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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Post-irradiation Heating Tests of As-Irradiated AGR-3/4 TRISO Fuel Compacts

Four post-irradiation heating tests of fuel compacts from the U.S. Advanced Gas Reactor (AGR)-3/4 irradiation experiment were completed. In addition to tristructural isotropic (TRISO)-coated driver fuel, each compact contained designed-to-fail (DTF) particles with fuel kernels coated only in pyrocarbon so as to simulate exposed kernels. Tests at 1600/1700°C, 1400°C, and 1200°C were performed to measure fission product release as a function of time and temperature. Silver release was highest in the 1200°C test, supporting the observation that silver release rates are highest in the 1100–1300°C range. Compared to tests of AGR-1 compacts with no exposed kernels, the Cs-134 and Kr-85 releases were noticeably higher in AGR-3/4. The exposed kernels’ contributions to Eu and Sr release are inconclusive, due to the difficulty in distinguishing among the combined effects of higher irradiation temperatures in these particular AGR-3/4 compacts, the presence of the DTF particles, and the Fuel Accident Condition Simulator (FACS) test temperatures. These data can be used to make inferences about fission product retention in exposed kernels as a function of time and temperature.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

In situ multi-tier auto-ignition detection applied to dual-fuel combustion simulations

Here we use an anomaly detection methodology that is centered on analyzing fourth-order joint moments (co-kurtosis), particularly focusing on its application in auto-ignition of combustion problems with large numbers of species. Unsupervised anomaly detection is challenging to generalize across problem types and domains. A recent technique, centered on analyzing information in the fourth-order joint moment co-kurtosis, has shown promise, especially for high-dimensional scientific data. In this work we present developments to the co-kurtosis based anomaly detection method needed to make it effective and scalable for large-scale distributed scientific data, such as those generated by massively parallel simulations. An in situ co-kurtosis algorithm is employed as the anomaly detection method for identifying ignition kernels in simulations of turbulent combustion. Here, we extend an existing methodology which identifies regions of the domain where anomalies are present, and add another tier of anomaly detection where the individual samples contributing to the anomaly are identified. We apply this algorithm on-the-fly to a variety of turbulent reacting flow problems and compare it to the widely used (but significantly more expensive) chemical explosive mode analysis (CEMA). We demonstrate the ability of the method to detect and identify the onset of low and high temperature ignition which can be used for computational steering, as chemical and combustion anomalies occur intermittently at spatio-temporal locations unknown a priori. Finally, we apply our lightweight in situ algorithm to an exascale high-fidelity simulation with a total of 2.4 Trillion degrees of freedom, performed using an adaptive mesh refinement solver. Furthermore, through a scalability analysis, we show that the relative computational cost of this in-situ anomaly detection algorithm compared to an iteration of the reacting flow solver is negligible.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Influence of neutrino-electron scattering and neutrino-pair annihilation on hypermassive neutron star

Here, we investigate the influence of inelastic neutrino microphysics in general-relativistic magnetohydrodynamics simulations of a hypermassive neutron star. In particular, we include species/energy groups coupled neutrino-matter interactions, such as inelastic neutrino-electron scattering and electron-positron annihilation kernels, into simulations up to 50 ms. Neutrino-electron inelastic scattering is known to have effective neutrino-matter energy exchange. We show that, with neutrino-electron inelastic scattering, simulations predict 75% higher disc mass with slightly different mass-averaged compositions, and 18% more ejected mass with similar distributions. The enhancement of the mass of the disc and the ejecta results in stronger baryon pollution, leading to less favorable jet launching environments. Furthermore, neutrino luminosities are about 50%, 40%, and 30% higher for electron neutrino, electron antineutrino, and heavy-lepton neutrinos. In contrast, we do not see any significant impacts due to electron-positron annihilation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

HPCReact

HPCReact is a library that contains functions to assist in the creation of portable computational kernels to simulate the evolution of chemical processes.

