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DOE OSTI2025

Nek5000/RS performance on advanced GPU architectures

The authors explore performance scalability of the open-source thermal-fluids code, NekRS, on the U.S. Department of Energy's leadership computers, Crusher, Frontier, Summit, Perlmutter, and Polaris. Particular attention is given to analyzing performance and time-to-solution at the strong-scale limit for a target efficiency of 80%, which is typical for production runs on the DOE's high-performance computing systems. Several examples of anomalous behavior are also discussed and analyzed.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Fixed Source Sensitivity Calculations for Inertial Confinement Fusion Applications

A numerical code library was developed for the radiation transport code MCNP6.3 to calculate generalized response sensitivity coefficients for fixed source neutron transport problems with applications to inertial confinement fusion (ICF) experiments. The new MCNP6.3 dependency is used to generate a novel time convolution response that represents a neutron time-of-flight (nToF) signal. The traditional suite of macroscopic cross-section sensitivities and constrained fixed source probability distribution sensitivities are available for both the standard and the new response tallies in this library. However, novel sensitivity coefficients for the constrained hyperparameters of analytic fixed source probability distributions are emphasized in this work for their connection to ICF neutron transport models. Particularly, advanced Monte Carlo methods are developed for calculating the sensitivity of a nToF signal to perturbations in an ICF plasma’s ion temperature and burn history as well as perturbations in the target liner mass density and the shape parameters of the nToF detector’s impulse response function. Together, these capabilities form an advanced suite of computational tools that can be used to analyze and extract information from any ICF experimental platform.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Demonstration of a code coupling framework for modeling beam-collimator impacts in the advanced photon source

The high-brightness beams being produced in current and future accelerators present new machine protection concerns with the potential for high-energy-density (HED) conditions ( >100 J/mm 3 ) in beam-intercepting components. Simulating HED conditions in accelerators requires utilizing a suite of physics codes for particle dynamics, particle-matter interactions, and hydrodynamics. This paper describes a method of coupling the codes elegant, fluka, and flash to simulate the effects of a rapid beam loss in the advanced photon source storage ring and the resulting interaction of the beam and collimators. This paper expands previous work [J. Dooling et al., Collimator irradiation studies at the advanced photon source, in Proceedings of the IBIC-2023 (2023), pp. 245–249] by introducing a definition of the evolving geometry of the collimator surface as well as providing methods for simulating the absorption of synchrotron radiation and tracking shower particles produced during beam strikes. We demonstrate this framework by simulating machine conditions of the APS ring before and after its recent upgrade. Simulation results are compared with observed damage to collimators and test samples taken from the APS ring.

Accelerator/storage ring control systems↗

DOE OSTI2024

A hybrid-kinetic simulation tool for non-thermal warm x-ray z-pinch sources, with gas-puff and wire array exemplars

Increasing the fluence of z-pinch x-ray radiation sources above ∼ 10 keV has been a long-standing goal for scientists at Sandia National Laboratories’ Z Machine. Optimizing sources for non-thermal “cold Kα” emission in higher atomic-number materials appears to be a promising path to increase warm x-ray yield. However, this emission is generated by supra-thermal electrons, which are not treated in the magnetohydrodynamic (MHD) codes that are typically used in z-pinch source development. MHD codes do not allow for charge separation or space-charge-generated electric fields, and constrain particle kinematics to Maxwellian distributions. The kinetic codes which do accommodate discrete, non-thermal energy distributions are computationally prohibitive when modeling plasmas near solid density and when modeling/tracking higher ionization states. Thus, modeling non-thermal z-pinch sources requires a new simulation tool. In this report, we present a new hybrid modeling capability that uses the fast features of MHD-type particles to the greatest extent possible, then transitions to the slower but more complete kinetic particle treatment to correctly capture the particle energy spectra that generate non-thermal emission. This capability is founded on the fully-relativistic particle-in-cell code Chicago, which already includes fluid particle treatments. The governing equations and hybrid methodology presented here are applied in simulations of an argon gas-puff and a molybdenum wire-array to provide preliminary code validation. The argon simulation is compared to measured implosion times and yields from Jones et al., Phys. Plasmas 22, 020706 (2015). The simulated x-ray yield is within 25% of measurements and the implosion times agree within a few percent. The molybdenum wire array simulation captures the implosion timing reported in Hansen et al., Phys. Plasmas 21, 031202 (2014), but work is needed to verify the available EOS table. These exemplar simulations represents the type of non-thermal sources that will be developed using the hybrid code capability going forward.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Code for the manuscript "Mori-Zwanzig Modal Decomposition"

