physics, soft materials, and composite media to porous media, biological systems, geosystems, ceramic engineering, pharmaceutical science and even in space discoveries. Among the most important materials are granular systems, which have received intense interest from the engineering, physics, and mathematics communities. In this review paper, the recent developments and new advances in experimental, and computational methods on a variety of scales and physics that extend understanding to a wide range of materials and phenomena are reviewed. Experimental advances include computed neutron and nanometer-scale tomography, magnetic resonance imaging, refractive index matching, digital image correlation, acoustic emission analysis, and the most recent 4D techniques. Furthermore, a tremendous shift has occurred from the continuum scale to micro-scale and developing multiscale approaches. As such, various computational methods, including, constitutive modeling, discrete modeling, and multiscale approaches, have been developed. In conclusion, aside from all these evolutions, more complicated modeling called coupled, or multiphysics, systems representing a simultaneous presence of heat, fluid, chemical variation, and mechanical effect are also explored.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Large-scale Multiphysics Simulations of Small Modular Reactors Operating in Natural Circulation

Thanks to the advancements in high-performance computing, advanced modeling and simulation have become crucial in driving the development and deployment of next-generation nuclear reactors, such as small modular reactors (SMRs). SMRs offer the promise of cost-effective baseload electricity production and improved safety, while addressing some of the challenges associated with large reactor designs, such as high capital costs and extended construction timelines. As part of the Exascale Computing Project, the large-scale multiphysics simulation of an entire SMR primary system has been achieved by combining computational fluid dynamics and neutronics. In addition to the successful demonstration of full-core SMR simulations, the current study integrated the impact of natural circulation into the system. Natural circulation is the primary mechanism driving coolant circulation in SMRs. The mass flow rate in the core depends on the core power, and a numerical model has been developed to predict it. The pressure drop caused by the helical coil steam generator was also accounted for by developing a pressure drop correlation based on high-fidelity large eddy simulation results, further improving prediction accuracy. In conclusion, the results of the study demonstrate that the implemented natural circulation model is effective in predicting the responses of SMR full-core multiphysics simulations.

ECP↗

DOE OSTI2023

Impact of fusion reactor neutronics modeling for transmutation and thermal feedback *

Abstract Fusion neutronics calculations provide important metrics pertinent to fusion device operations, such as tritium breeding ratios (TBRs) and data on heat deposition, material activation, and damage. Because of the high computational burden required to generate a high-fidelity Monte Carlo simulation of a 3D fusion device, various assumptions are made to reduce computational time by simplifying the reactor model or the calculation iteration. This paper explores the impact of fusion neutronics metrics such as the TBR and decay heat of structural materials based on assumptions of material composition in the fusion reactor and temperature modeling of materials. Results show that for compact tokamaks with high power and long operational cycles, the transmutation of structural materials is significant enough to cause a substantial change in the flux spectrum and decrease the TBR by 1.68% after 2 years of full power operation. Additionally, assuming a constant temperature and material density can impact the TBR calculations up to 3%.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Machine learning–aided real-time detection of keyhole pore generation in laser powder bed fusion

Porosity defects are currently a major factor that hinders the widespread adoption of laser-based metal additive manufacturing technologies. One common porosity occurs when an unstable vapor depression zone (keyhole) forms because of excess laser energy input. With simultaneous high-speed synchrotron x-ray imaging and thermal imaging, coupled with multiphysics simulations, we discovered two types of keyhole oscillation in laser powder bed fusion of Ti-6Al-4V. Amplifying this understanding with machine learning, we developed an approach for detecting the stochastic keyhole porosity generation events with submillisecond temporal resolution and near-perfect prediction rate. Finally, the highly accurate data labeling enabled by operando x-ray imaging allowed us to demonstrate a facile and practical way to adopt our approach in commercial systems.

42 ENGINEERING↗

DOE OSTI2026

Discovery of Probabilistic Dirichlet-to-Neumann Maps on Graphs

Dirichlet-to-Neumann maps enable the coupling of multiphysics simulations across computational subdomains by ensuring continuity of state variables and fluxes at artificial interfaces. We present a novel method for learning Dirichlet-to-Neumann maps on graphs using Gaussian processes, specifically for problems where the data obey a conservation law arising from an underlying partial differential equation. Our approach combines discrete exterior calculus and nonlinear optimal recovery to infer relationships between vertex and edge values. This framework yields data-driven predictions with uncertainty quantification across the entire graph, even when observations are limited to a subset of vertices and edges. By minimizing the reproducing kernel Hilbert space norm while penalizing kernel complexity through maximum likelihood estimation, our method ensures that the resulting surrogate strictly enforces conservation laws without overfitting. We demonstrate our method on two representative applications: subsurface flow in fracture networks and arterial blood flow. Finally, the results demonstrate that the method maintains high accuracy and well-calibrated uncertainty estimates even under severe data scarcity, highlighting its potential for scientific applications where limited data and reliable uncertainty quantification are critical.

