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NASA NTRSDate not supplied

Recent Advancements in the PATO Material Response Code

Introduction: Predicting the complicated multiphysics phenomena during atmospheric entry requires high-fidelity modeling tools to refine estimates of mission risks during entry. To this end, new capabilities are being added to the Porous-material Analysis Toolbox based on OpenFOAM (PATO). PATO is an open-source software for Computational Material Response (CMR) of reactive porous materials submitted to high-temperature environments. The objective of this work is to highlight current efforts to add to and improve upon the modeling capabilities of PATO. These include efforts to loosely couple PATO with other discipline specialized codes including hypersonic Computational Fluid Dynamics (CFD), to assess the interaction effects between pyrolysis gas blowing and the boundary layer, and Computational Solid Mechanics (CSM), to address modeling of mechanical erosion. Other refinements include surface phenomena modeling capabilities to address the effects of silicone-based coatings applied to the TPS during flight preparation, and a unified multiphase solver for a mixed porous-material and plain-fluid domain. Coupling CMR with CFD (CMR/CFD): A loose coupling between PATO and the Data Parallel Line Relaxation (DPLR) CFD code has been achieved by making use of a blowing boundary condition at the heatshield surface available in DPLR. Starting with heat flux estimates with no pyrolysis gas blowing at the surface, blowing gases are computed by the CMR and passed to the CFD such that aerothermal properties of the environment can be recomputed for a new CMR computation. This leads to an iterative process which is supplemented with an estimate of the radiative heat flux using the Nonequilibrium air radiation (NEQAIR) program. The entire iterative process is illustrated in Figure 1. This coupling strategy has been utilized in computing the MSL material response. The goal is to compare the coupled CMR/CFD results with material response results obtained using traditional blowing corrections. Coupling CMS with CMR: A mechanical erosion model is currently being implemented in PATO to account for the additional mass removal induced by high shear conditions. The modeling process at each timestep consists of updating the mechanical properties as a function of temperature and computing the stress tensor and displacement fields of the material. Then, a failure criteria model determines the regions in which the stress exceeds the ultimate strength values resulting in mesh movement to account for mass removal. This model allows the material response simulation to compute the recession due to both oxidation and shear-induced erosion. The model is demonstrated by computing material response of sphere-cone arc jet samples. Surface Modeling Capabilities: NuSil, a silicone-based coating, was sprayed onto the MSL and Mars 2020 heatshields to mitigate shedding of phenolic dust. To better understand the effects of the NuSil coating on the material response, a novel model has been implemented in PATO. In this model, the equilibrium of the charred NuSil surface is modeled as pure silica, and a constant offset, inspired by the classical spallation model, is added to the the char blowing rate and wall enthalpy to reproduce HyMETS experimental results. The model has also been used to estimate the 3D material response of the MSL heatshield. Unified Solver: In addition to the iterative loose coupling approach mentioned above, a multiphase unified solver is being developed to couple the environment (plain-fluid phase) and the porous-material phase. The solver is based on the volume averaged conservation of mass, momentum, and energy for the macroscale with closure models which include microscale effects through effective physicochemical properties. The unified solver has been used to compute flow through a porous plug and solve the Beavers and Joseph problem. Since the strong coupling between phases is inherent to this solver, modeling assumptions present in other coupling methods of material response are mitigated. This strategy also makes it feasible to capture the competition between surface and volume ablation in the same computational domain, which is usually not possible with other coupling approaches.