We would like to create an open source repository in LANL's github on code written in Julia, in which we implement and extend the data-driven Mori-Zwanzig method for extracting large-scale spatio-temporal structures from data, which we call MZMD. This method is an extension of Dynamic Mode Decomposition (DMD) in which Mori-Zwanzig memory kernels are included into the associated companion matrix. In the code we would like to release, we apply MZMD to a flow over a cylinder with Reynolds number 100 rather than the much larger data set used in the associated manuscript. DMD is used extensively in the fluid dynamics community mainly for extracting large scale spatio-temporal structures (patters) from flow data. This is useful for understanding the key mechanisms that generate certain complex dynamical process relevant in engineering design. In MZMD, we improve upon DMD by adding the Mori-Zwanzig memory kernels, and show this improvement is especially important in strongly nonlinear regions of the flow.

Woodward, Michael↗

DOE OSTI2025

An Educational Guide for 2D Stellar Structure Calculations of Rapidly Rotating Stars using the ESTER code

The Evolution STEllaire en Rotation (ESTER) code is the first 2D stellar structure code to be made open-source and freely available to the astronomy and astrophysics community. An important and novel advancement of this code is that it can reproduce the distorted shape and observable signatures (e.g., gravity darkening) of rapidly rotating stars. ESTER also calculates the steady-state large-scale flows within the star, namely their differential rotation and associated meridional circulation. In this report, we explore and document the physics implemented within version 1.1.0rc2 of the ESTER code, in a way that complements published descriptions. We illustrate this physics by plotting how stellar structure parameters vary through stellar interiors at a range of latitudes and at different angular velocities. We investigate how the thin convective envelopes of intermediate mass stars vary with latitude when rapidly rotating, becoming deeper and thicker near the equator. Simple comparisons of ESTER model predictions (e.g., central temperature and density, luminosity) with the output from the Modules for Experiments in Stellar Astrophysics (MESA) code [Paxton et al., 2010] shows generally good agreement. Additional comparisons provide important benchmarking and verification for ESTER as a comparatively young code. Finally, we provide a guide for installing and running the code on our local university cluster, aimed at helping students to begin work.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Pseudoatom molecular dynamics plasma microfields

Spectral lines are powerful diagnostic tools for both laboratory and astrophysical plasmas, as their shape is sensitive to the plasma environment. The low-frequency component of the electric microfield is an important input for semi-analytic line broadening codes. Here, in this paper, we detail a new method of calculating plasma microfields using configuration-resolved pseudoatom molecular dynamics. This approach accounts for both quantum atomic structure and N-body effects, similar to density functional theory molecular dynamics, but with less computational cost. We present pseudoatom microfields at plasma conditions relevant for recent high energy density laboratory astrophysics experiments conducted at the Sandia Z-Machine, National Ignition Facility, and Linac Coherent Light Source. Compared to established microfield codes we find moderate deviations at solid density conditions and strong agreement at lower plasma densities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Polarized Deep-Inelastic Scattering with Spin Correlations in Herwig 7

This repository is the research software and reproducibility companion for the HerwigPol polarized deep-inelastic scattering implementation developed for Herwig 7. It brings together the modified Herwig and ThePEG source snapshots, the curated POLDIS fixed-order reference code, the custom Rivet analyses, the DIS validation workflow, and the paper source in a single formal repository layout. The repository is intended to preserve the source-level ingredients needed to rebuild and re-run the validated DIS studies. It therefore tracks code, input cards, workflow drivers, and technical notes, while intentionally excluding generated artifacts such as build products, campaign outputs, merged YODA files, plots, and rendered paper outputs.

Papaefstathioou, Andreas [Kennesaw State Universit↗

DOE OSTI2026

Collision Tracking in OpenMC: Methods and Applications in Neutron Noise, Neutron Imaging, Time-of-Flight, and Multiplicity Counting

We present the development and application of a collision tracking feature within the OpenMC Monte Carlo particle transport code, designed for diverse applications such as neutron spectroscopy, scatter camera system, neutron noise, and multiplicity counting simulations. This feature enables the tracking of individual particle collisions, with potential applications in nuclear nonproliferation, reactor physics, and nuclear security. Additionally, the feature holds potential for the calibration of neutron detectors, specifically in converting light output into energy deposited within the detectors. The implementation consists of a set of filters—such as reaction type, energy, cell, and material—that constrain the set of collisions that are tracked, extensions to the Python API to enable simple input specification, and support for writing either OpenMC’s native HDF5-based format or the Monte Carlo particle list format. This feature was added to the official OpenMC release in version 0.15.3. In this work, the feature will be applied to showcase scenarios such as time-of-flight simulations, scatter-camera imaging for neutron source localization, neutron-noise analysis to extract integral kinetic parameters such as the prompt decay constant α, and multiplicity counting to estimate the mass of special nuclear materials. Ultimately, this feature aims to expand the application scope of open-source Monte Carlo particle transport codes such as OpenMC.