Dirichlet-to-Neumann map↗

DOE OSTI2021

A New Design of a Dressed Balloon Cavity with Superior Mechanical Properties

Superconducting spoke cavities are prone to multipactor - resonant raise of a number of electrons due to secondary emission. Recently proposed and tested by TRIUMF balloon-type spoke cavity showed an outstanding multipactor (MP) suppression property but unfortunately serious Q degradation at high fields. A new fully developed design of a dressed balloon cavity which can be used for any proton linac SSR2 section is developed. The design incorporates additional EP ports for high Q-factor demonstration. Superior properties are demonstrated, such as effective multipactor suppression, 40% lower Lorentz force coefficient, zero sensitivity to external pressure. This paper presents the results of coupled structural Multiphysics analysis, and engineering design of the dressed balloon cavity with EP ports.

43 PARTICLE ACCELERATORS↗

DOE OSTI2020

Sockeye Theory Manual

Sockeye is an application that models heat pipe performance, based on the MOOSE framework. Its primary focus is on liquid-metal heat pipes with annular screen or porous wick structures, with the intended application being the simulation of heat pipes in microreactors. The purpose of this capability is to evaluate and understand heat pipe performance under different conditions. Furthermore, this heat pipe performance is intended to be coupled to multiphysics applications for modeling microreactors, so that the effects of heat pipe performance on the larger reactor system can be simulated.

42 ENGINEERING↗

DOE OSTI2023

Mapping the performance of a versatile water-based condensation particle counter (vWCPC) with numerical simulation and experimental study

Accurate airborne aerosol instrumentation is required to determine the spatial distribution of ambient aerosol particles, particularly when dealing with the complex vertical profiles and horizontal variations of atmospheric aerosols. A versatile water-based condensation particle counter (vWCPC) has been developed to provide aerosol concentration measurements under various environments with the advantage of reducing the health and safety concerns associated with using butanol or other chemicals as the working fluid. However, the airborne deployment of vWCPCs is relatively limited due to the lack of characterization of vWCPC performance at reduced pressures. Given the complex combinations of operating parameters in vWCPCs, modeling studies have advantages in mapping vWCPC performance. In this work, we thoroughly investigated the performance of a laminar-flow vWCPC using COMSOL Multiphysics® simulation coupled with MATLAB™. We compared it against a modified vWCPC (vWCPC model 3789, TSI, Shoreview, MN, USA). Our simulation determined the performance of particle activation and droplet growth in the vWCPC growth tube, including the supersaturation, $D$ p,kel,0 (smallest size of particle that can be activated), $D$ p,kel,50 (particle size activated with 50 % efficiency) profile, and final growth particle size D d under wide operating temperatures, inlet pressures $P$ (30–101 kPa), and growth tube geometry (diameter $D$ and initiator length $L$ ini ). The effect of inlet pressure and conditioner temperature on vWCPC 3789 performance was also examined and compared with laboratory experiments. The COMSOL simulation result showed that increasing the temperature difference (Δ$T$) between conditioner temperature $T$ con and initiator $T$ ini will reduce $D$ p,kel,0 and the cut-off size $D$ p,kel,50 of the vWCPC. In addition, lowering the temperature midpoint ($T$ mid = $\frac{T_{con}+T_{ini}}{2}$ increases the supersaturation and slightly decreases the $D$ p,kel . The droplet size at the end of the growth tube is not significantly dependent on raising or lowering the temperature midpoint but significantly decreases at reduced inlet pressure, which indirectly alters the vWCPC empirical cut-off size. Our study shows that the current simulated growth tube geometry ($D$=6.3 mm and $L$ ini =30 mm) is an optimized choice for current vWCPC flow and temperature settings. The current simulation can more realistically represent the $D$ p,kel for 7 nm vWCPC and also achieved good agreement with the 2 nm setting. Using the new simulation approach, we provide an optimized operation setting for the 7 nm setting. This study will guide further vWCPC performance optimization for applications requiring precise particle detection and atmospheric aerosol monitoring.

47 OTHER INSTRUMENTATION↗

NASA NTRS1997

An Overview of Three Approaches to Multidisciplinary Aeropropulsion Simulations

The broad scope of aeropropulsion multidisciplinary applications necessitates that a collection of approaches, with distinct capabilities, be developed. Three general approaches to multidisciplinary simulations have been identified. The three approaches; loosely coupled, coupled process, and multiphysics, provide a comprehensive collection of capabilities for multidisciplinary aeropropulsion analysis. At the data access level, or loosely coupled approach of coupling, existing disciplinary simulations are run, data is generated, and made available and used for subsequent analysis. The data must be in the correct format for implementation by the subsequent analysis but the subsequent code need not directly communicate with the previous code. At the process level, or coupled process approach of coupling, individual disciplinary codes are used, similarly to the loosely coupled approach, however, in the coupled process approach the disciplinary codes need to run concurrently with each other. The system of equation coupled approach, or multiphysics approach, addresses those applications whose characteristics require that the disciplines be coupled at the fundamental equation level to accurately, or more efficiently, capture the multidisciplinary physics of the problem. No one of these approaches, by itself, addresses all of the community needs in this area. However, collectively the three approaches encompass all of the multidisciplinary applications which have been identified thus far. Multiple approaches to multidisciplinary simulations will be needed as long as the applications and their requirements remain as diverse as they currently are today.