Material Response↗
NASA NTRSDate not supplied

Recent Advancements in the PATO Material Response Code

Introduction: Predicting the complicated multiphysics phenomena during atmospheric entry requires high-fidelity modeling tools to refine estimates of mission risks during entry. To this end, new capabilities are being added to the Porous-material Analysis Toolbox based on OpenFOAM (PATO) [1,2,3]. PATO is an open-source software for Computational Material Response (CMR) of reactive porous materials submitted to high-temperature environments. The objective of this work is to highlight current efforts to add to and improve upon the modeling capabilities of PATO. These include efforts to loosely couple PATO with other discipline specialized codes including hypersonic Computational Fluid Dynamics (CFD), to assess the interaction effects between pyrolysis gas blowing and the boundary layer, and Computational Solid Mechanics (CSM), to address modeling of mechanical erosion. Other refinements include surface phenomena modeling capabilities to address the effects of silicone-based coatings applied to the TPS during flight preparation, and a unified multiphase solver for a mixed porous-material and plain-fluid domain. Coupling CMR with CFD (CMR/CFD): A loose coupling between PATO and the Data Parallel Line Relaxation (DPLR) [4] CFD code has been achieved by making use of a blowing boundary condition at the heatshield surface available in DPLR. Starting with heat flux estimates with no pyrolysis gas blowing at the surface, blowing gases are computed by the CMR and passed to the CFD such that aerothermal properties of the environment can be recomputed for a new CMR computation. This leads to an iterative process which is supplemented with an estimate of the radiative heat flux using the Nonequilibrium air radiation (NEQAIR) [5] program. The entire iterative process is illustrated in Figure 1. This coupling strategy has been utilized in computing the MSL material response. The goal is to compare the coupled CMR/CFD results with material response results obtained using traditional blowing corrections. Coupling CMS with CMR: A mechanical erosion model is currently being implemented in PATO to account for the additional mass removal induced by high shear conditions. The modeling process at each timestep consists of updating the mechanical properties as a function of temperature and computing the stress tensor and displacement fields of the material. Then, a failure criteria model determines the regions in which the stress exceeds the ultimate strength values resulting in mesh movement to account for mass removal. This model allows the material response simulation to compute the recession due to both oxidation and shear-induced erosion. The model is demonstrated by computing material response of sphere-cone arc jet samples. Surface Modeling Capabilities: NuSil, a silicone-based coating, was sprayed onto the MSL and Mars 2020 heatshields to mitigate shedding of phenolic dust. To better understand the effects of the NuSil coating on the material response, a novel model has been implemented in PATO. In this model, the equilibrium of the charred NuSil surface is modeled as pure silica, and a constant offset, inspired by the classical spallation model, is added to the the char blowing rate and wall enthalpy to reproduce HyMETS experimental results. The model has also been used to estimate the 3D material response of the MSL heatshield [6]. Unified Solver: In addition to the iterative loose coupling approach mentioned above, a multiphase unified solver is being developed to couple the environment (plain-fluid phase) and the porous-material phase. The solver is based on the volume averaged conservation of mass, momentum, and energy for the macroscale with closure models which include microscale effects through effective physicochemical properties. The unified solver has been used to compute flow through a porous plug and solve the Beavers and Joseph problem [7]. Since the strong coupling between phases is inherent to this solver, modeling assumptions present in other coupling methods of material response are mitigated. This strategy also makes it feasible to capture the competition between surface and volume ablation in the same computational domain, which is usually not possible with other coupling approaches.

Thermal Protection Systems↗
DOE OSTI2023

Domain Aware Deep-learning Algorithms Integrated with Scientific-computing Technologies (DADAIST)

This technical report summarized the contribution of the DADAIST project funded by the Data Model Convergence Initiative via the Laboratory Directed Research and Development (LDRD) investments at Pacific Northwest National Laboratory (PNNL). Specifically, we report the development of the NeuroMANCER (Neural Modules with Adaptive Nonlinear Constraints and Efficient Regularizations), a new open-source Scientific Machine Learning library for formulating and solving parametric constrained optimization problems, physics-informed system identification, and parametric optimal control problems. NeuroMANCER is using differentiable programming to combine modern data-driven models and optimization modeling language into a coherent algorithmic and software framework. NeuroMANCER is a Pytorch-based framework and adopts much of its philosophy focused on research and development, rapid prototyping, and streamlined deployment. Strong emphasis is given to extensibility, interoperability with the PyTorch ecosystem, and quick adaptability to custom domain problems. Neuromancer repository contains a comprehensive library of differentiable modules, including custom activation functions, matrix factorizations, deep learning architectures, neural differential equations, differential equation solvers, implicit layers such as iterative solvers, high-level API for symbolic expressions, API for modeling and control of dynamical systems, and extensive set of tutorial code examples in the form of python scripts and jupyter notebooks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Scientific Core Library Stack (SCLS) v2026