Monte Carlo code↗

DOE OSTI2025

GPU-accelerated kinetic Hall thruster simulations in WarpX

Abstract Two-dimensional (axial-azimuthal) simulations of a Hall thruster are performed using the open-source particle-in-cell code WarpX. The simulation conditions are chosen to match those of the axial-azimuthal benchmark first reported by Charoy et al. in 2019. A range of numerical and solver parameters is investigated in order to find those which yield the best performance. It is found that WarpX completes the benchmark case in 3.8 days on an Nvidia V100 GPU, and in as low as 1.5 days on a more recent Nvidia H100 GPU. Of the numerical parameters investigated, it is determined that the field-solve tolerance and particle resampling thresholds have the largest effect on the simulation wall time and that particle resampling may artificially widen electron velocity distribution functions, leading to unphysical heating. A semi-implicit scheme for the electrostatic field solve is tested and is found to produce results consistent to within 10% of the benchmark in less than twelve hours. The scaling properties of the electrostatic solver to multiple GPUs are also assessed on a uniform plasma test problem. The results of this work are discussed in the context of advancements in GPU hardware and the suitability of kinetic Hall thruster simulations for engineering applications.

Marks, Thomas A.↗

DOE OSTI2025

Direct sensitivity analysis on the parameterization of crystal plasticity models

Various methods for calibrating crystal plasticity finite element (CPFE) models lead to non-unique input parameter values, which subsequently introduce uncertainty in the predicted mechanical response. Sensitivity analysis (SA) conducted on crystal plasticity models is used to identify how variability in these parameters contribute to output uncertainty. Traditional SA on CPFE parameters uses simplified surrogate models to save computational time. However, the accuracy of the surrogate models depends on the quantity of training data used, and any modeling error can propagate into the SA results, potentially affecting their reliability. In this work, the elementary effects test (EET) method, a global SA technique using direct CPFE simulations was employed, and the results obtained were compared with the First Order Second Moment (FOSM) method. ExaConstit, an open-source GPU-enabled CPFE code, was used to perform the simulations and direct SA. The EET method was accurately able to capture the non-linear effects of all the input parameters on the output and is a valuable approach for reliably attributing parameter sensitivities in CPFE models. Based on the results, efficient strategies to perform future parameter calibration and SA are discussed. Additionally, the SA trends observed in different single crystal orientations closely mirrored the activity of the slip systems.

Elementary Effects Test↗

DOE OSTI2026

AstraAI v1

AstraAI is an open-source, structure-aware AI coding agent designed for large scientific and DOE-HPC codebases such as AMReX-based applications. Unlike general-purpose coding assistants, AstraAI combines retrieval-augmented generation (RAG) with compiler-level Abstract Syntax Tree (AST) analysis to perform precise, scope-constrained code modifications. It identifies exact function spans, enforces locality of edits, and maintains cross-file invariants, enabling deterministic and build-safe transformations in complex C++/GPU environments. AstraAI is intended for developers working on large, evolving HPC frameworks where correctness, reproducibility, and structural integrity are critical. Typical use cases include modifying physics kernels, updating GPU device lambdas, and performing multi-file refactors without breaking compilation or runtime semantics. Compared to conventional LLM-based coding agents - even those with repository access - AstraAI provides structural guarantees rather than free-form text patches. It minimizes unintended diffs, prevents scope drift, preserves formatting and build stability, and reduces structural hallucinations. By integrating compiler tooling directly into the generation loop, AstraAI transforms AI-assisted coding from probabilistic text editing into deterministic, structure-preserving program transformation suitable for mission-critical scientific software.