Lawrence, Charles↗

DOE OSTI2024

Dynamic flux surrogate-based partitioned methods for interface problems

Loosely coupled partitioned methods for multiphysics problems treat each subproblem as a separate entity and advance them independently in time. In so doing these methods enable code reuse, increase concurrency and provide a convenient framework for plug-and-play multiphysics simulations. However, mathematically loosely coupled schemes are equivalent to a single step of an iterative solution method, which can compromise their accuracy and stability. We present a new data-driven partitioned method for coupled parametric PDEs that can improve upon the accuracy of traditional loosely coupled methods without incurring a performance penalty. To that end, we replace conventional field transfers across the interface by a surrogate for the dynamics of the interface flux exchanged between the subdomains. To develop this surrogate we apply dynamic mode decomposition to a non-standard staggered-in-time state, comprising the interface flux and small solution patches near the interface. The new approach shifts the main computational burden to an offline training phase, whereas application of the surrogate in the online phase amounts to a single matrix–vector multiplication. In conclusion, we provide stability analysis of the surrogate-based partitioned scheme and include numerical results that demonstrate its potential.

Dynamic mode decomposition (DMD)↗

DOE OSTI2026

Innovations in underground hydrogen storage with multiphysics simulations, optimization, and monitoring: A review

Underground Hydrogen Storage (UHS) is a promising solution for large-scale energy storage and a critical component in advancing low-carbon energy system. Ensuring the safety and efficiency of UHS necessitates a comprehensive understanding of multiphysical interactions driven by cyclic pore fluid pressure fluctuations and coupled physicochemical processes. Here, this review examines the key geomechanical responses in UHS, including rock property variations under cyclic loading, fracture evolution and propagation, reservoir stress sensitivity, and fault stability. It also explores the impact of geochemical and microbial reactions on geomechanical characteristics. We provide an in-depth analysis of Thermal-Hydraulic-Mechanical-Chemical (THMC) coupled numerical simulations, highlighting their potential for future multi-scale modeling. Limitations of current machine learning (ML) approaches in addressing UHS challenges are highlighted, emphasizing the need for innovative ML-based methodologies. Operational strategies for hydrogen injection and production are reviewed, focusing on safety, efficiency, and economic viability. The necessity for multi-objective optimization (MOO) to balance storage efficiency, risk mitigation, and cost-effectiveness is also discussed. Current monitoring technologies are evaluated to ensure safe and efficient UHS operations. Finally, this review identifies critical knowledge gaps and underscores the importance of advancing geomechanical understanding under multiphysics-coupling. We highlight the need for ML-driven multiphysics theories, enhanced modeling techniques, and robust optimization strategies to improve UHS performance. This study serves as a comprehensive reference for future research and the large-scale implementation of UHS systems.

25 ENERGY STORAGE↗

DOE OSTI2021

A Novel Multiphysics Multiscale Multiporosity Shale Gas Transport Model for Geomechanics/Flow Coupling in Steady and Transient States

Summary A novel multiphysics multiscale multiporosity shale gas transport (M3ST) model was developed to investigate shale gas transport in both transient and steady states. The microscale model component contains a kerogen domain and an inorganic matrix domain, and each domain has its own geomechanical and gas transport properties. Permeabilities of various shale cores were measured in the laboratory using a pulse decay permeameter (PDP) with different pore pressure and confining stress combinations. The PDP-measured apparent permeability as a function of pore pressure under two effective stresses was fitted using the microscale M3ST model component based on nonlinear least squares fitting (NLSF), and the fitted model parameters were able to provide accurate model predictions for another effective stress. The parameters and petrophysical properties determined in the steady state were then used in the transient-state, continuum-scale M3ST model component, which performed history matching of the evolutions of the upstream and downstream gas pressures. In addition, a double-exponential empirical model was developed as a powerful alternative to the M3ST model to fit laboratory-measured apparent permeability under various effective stresses and pore pressures. The developed M3ST model and the research findings in this study provided critical insights into the role of the multiphysics mechanisms, including geomechanics, fluid dynamics and transport, and the Klinkenberg effect on shale gas transport across different spatial scales in both steady and transient states.

Engineering↗