SCLS (Scientific Core Library Stack) is an opinionated build and packaging system for scientific computing libraries developed at Lawrence Berkeley National Laboratory. It produces a coherent, reproducible stack of numerical libraries — including BLAS/LAPACK, MPI, sparse direct and iterative solvers, graph partitioners, and parallel I/O libraries (e.g., PETSc, SLEPc, HDF5, NetCDF, MUMPS, OpenBLAS) — that work together without manual repair by downstream scientific software. From a single recipe-and-flavor model, SCLS produces native RPM packages for RHEL-family Linux, DEB packages for Debian/Ubuntu, direct Unix-style prefix installs for HPC and locked-down environments, and native macOS builds. Multiple build "flavors" (e.g., GCC+OpenBLAS, GCC+MKL, Intel+MKL, debug) coexist in distinct prefixes on the same host. Compared to general-purpose meta-build frameworks, SCLS is deliberately curated rather than infinitely configurable. It enforces deterministic, audit-friendly behavior: explicit build dependencies, no silent feature autodetection, a clear open-source license policy, and rpath-based runtime linkage so installs integrate cleanly with standard package-manager workflows.

Messe, Christian [Lawrence Berkeley National Labor↗
DOE OSTI2025

The Water Table Model (WTM) (v2.0.1): coupled groundwater and dynamic lake modelling

Abstract. Ice-free land comprises 26 % of the Earth's surface and holds liquid water that delineates ecosystems, affects global geochemical cycling, and modulates sea levels. However, we currently lack the capacity to simulate and predict these terrestrial water changes across the full range of relevant spatial (watershed to global) and temporal (monthly to millennial) scales. To address this knowledge gap, we present the Water Table Model (WTM), which integrates coupled components to compute dynamic lake and groundwater levels. The groundwater component solves the 2D horizontal groundwater flow equation using non-linear equation solvers from the C++ PETSc (Portable, Extensible Toolkit for Scientific Computation) library. The dynamic lake component makes use of the Fill–Spill–Merge (FSM) algorithm to move surface water into lakes, where it may evaporate or affect groundwater flow. In a proof-of-concept application, we demonstrate the continental-scale capabilities of the WTM by simulating the steady-state climate-driven water table for the present day and the Last Glacial Maximum (LGM; 21 000 calendar years before present) across the North American continent. During the LGM, North America stored an additional 14.98 cm of sea-level equivalent (SLE) in lakes and groundwater compared to the climate-driven present-day scenario. We compare the present-day result to other simulations and real-world data. Open-source code for the WTM is available on GitHub and Zenodo.

Callaghan, Kerry L. (ORCID:0000000226740838)↗
DOE OSTI2024

ReEDS Performance Improvement

The Regional Energy Deployment System (ReEDS) is an open-source, spatially explicit, long-term capacity expansion model for the bulk electric power system of the contiguous United States, encompassing multiple scenarios with technological and political assumptions (see https://github.com/NREL/ReEDS-2.0). With the increased needs for capabilities, higher temporal and spatial resolutions to model the evolution of the power system with modern technologies and low-carbon pathways, ReEDS' model solution times have increased significantly from 4-6 hours in 2018 to 18-48+ hours in 2023 . Also, the model size for commonly-run ReEDS scenarios reached 22 and 28 million equations and variables, respectively. These runtimes can be especially challenging under certain scenario settings (e.g., very high temporal or spatial resolution) or with limited computational power. In this presentation, we will discuss several methods we used to improve model runtime, including data preparation, model modification, and solver tuning. The implementation of these methods shrank the model size to 7.2 and 7.3 million equations and variables, respectively. Furthermore, this led to a 77% reduction in the model's run time for commonly-run ReEDS scenarios. We will discuss the process of identifying areas for solve time improvements and how the specific enhancements for the ReEDS model might be applied to other similar large-scale models.