Settgast, RandolphR [Lawrence Livermore National L↗
DOE OSTI2025

The total neutron cross section of liquid and solid ammonia

Ammonia is a material of interest for future neutron moderators at high-power sources due to its high hydrogen density, low melting point, and resistance to polymerization in an intense radiation field. Its performance in such applications cannot currently be calculated due to the absence of suitable computer models for the interaction of neutrons with ammonia under relevant conditions. In an effort to develop suitable scattering kernels for computer simulations of moderator performance, we have conducted a series of Density Functional Theory and Molecular Dynamics calculations of the molecular-level thermal properties of ammonia at various temperatures within both the solid and liquid phases. In this paper, we compare computer calculations for the energy-dependent total neutron cross section of ammonia, based on these models, to experimental measurements of those cross sections at temperatures of 221 K, 180 K, and 35 K. The experimental data were collected over an energy range from 0.1 meV to 10 eV using time-of-flight techniques at the Low Energy Neutron Source (LENS) facility at Indiana University. This comparison provides a first validation in the development of thermal scattering libraries for Monte Carlo source design simulations based on liquid and solid ammonia. In conclusion, we also provide some insights into where additional development of tools for creating such models may be needed.

Ammonia↗
DOE OSTI2024

FY24 Mole Development Updates and SAM-Mole Coupling for MSR Species Transport Applications

In this report, a new coupling strategy linking Mole to SAM is demonstrated where SAM is used to drive the solution and Mole is used primarily as a library for mass transport coefficient models. Groundwork is laid to transition Mole into a harbor for various mass transfer coefficient models, which generally take the form of scalar, auxiliary Multiphysics Object-Oriented Simulation Environment (MOOSE) kernels. It is envisioned that these models will be agnostic to the spatial discretization scheme and can be used across the MOOSE ecosystem, providing a centralized library for certain mass transfer coefficients to MOOSE codes that must account for liquid-to-vapor and vapor-to-liquid mass transport phenomena for both high-volatility and low-volatility species.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Post-irradiation 1600°C Heating Test of AGR-1 UCO Fuel Kernels

Five bare kernels were selected from the U.S. Advanced Gas Reactor (AGR) 1 irradiation experiment Compact 5-3-1 to perform post-irradiation safety tests. The safety test involved heating the kernels in the Fuel Accident Condition Simulator (FACS) furnace in the inert atmosphere to a peak temperature of 1600°C and isothermally holding at this temperature for about 47 hours while collecting fission products released. This test was to assess the retention of fission products in bare kernels without the effects of the other TRISO layers (buffer, IPyC, SiC, and OPyC) or the graphitic matrix material. The bare kernels released nearly 100% of cesium and antimony, while they were able to maintain about 30% of europium, 50% of strontium, and the majority of cerium and ruthenium. In addition, about 48% of the calculated inventory of Kr-85 released during the test, indicating that kernels were capable of retaining a considerable fraction of fission gas K-85 during irradiation.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Physics and Components syntax to enable a systems-based approach to multiphysics

Simulations in MOOSE have traditionally used kernel and boundary condition classes to describe the equations. Downstream applications leveraged a system called Actions to define a pre-packaged discretization of the equations they solve. Unfortunately, the Action base class was very limited, and most applications implemented the same concepts in their Actions. This led to an increased maintenance burden and a reduction in coupling opportunities, save for the use of MultiApps which renders each input mostly independent. With the introduction of multi-system capabilities in MOOSE, there is growing interest in defining entire simulations of complex multiphysics systems in a single input file. By introducing a new Physics system, with its dedicated syntax and a new base class providing wide-ranging capabilities, we are now able to define multiple equations in a single input file in a compact and user-friendly way. With new interactions between Physics and the Component system, these equations can be defined on each component of a complex system. In this talk, we will present the capabilities of these new systems, their interactions, and how to define complex systems multiphysics simulations with Physics and Components.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