Natarajan, Mahesh [Lawrence Berkeley National Labo↗

DOE OSTI2024

Integrating ytopt and libEnsemble to autotune OpenMC

Ytopt is a Python machine-learning-based autotuning software package developed within the ECP PROTEAS-TUNE project. The ytopt software adopts an asynchronous search framework that consists of sampling a small number of input parameter configurations and progressively fitting a surrogate model over the input-output space until exhausting the user-defined maximum number of evaluations or the wall-clock time. libEnsemble is a Python toolkit for coordinating workflows of asynchronous and dynamic ensembles of calculations across massively parallel resources developed within the ECP PETSc/TAO project. libEnsemble helps users take advantage of massively parallel resources to solve design, decision, and inference problems and expands the class of problems that can benefit from increased parallelism. In this paper we present our methodology and framework to integrate ytopt and libEnsemble to take advantage of massively parallel resources to accelerate the autotuning process. Specifically, we focus on using the proposed framework to autotune the ECP ExaSMR application OpenMC, an open source Monte Carlo particle transport code. OpenMC has seven tunable parameters some of which have large ranges such as the number of particles in-flight, which is in the range of 100,000 to 8 million, with its default setting of 1 million. Setting the proper combination of these parameter values to achieve the best performance is extremely time-consuming. Therefore, we apply the proposed framework to autotune the MPI/OpenMP offload version of OpenMC based on a user-defined metric such as the figure of merit (FoM) (particles/s) or energy efficiency energy-delay product (EDP) on Crusher at Oak Ridge Leadership Computing Facility. In conclusion, the experimental results show that we achieve the improvement up to 29.49% in FoM and up to 30.44% in EDP.

Autotuning↗

DOE OSTI2026

Modeling The Nucleosynthetic Imprint of Stellar Merger Phenomena - Final Technical Report

This DOE CAREER project developed a comprehensive, multi-physics framework for modeling stellar mergers and their observable consequences. The work successfully integrated analytical models, three-dimensional hydrodynamic simulations, stellar evolution calculations, nucleosynthesis, and radiation transport into a unified pipeline. Key scientific advances include demonstrating stellar mergers as a unifying explanation for systems such as Betelgeuse and R Coronae Borealis stars, quantifying merger-driven chemical signatures, and establishing the connection between merger physics and circumstellar environments. A major outcome of the project is the development of SuperLite, an open-source Monte Carlo radiation transport code that enables the generation of synthetic spectra for astrophysical transients. This work bridges dynamical, thermal, and radiative timescales and provides a powerful, DOE-relevant computational framework for interpreting observations of supernovae and related transient phenomena, while also contributing to workforce development through the training of postdoctoral researchers and graduate students.

Chatzopoulos, Emmanouil [Louisiana State Universit↗

DOE OSTI2024

Lambda-PFLOTRAN 1.0: a workflow for incorporating organic matter chemistry informed by ultra high resolution mass spectrometry into biogeochemical modeling

Abstract. Organic matter (OM) composition plays a central role in microbial respiration of dissolved organic matter and subsequent biogeochemical reactions. Here, a direct connection of organic matter chemistry and thermodynamics to reactive transport simulators has been achieved through the newly developed Lambda-PFLOTRAN workflow tool that succinctly incorporates carbon chemistry data generated from Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) into reaction networks to simulate organic matter degradation and the resulting biogeochemistry. Lambda-PFLOTRAN is a Python-based workflow, executed through a Jupyter notebook interface, that digests raw FTICR-MS data, develops a representative reaction network based on substrate-explicit thermodynamic modeling (also termed lambda modeling due to its key thermodynamic parameter λ used therein), and completes a biogeochemical simulation with the open source, reactive flow and transport code PFLOTRAN. The workflow consists of the following five steps: configuration, thermodynamic (lambda) analysis, sensitivity analysis, parameter estimation, and simulation output and visualization. Two test cases are provided to demonstrate the functionality of the Lambda-PFLOTRAN workflow. The first test case uses laboratory incubation data of temporal oxygen depletion to fit lambda parameters (i.e., maximum utilization rate and microbial carrying capacity). A slightly more complex second test case fits multiple lambda formulation and soil organic matter release parameters to temporal greenhouse gas generation measured during a soil incubation. Overall, the Lambda-PFLOTRAN workflow facilitates upscaling by using molecular-scale characterization to inform biogeochemical processes occurring at larger scales.

58 GEOSCIENCES↗

DOE OSTI2026

ACDC (Automated Campbell Diagram Code) [SWR-26-042]

This application provides a web-based graphical user interface to generating Campbell Diagrams and visualizing mode shapes for OpenFAST turbine models. Determining the aeroelastic stability and dynamic characteristics of wind turbines is a critical step in turbine design and analysis. Historically, extracting natural frequencies and mode shapes from OpenFAST—the industry-standard whole-turbine simulation code—has been a fragmented and tedious process. It required manual model configuration, command-line linearization execution, and complex post-processing via proprietary scripts to handle rotating-frame dynamics. To address these workflow bottlenecks, we present the Automated Campbell Diagram Code (ACDC), an open-source graphical software tool developed by the National Laboratory of the Rockies (NLR) under the DOE-funded Distributed Wind Aeroelastic Modeling (dWAM) project. ACDC streamlines the end-to-end linearization and stability analysis workflow into a single, intuitive cross-platform application. The software guides users through OpenFAST model configuration, definition of operating points, and the automated execution of steady-state trim and linearization simulations. Under the hood, ACDC automates the complex mathematical post-processing steps required for rotating systems, including Multi-Blade Coordinate (MBC) transformations, eigenanalysis, and advanced modal tracking utilizing the Modal Assurance Criterion (MAC) and spectral clustering. Finally, ACDC processes these results to automatically generate Campbell diagrams and features a robust 3D visualization engine to animate full-system mode shapes. By eliminating the reliance on external post-processing environments and manual data manipulation, ACDC significantly accelerates dynamic analysis and lowers the barrier to entry for wind energy researchers and engineers.