ENERGY PLANNING, POLICY, AND ECONOMY,MATHEMATICS A↗
DOE OSTI2025

Kinetic Plasma Simulation Capabilities in the MOOSE Framework: Verification of Particle-Particle Collisions

High-fidelity simulations of complex plasma systems allow researchers to gain key insights into and understanding of these systems. To facilitate massively parallel high-fidelity plasma simulations, finite-element-based particle-in-cell capabilities are being developed within the open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) based framework called Software for Advanced Large-scale Analysis of MAgnetic confinement for Numerical Design, Engineering & Research (SALAMANDER). While SALAMANDER’s primary objective is modeling edge plasmas and plasma-facing components in fusion devices, the particle-in-cell capabilities being developed are general and will support modeling low-temperature plasmas as well. Previously, collisionless magnetostatic simulation capabilities have been verified with the two-stream and Dorey-Guest-Harris instabilities, and single particle motion. Collisions were implemented using the direct simulation Monte Carlo method, and verification of this capability will be presented here several verification problems: relaxation of a randomly initialized gas to a Maxwellian distribution, Fourier heat flow, and comparison of reaction rates to both analytic calculations and those calculated using a multi-term Boltzmann solver.

70 - PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

The Verification and Validation of a Magnetic Plasma Fluid Model Utilizing the MOOSE (Multiphysics Object Oriented Simulation Environment) Framework

As the goal of achieving fusion power on the grid comes closer to fruition, fully coupled multiphysics models of fusion devices will be crucial. Currently, there are two main approaches to developing these platforms: (1) loosely coupled, where one couples existing codes and solvers together through input and output parameters and data, and (2) tightly coupled, where one develops the necessary models within a singular, integrated framework. This work focuses on the latter approach for magnetically confined fusion devices by developing a fluid-based plasma-edge model within the Multiphysics Object Oriented Simulation Environment (MOOSE) Framework. This effort is coordinated with other efforts to develop, test, demonstrate, and deploy fusion relevant multiphysics capabilities including electromagnetics, particle-in-cell plasma, tritium transport, and fusion blanket design. This new model is an expansion of the MOOSE-based plasma application, Zapdos, which was originally formulated to model low-temperature, non-magnetized plasma processes. Verification, benchmarking, and validation studies have been conducted. Verification studies involved utilizing the method of manufactured solutions and comparing the convergence slope of a known solution to the theoretical slope. Benchmarking consists of comparisons to existing edge codes, namely BOUT++ and SOLEDGE3X. Validation efforts focused on comparisons against open-source data from the TCV tokamak.

70 - PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

New Developments and Capabilities Within WEC-Sim

WEC-Sim is an open-source software for simulating wave energy converters and has been actively developed and applied since its initial release in 2014 to simulate a wide variety of device archetypes. WEC-Sim is developed jointly by the National Renewable Energy Laboratory and Sandia National Laboratories within the MATLAB/SIMULINK environment. A general wave-to-wire model begins with a deployment site resource characterization, which is used to complete the hydrodynamic simulation of wave energy converters (WEC), with the power generation profile imported to a grid simulator to understand the influence on the local electrical network. While modeling the entire wave-to-wire is difficult and encompasses multiple time scales and physics, WEC-Sim is focused on the hydrodynamics simulation to predict, analyze, and optimize WEC dynamics and power performance. WEC-Sim simulations are performed in the time domain based on the radiation and diffraction method using hydrodynamics coefficients derived from boundary element method (BEM)-based frequency-domain potential flow solvers (e.g., WAMIT, NEMOH, Capytaine, or ANSYS-AQWA). With this level of modeling fidelity, WEC-Sim can handle floating body hydrodynamics, mechanical and electrical power generation methods, advanced control implementation, mooring systems, and other unique applications such as desalination. Additional WEC-Sim functionalities include pre-built Simulink blocks and MATLAB scripts that can simulate a wide range of floating systems and the corresponding auxiliary subsystems. The developers of WEC-Sim continue to release new versions of the software, at least annually, with the latest release in September 2022. These releases include bug fixes, updates to software documentation, as well as new features to expand WEC-Sim's capabilities to model a wide range of WEC concepts. This publication will highlight the new features added to WEC-Sim between versions 4.1.0 to 5.0.1, which spans a 2-year period from June 2020 to September 2022. New features described here include topics such as continuous integration checks, revised Morison Element and nonlinear hydro implementations, run directly from Simulink (required for hardware-in-the-loop execution), BEMIO updates to import Capytaine BEM hydrodynamics, addition of cable blocks, and new wave visualization features.