DNS of ignition and flame stabilization in a simplified gas turbine premixer

With the increasing need for fuel flexibility, mitigation of auto-ignition (AI) inside gas turbine (GT) premixers becomes crucial. They must be designed to yield a sufficiently homogeneous fuel-air mixture to achieve low emissions while at the same time avoiding the occurrence of AI and subsequent flame stabilization. This challenge requires a detailed understanding of turbulent mixing and chemistry interactions. In the present work, a direct numerical simulation (DNS) of an array of jets in crossflow (JICF), representative of an industrial GT premixer, is reported to shed light on these complex phenomena. It is found that AI kernels form in the aft part of the premixer and coalesce into a flame front that then propagates upstream, mainly through the boundary layer, and successively engulfs the jets. This, therefore, suggests a significant role of the jet array pattern on the flame stabilization. It is noted that AI kernels continue to form independently during the whole time of the simulation. To clarify the contribution of AI and diffusion in the ignition kernels and the main flame, chemical explosive mode analysis (CEMA) is employed jointly with a kernel tracking algorithm. It is found that during the initial formation of the flame, many ignition kernels form in mixtures with low scalar dissipation rate and large contribution from AI mode. As they quickly grow, they merge into a single flame front that becomes increasingly more diffusion-assisted over time, balancing the AI mode. Turbulence is shown to have a significant enhancing effect in lean premixed flames, but further analysis is required to fully characterize it. These findings are relevant for the industrial premixer studied, and also for novel micromix concepts that may be used in the next generation of GT combustion systems.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Inverse Mapping of the Collision Kernel and Wall Flux Scaling in a Tall Convection‐Cloud Chamber Using Local Sensors and Knowledge‐Informed Deep Learning

Droplet collision–coalescence is a crucial process in cloud physics, but accurately representing this process under different dynamical conditions remains challenging. A proposed future convective‐cloud chamber aims to investigate this key process, but the method for observing it remains unclear, even though it is theoretically established that collision‐coalescence will occur. This study serves as a proof‐of‐concept demonstration of how knowledge‐informed deep learning, combined with measurement data from local sensors in the chamber, can be used to estimate the collision kernels, which determine how the droplet size distribution evolves during collision‐coalescence. In addition to estimating the collision kernel, we also address wall fluxes, another uncertain but important process that acts as a source of heat and moisture in the chamber. Ensemble runs of large‐eddy simulations are conducted by scaling the wall fluxes and the collision kernel, while the measured flow and cloud properties are used as inputs for a neural network. Results indicate that this approach successfully maps the scaling of wall fluxes and the collision kernel with biases of approximately 1% or less relative to the range of the target data. This proof‐of‐concept lays the groundwork for future applications; when the real measurements are available, real sensor data combined with the trained model presented in this work will enable estimation of the actual wall fluxes and collision kernel.

cloud chamber↗
DOE OSTI2025

On nonlocal problems with Neumann boundary conditions: scaling and convergence for nonlocal operators and solutions

Formulations of Neumann-type boundary conditions for boundary value problems in the nonlocal framework are beset with difficulties, some related to the choice of a proper scaling. Here we identify a space-dependent scaling for a nonlocal Neumann operator, for which we prove linear in δ (δ being the radius for the support for the kernel) convergence of the Neumann operator and $\mathcal{O}$(δ 2 ) convergence of solutions to their classical counterparts. The pointwise-like convergence of the nonlocal normal operator is cast as a new type of two-scale operator-point convergence, which we call condensated convergence . The results hold for general integrable kernels, a setting which is favored in numerical simulations. We support this analysis with numerical convergence studies using a piecewise linear discontinuous Galerkin discretization and show an $\mathcal{O}$(δ 2 ) rate of convergence of solutions, also exhibiting an $\mathcal{O}$(h 2 ) convergence, where h is the mesh size.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

"Source Term Modeling for Advanced Gas Micro-Reactors"