Summerville, Brent [National Laboratory of the Roc↗

DOE OSTI2024

Accelerating Thermochemical Equilibrium Calculations for Nuclear Reactor Applications

Thermochemical properties play a key role in modeling and simulation of several key phenomena in nuclear reactors. There has been an increasing interest in incorporating CALPHAD-based formulations in multiphysics simulations including for Molten Salt Reactors where knowledge of phase evolution of the salt and the chemical potentials of various elements are of utmost importance in source term analyses and redox control. However, the size of such simulations is often limited by the high computational cost of full thermodynamic equilibrium calculations. This work discusses the current efforts aimed at accelerating thermochemical equilibrium calculations for multiphysics simulations performed using the open-source finite element / finite volume code Multiphysics Object Oriented Simulation Environment (MOOSE) [1]. While several methods have been proposed for accelerating phase equilibrium calculations [2], most focus on relatively small systems and often rely on a- priori knowledge of the state-space of the system. Nuclear materials, however, are often multi-component systems owing to the evolution of composition under irradiation and an approach based on a-priori mapping of phase diagram is often not enough. This work is aimed at demonstrating an on-the-fly surrogate modeling framework that uses active learning to reduce the number of full equilibrium calculations that must be performed. By combining with efficient coupling approaches, the surrogate framework helps in reducing the computational cost of thermodynamic equilibrium informed multiphysics simulations of nuclear materials. The performance is benchmarked against full coupling with the thermochemistry library Thermochimica [3]. This work uses a machine learning based approach for constructing surrogate models to predict the stable phases in a multicomponent system. The surrogates were constructed using neural networks and Gaussian process classification. In this work, we compare the relative performance of the two methods. We also demonstrate the use of caching previous calculations by interpolating the values from nearest neighbors. References [1] Lindsay, A.D., et al. "2.0 – MOOSE: Enabling massively parallel multiphysics simulation", SoftwareX, 20 (2022): 101202. [2] Roos, W.A. and Zietsman J.H. "Accelerating complex chemical equilibrium calculations – A Review", Calphad, 77 (2022): 102380. [3] Piro, M.H.A., et al. "The thermochemistry library Thermochimica", Computational Materials Science, 67 (2013): 266-272.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Fusion Neutron Generator

The proposed code, named FROG (Fusion neutron Generator) is built upon the open-source particle transport Monte Carlo toolkit Geant4. Geant4 provides C++ classes that can be leveraged to build application-specific codes dealing with the transport of particles through matter. Geant4-based codes are applied in high-energy particle physics experiments, medical applications, shielding, and space applications for example. The FROG code allows the user to define the geometry of a neutron converter device shaped as a hollow cylinder, where a neutron breeding material such as lithium deuteride (LiD) is cladded by two concentric cylinders. Such neutron converter is then placed inside a regular nuclear fission reactor, where thermal neutrons will react with the neutron breeder material (typically, Lithium 6), and through a series of reactions, will generate high-energy neutrons – neutrons whose kinetic energy are around 14 MeV. The hollowed central portion can hold a specimen that will be bombarded by high-energy neutrons created inside the neutron breeding material. Figuratively speaking, this type of device transforms neutrons from thermal (~0.625 eV) to fusion (~14 MeV) energies and is sometimes termed “fusion-to-thermal neutron converters” in the literature. The code consists of C++ source file compiled and linked to generate an executable. The user can select the dimensions of the converter (radius, length, and thickness of the breeder material), the breeder material type, the cladding material, and the specimen material that will be activated or irradiated. As input, the neutron flux for a specific location inside a reactor, for instance, positions in ATR, is required. As output, the code predicts the number of high-energy neutrons produced, the total neutron flux and fluence as well as its detailed spectrum. The physics involved in such device is very complex, as it requires modeling neutron transport, light-ion (tritons) transport, as well as fusion reactions. The Geant4 toolkit provides the required physical models.

Martin, NicholasP. [Idaho National Laboratory (INL↗