TIDAL AND WAVE POWER↗
DOE OSTI2024

Towards exascale for wind energy simulations

We examine large-eddy-simulation modeling approaches and computational performance of two open-source computational fluid dynamics codes for the simulation of atmospheric boundary layer flows that are of direct relevance to wind energy production. The first code, NekRS, is a high-order, unstructured-grid, spectral element code. The second code, AMR-Wind, is a second-order, block-structured, finite-volume code with adaptive mesh refinement capabilities. The objective of this study is to co-develop these codes in order to improve model fidelity and performance for each. These features will be critical for running ABL-based applications such as wind farm analysis on advanced computing architectures. To this end, we investigate the performance of NekRS and AMR-Wind on the Oak Ridge Leadership Facility supercomputers Summit, using 4 to 800 nodes (24 to 4,800 NVIDIA V100 GPUs), and Crusher, the testbed for the Frontier exascale system, using 18 to 384 Graphics Compute Dies on AMD MI250X GPUs. We compare strong- and weak-scaling capabilities, linear solver performance, and time to solution. We also identify leading inhibitors to parallel scaling.

17 WIND ENERGY↗
NASA NTRSDate not supplied

Trajectory Engineering with Modular Patched Conics for Entry Systems and TPS (TEMPEST)

Brief Presenter Biography (35 word limit): Bohdan Wesely is an Aerospace Engineer in the Entry Systems and Technology Division at Ames. He has worked on a variety of projects for NASA including integrated TPS (thermal protection system) flight hardware deliveries and testing services for commercial partners. Introduction: TEMPEST is a new trajectory analysis framework that is designed to fill the gap between dedicated flight mechanics tools and aerothermal and TPS sizing tools. The project started as an SJSU master’s thesis and has since evolved into a general conceptual design tool capable of studying a wide variety of entry problems. Development is ongoing in the Entry Systems and Technology Division at NASA ARC. Why TEMPEST: Space missions involving entry into a planetary atmosphere involve a series of unique requirements across multiple disciplines. Whether it is traditional entry descent and landing (EDL), or aerocapture, the vehicle must navigate to its target landing location or orbit state, and the TPS must protect the payload during entry. The design process typically involves iterative handoffs between various flight mechanics, flow solver, and material response level tools. During the early conceptual phase, a wide variety of feasible trajectories are simulated in a Monte Carlo scenario which broadly satisfy the mission or landing requirements. Next, computational fluid dynamics (CFD), direct simulation Monte Carlo (DSMC), and other flow solver analyses are performed at various key trajectory points to generate an aero-database, heating and TPS design requirements also emerge at this stage. At this point, with updated aerodynamics from the various flow solvers, trajectories can be re-run, this in turn can change the required freestream conditions for the CFD tools, and as a project progresses, these analyses converge, and uncertainty is reduced. However, there is always a “hand-off” occurring between two inherently coupled phenomena. Analysis Description: One of the goals with TEMPEST is to use a variety of first principles estimation methods coupled with an atmosphere model to predict vehicle aerothermodynamics across the entire flight regime while propagating a 3 or 6 degree of freedom (DoF) trajectory. Aerodynamics methods include modified Newtonian, Maxwell and Cercignani- Lampis-Lord (CLL) for continuum, transitional, and free molecular flow regimes. Aerothermodynamics include boundary layer and reference enthalpy methods, and Mutation++ for non-equilibrium chemistry modeling. TEMPEST is also capable of stitching multiple trajectory segments together to study mission scenarios like multi-pass aerocapture and aero-gravity assists. Most of the program is implemented in MATLAB using modern system objects, it relies on several C++ shared libraries for supporting tools like Gmsh, the Global Reference Atmospheric Model (GRAM), and Mutation++. The various first principles aerothermal estimation methods are discretized across either a structured axisymmetric panel mesh or an unstructured tri-mesh generated from an open-source tool such as Gmsh, this allows solutions on the same mesh to be compared across tools such as CB-Aero. CFD Coupling. A physics-aware, gaussian process CFD anchoring scheme is proposed to adjust the various first principles methods as a CFD database is populated. One goal for this anchoring module is to inform the project where CFD should be run. Full knowledge of the entire trajectory, atmosphere, and aerothermodynamics allows for easier identification of high sensitivity areas and uncertainty quantification. While the first principles effects are well known and proven accurate in existing tools such as CB- Aero and Cart3D, a physics aware CFD anchoring scheme increases tool credibility across a project lifecycle. Material Response Modeling. Correct TPS sizing is critical for optimizing mass for science payloads and ensuring mission success. The process typically involves a thermal analysis along the trajectory with surface heating environments as a boundary condition. Several design constraints are maximum bondline temperature and maximum recession with various margining techniques. The material response tool FIAT, developed out of NASA Ames, is currently being integrated into the TEMPEST environment. TPS recession, shape change, mass loss, and mass property alteration are all factors that can perturb an entry trajectory. For missions like Mars 2020, recession was minimal and was safely handled separately as a post process. For missions such as Jupiter Galileo with a high TPS mass fraction or asteroid entries, recession plays a major role. The proposed fully coupled scheme is to use an epoch-based approach where the trajectory integration is halted after a recession threshold, the energy balance and FIAT are solved at each panel, the mesh, aerodynamics, and mass properties are updated, and the trajectory continues. Several computational tradeoffs have been made during the development of TEMPEST to limit the cost of a single trajectory and preserve its utility as a conceptual, rapid iteration tool. Conclusion: Development of TEMPEST is ongoing and the project is still in its infancy. This talk aims to showcase its unique capabilities to support future NASA entry systems missions.