Maintaining the safety of the public, environment, and operating personnel is the most important factor in designing, operating, maintaining, and decommissioning nuclear reactors. In recent years, there has been a growing interest in the development of micro-reactors employing TRi-structural ISOtropic (TRISO)-coated particle fuel. In gas reactors, TRISO fuel plays an important role in the safety case for high temperature reactors because of the fission product retention properties of the fuel. This ability enables the use of a functional containment strategy for the reactor where multiple barriers are used to prevent fission product release to the environment. Part of the safety analysis of these advanced reactors is the assessment of radionuclide releases under normal and accident conditions through the multiple credited safety barriers. Using conservative assumptions, a mechanistic analysis can be performed to quantify these releases that combines the probabilistic assessment of failure with analytic solutions to radionuclide transport equations. Source term modeling for TRISO fuel has been performed for previous reactor designs; however, these models are outdated, in many cases proprietary, and need updates to be applied to the current state of TRISO fuel technology and alternative gas reactor core configurations [1]. Currently, the only publicly available source term assessment for gas reactors is an expert-based Monte Carlo simulation based on the effectiveness of the fuel kernel, coating layers, and graphite block in a modular high temperature gas reactor [2]. Thus, there is a need to develop a simple, versatile, and mechanistic model of fission product release and transport in gas reactor cores that could be applied to a variety of reactors through user inputs and reactor-specific radionuclide inventories. The release is calculated by the diffusion of the key safety important fission products through the kernel, silicon carbide (SiC), graphite for both intact and defective TRISO particles based on fuel and graphite temperatures in the reactor under normal operation. These releases from the fuel enter the coolant where they can plate-out on cooler surfaces. A clean-up model is included for designs with a coolant purification system to remove fission gases. This initial distribution of fission products in the reactor serves as an initial condition for potential releases under postulated accident conditions. The model then can calculate the fission product release for any transient temperature profile and fission product releases can then be used to assess radiological dose to the workers and the public using conventional dose tools. Data on the diffusion of fission products is based on historic German TRISO experiments and the more current Department of Energy (DOE) Advanced Gas Reactor (AGR) TRISO fuel development program. The model is coded in python with inputs and outputs in excel spreadsheets, as well as python plotting utilities to aid in the interpretation of the results. References: [1] INL, NGNP Mechanistic Source Term White Paper, INL-10-17997, July 2010. [2] David A. Petti, Richard R. Hobbins, Peter Lowry, Hans Gougar, “Representative Source Terms and The Influence of Reactor Attributes on Functional Containment in Modular High Temperature Gas-cooled Reactors,” Nuclear Technology, Vol. 184, p. 181-197, Nov. 2013.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2025

Assessment of buffer-IPyC thermomechanical debonding behavior using new experimental strength data in BISON

TRIstructural ISOtropic (TRISO) fuel is a nuclear fuel commonly used in High Temperature Gas-cooled Reactors (HTGRs). A single sub-millimeter-diameter TRISO fuel particle consists of a spherical fuel kernel surrounded by four coating layers: a low-density pyrocarbon buffer layer, an inner pyrolytic carbon (IPyC) layer, a silicon carbide (SiC) layer, and an outer pyrolytic carbon (OPyC) layer. The kernel is commonly made of UO2 or a mixture of uranium carbide and uranium oxide (UCO). During reactor operation, the TRISO coating layers are subjected to irradiation-induced dimensional changes and the associated thermomechanical behavior of each layer. One of the observed behaviors is gap formation between the buffer and IPyC layer due to the porous buffer’s irradiation-induced shrinkage exceeding that of the IPyC layer. Not all irradiated particles will experience buffer-IPyC gap formation. The debonding may be partial, or it may be nearly total. However, from post-irradiation examination of UCO TRISO fuels irradiated as part of the Advanced Gas Reactor (AGR) Fuel Development and Qualification Program, it was concluded that partial buffer-IPyC debonding was the most common type of buffer-IPyC interaction. To predict TRISO thermomechanical performance, multi-physics models have been built that are being continually updated and refined. The BISON code is a finite element-based nuclear fuel performance code that may be used for 1D, 2D, and 3D TRISO particle simulations. This code is used to calculate fuel temperature, kernel swelling, buffer densification, thermal and irradiation creep, fracture, and fission gas production and release. One of the recent additions to the BISON code is the ability to model the process of layer debonding. This paper will focus on the simulation results of the improved BISON debonding model that will utilize updated strengths measured from irradiated AGR TRISO fuel particles. The new experimental strength data from micromechanical tests of irradiated TRISO fuel samples were exercised in the BISON simulations and compared to baseline strength data to assess their applicability in the models. This also includes updated buffer-IPyC bond strengths to simulate layer delamination. Based on current experimental observations it is noted that the buffer-IPyC separation occurs not exactly at the junction of these two layers, but more on the side of the buffer layer. That observation is also implemented in the TRISO interface debonding model. This improved modeling approach using experimental strength data to characterize buffer-IPyC debonding and its potential subsequent cracking will be presented in the paper along with comparisons to available experimental observations.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Improved Weld Residual Stress Modeling System in BlackBear