Bohdan O Wesely↗
DOE OSTI2024

GX: a GPU-native gyrokinetic turbulence code for tokamak and stellarator design

GX is a code designed to solve the nonlinear gyrokinetic system for low-frequency turbulence in magnetized plasmas, particularly tokamaks and stellarators. In GX, our primary motivation and target is a fast gyrokinetic solver that can be used for fusion reactor design and optimization along with wide-ranging physics exploration. Here, this has led to several code and algorithm design decisions, specifically chosen to prioritize time to solution. First, we have used a discretization algorithm that is pseudospectral in the entire phase space, including a Laguerre–Hermite pseudospectral formulation of velocity space, which allows for smooth interpolation between coarse gyrofluid-like resolutions and finer conventional gyrokinetic resolutions and efficient evaluation of a model collision operator. Additionally, we have built GX to natively target graphics processors (GPUs), which are among the fastest computational platforms available today. Finally, we have taken advantage of the reactor-relevant limit of small $\rho _*$ by using the radially local flux-tube approach. In this paper we present details about the gyrokinetic system and the numerical algorithms used in GX to solve the system. We then present several numerical benchmarks against established gyrokinetic codes in both tokamak and stellarator magnetic geometries to verify that GX correctly simulates gyrokinetic turbulence in the small $\rho _*$. Moreover, we show that the convergence properties of the Laguerre–Hermite spectral velocity formulation are quite favourable for nonlinear problems of interest. Coupled with GPU acceleration, which we also investigate with scaling studies, this enables GX to be able to produce useful turbulence simulations in minutes on one (or a few) GPUs and higher fidelity results in a few hours using several GPUs. GX is open-source software that is ready for fusion reactor design studies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Feedforward equilibrium trajectory optimization with GSPulse

One of the common tasks required for designing new plasma scenarios or evaluating capabilities of a tokamak is to design the desired equilibria using a Grad-Shafranov (GS) equilibrium solver. However, most standard equilibrium solvers are time-independent and do not include dynamic effects such as plasma current flux consumption, induced vessel currents, or voltage constraints. Another class of tools, plasma equilibrium evolution simulators, do include time-dependent effects. These are generally structured to solve the forward problem of evolving the plasma equilibrium given feedback-controlled voltages. In this work, we introduce GSPulse, a novel algorithm for equilibrium trajectory optimization, that is more akin to a pulse planner than a pulse simulator. GSPulse includes time-dependent effects and solves the inverse problem: given a user-specified set of target equilibrium shapes, as well as limits on the coil currents and voltages, the optimizer returns trajectories of the voltages, currents, and achievable equilibria. This task is useful for scoping performance of a tokamak and exploring the space of achievable pulses. The computed equilibria satisfy both Grad-Shafranov force balance and axisymmetric circuit dynamics. The optimization is performed by restructuring the free-boundary equilibrium evolution equations into a form where it is computationally efficient to optimize the entire dynamic sequence. GSPulse can solve for hundreds of equilibria simultaneously within a few minutes. GSPulse has been validated against NSTX-U and MAST-U experiments and against SPARC feedback control simulations, and is being used to perform scenario design for SPARC. The computed trajectories can be used as feedforward inputs that are connected to the feedback controller to inform and improve feedback performance. The code for GSPulse is available open-source at github.com/jwai-cfs/GSPulse_public.

equilibrium↗
DOE OSTI2025

Verification of a Fluid-Based Plasma-Edge Model Within the Multiphysics Object-Oriented Simulation Environment (MOOSE) Framework

As the goal of achieving fusion power on the grid comes closer to fruition, fully coupled multiphysics models of fusion devices will be crucial. These models must incorporate the interconnected phenomena of these devices, including plasma physics, neutronics, first wall interactions, and tritium transport. Currently, there are two main approaches to developing these platforms: (1) loosely coupled, where one couples existing codes and solvers together through input and output parameters and data, and (2) tightly coupled, where one develops the necessary models within a singular, integrated framework. This work focuses on the latter approach for magnetically confined fusion devices by developing a fluid-based plasma-edge model within the Multiphysics Object Oriented Simulation Environment (MOOSE) Framework. This effort is coordinated with other efforts to develop, test, demonstrate, and deploy fusion relevant multiphysics capabilities including electromagnetics, particle-in-cell plasma, tritium transport, and fusion blanket design. This new model is an expansion of the MOOSE-based plasma application, Zapdos, which was originally formulated to model low-temperature, non-magnetized plasma processes. Verification studies have been conducted using newly developed magnetic plasma capabilities. These involved convergence analyses utilizing the method of manufactured solutions to verify new operators and case studies. A modular approach was taken here to demonstrate increasingly complicated simulation scenarios, which included a singular fluid with uniform magnetic field case, a singular fluid with spatially varying magnetic field case, and a coupled multifluid case.

70 - PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Symbolic construction of the chemical Jacobian of quasi-steady state (QSS) chemistries for Exascale computing platforms

The Quasi-Steady State Approximation (QSSA) can be an effective tool for reducing the size and stiffness of chemical mechanisms for implementation in computational reacting flow solvers. However, for many applications, the resulting model still requires implicit methods for efficient time integration. Here, in this paper, we outline an approach to formulating the QSSA reduction that is coupled with a strategy to generate C++ source code to evaluate the net species production rates, and the chemical Jacobian. The code-generation component employs a symbolic approach enabling a simple and effective strategy to analytically compute the chemical Jacobian. For computational tractability, the symbolic approach needs to be paired with common subexpression elimination which can negatively affect memory usage. Several solutions are outlined and successfully tested on a 3D multipulse ignition problem, thus allowing portable application across chemical model sizes and GPU capabilities. The implementation of the proposed method is available at https://github.com/AMReX-Combustion/PelePhysics under an open-source license.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Development of MOSCATO: A CFD-Level Electrochemistry and Corrosion Simulator for Molten Salt Systems