This report presents enhancements to the MOOSE-based BlackBear application aimed at improving its capability to simulate welding and other thermo-mechanical manufacturing processes. Two primary avenues of improvement are pursued. First, to enhance user accessibility, we introduce a centralized default block restriction mechanism that ensures coverage checks are performed within user-specified default blocks. This default setting is applied consistently to all block-describable objects, such as variables, kernels, and more. In addition, we develop a modular action for moving heat source simulations, which integrates path file parsing, subdomain modification, and heat source kernel enforcement into a single, streamlined configuration. Second, to improve solver robustness, we implement an alternative method for assigning initial conditions to the updated active domain during the simulation, thereby enhancing convergence behavior. To validate the framework, we design and conduct several benchmark simulations, including heat conduction with progressive material addition, linear elasticity with time-dependent material deposition, and viscoplasticity model with isotropic hardening under similar conditions. Finally, we demonstrate the effectiveness of the proposed framework through large-scale thermo-mechanical welding simulations in both two and three dimensions.

42 ENGINEERING↗
DOE OSTI2025

Accelerating magnonic simulations with the pseudospectral Landau-Lifshitz equation

The pseudospectral Landau-Lifshitz (PS-LL) model can describe atomic-scale magnetic exchange interactions within a continuum framework. This is achieved by employing a convolution kernel that models the nonlocal interaction in a grid-independent manner. Even though the PS-LL was originally introduced to address atomic exchange, any nonlocal kernel can be modeled. In the field of magnonics, the dipole field is fundamental to describe the dispersion relation of magnons, the quasiparticle representation of angular momentum. Because dipole-dipole interactions are long-range, numerical approaches typically rely on convolutions. Here, we demonstrate that the PS-LL model can be used to perform magnonic simulations with a single convolution kernel derived from analytical solutions. We demonstrate a twofold increase in computational speed compared with the full dipole calculation. This approach is valid insofar as the excitations are linear, which is typically the case for magnons. Our results have the potential to accelerate magnonic research, particularly for the inverse design method, where several simulations must be performed to achieve the desired outcome.

Mathematics and computing↗
DOE OSTI2024

GPU Accelerated Sparse Cholesky Factorization

The solution of sparse symmetric positive definite linear systems is an important computational kernel in large-scale scientific and engineering modeling and simulation. We will solve the linear systems using a direct method, in which a Cholesky factorization of the coefficient matrix is performed using a right-looking approach and the resulting triangular factors are used to compute the solution. Sparse Cholesky factorization is compute intensive. In this work we investigate techniques for reducing the factorization time in sparse Cholesky factorization by offloading some of the dense matrix operations on a GPU. We will describe the techniques we have considered. We achieved up to 4x speedup compared to the CPU-only version.

Karsavuran, M Ozan↗