For both coolant and fueled variants of molten salt reactors (MSRs), the corrosion of structural materials is a significant challenge. The corrosion stems from chemical and electrochemical reactions initiated by fissile material, fission products, and impurities in the salt. Lower-fidelity models rely on empirical correlations for mass transfer, simplified lumped temperature profiles, and similar assumptions. They do not capture detailed spatial variations in complex geometries, creating the need for high-fidelity modeling to bridge this gap.As we approach the demonstration and possible deployment of MSRs in this decade, the development of a high-fidelity, high-performance simulator becomes imperative. To simulate the complex electrochemical environment and corrosion within molten salt systems, we have developed the Molten Salt Chemistry And TranspOrt (MOSCATO) code. This endeavor is comprised of three essential components. First, mass transfer equations are coupled with the Navier-Stokes equations in order to account for the transport of species in the salt. Second, the diffusion of alloy constituents, such as Cr, Fe, Ni, etc. is simulated within the structural metals. Third, the alloy and salt domains are coupled to account for the heterogeneous chemical and electrochemical reactions that occur at the salt-alloy interface.MOSCATO manages all three components within the framework of the highly scalable, open-source spectral element method computational fluid dynamics code Nek5000/NekRS. This integration enables MOSCATO to harness the immense computational power of modern high-performance computing resources, ensuring both high fidelity and computational speed.In addition to code development, we have initiated a comprehensive verification and validation campaign, utilizing data from diverse sources. First, MOSCATO's electrochemical solver was verified with reference numerical data. Then validation occurred against experiments: one of a thermal galvanic cell and the other for corrosion in flowing molten salt of FLiNaK (LiF-NaF-KF). This campaign verified and validated MOSCATO as a reliable tool for simulating electrochemical environments and corrosion in molten salt systems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Implementation of the D1S Methodology for Shutdown Dose Rate Calculations in the OpenMC Monte Carlo Particle Transport Code

We present an implementation of the direct one-step (D1S) methodology for shutdown dose rate (SDR) calculations in the OpenMC Monte Carlo particle transport code. In addition to being the first fully open-source D1S implementation, it is also the first to require no ad hoc source code or nuclear data library modifications. The code can seamlessly switch between production of prompt and decay photons based on a user input parameter, and the decay data needed for decay photon generation are made available through a depletion chain file, which is already used for OpenMC’s built-in depletion/activation solver. A set of Python functions significantly eases the burden of computing and applying time correction factors needed to properly account for the time dependence of radionuclide activity. To assess the accuracy of the D1S implementation, SDR calculations have been carried out for three problems: a prism of iron irradiated by 14-MeV neutrons, the ITER port plug computational benchmark, and the Frascati Neutron Generator (FNG) ITER dose rate benchmark problem from the Shielding INtegral Benchmark Archive and Database (SINBAD). For each of these problems, comparisons were made to calculations using the rigorous two-step (R2S) method. The results on the iron prism problem illustrate how the D1S method achieves superior spatial resolution compared to the R2S method without the need for spatial discretization of the activation regions. The D1S and R2S results for the ITER port plug benchmark agree well with previously reported results in the literature. While the D1S results are 10% to 15% lower than the R2S results, this may be due to stochastic uncertainty and/or spatial discretization in the R2S calculations. On the FNG dose rate benchmark problem, the D1S method produces dose rate estimates that are within 4% of the dose rates predicted using a cell-based R2S workflow. The D1S estimates of the SDR are also in reasonable agreement with the experimental measurements and show the same basic trends that have been observed in previous works. A qualitative analysis of the execution time and uncertainty for the R2S and D1S workflows suggests that the D1S method would attain a higher figure of merit.

D1S method↗
DOE OSTI2026

Hydrodynamic Analysis and Optimization of Aquantis Marine Turbine: Cooperative Research and Development (Final Report)

The primary aim of this proposal is to improve the accurate prediction of hydrodynamic performance and dynamic load responses of the AQ10 floating axial-flow tidal turbine with a tri-cat mooring configuration. The validation of reduced-order modeling approaches with high-fidelity model will be implemented. Additionally, the frequency response domain, Response Amplitude Floating Wind (RAFT) toolbox plus an optimizer expanded for marine hydrokinetic turbines under the Submarine Hydrokinetic And Riverine Kilo-megawatt. Systems (SHARKS) program will be used for designing and exploring different key design parameters (platform dimension, mooring layout and its parameters) of next marine hydrokinetic (MHK) turbine generation.

16 TIDAL AND WAVE POWER↗