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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 235 records · Page 13

Predicting Large Deflections of Multiplate Fuel Elements Using a Monolithic FSI Approach

As part of the Global Threat Reduction Initiative, the Oak Ridge National Laboratory is evaluating conversion of fuel for the High Flux Isotope Reactor (HFIR) from high-enriched uranium to low-enriched uranium. Currently, multiphysics simulations that model fluid-structure interaction phenomena are being performed to ensure the safety of the reactor with the new fuel type. A monolithic solver that fully couples fluid and structural dynamics is used to model deflections in the new design. A classical experiment is chosen to validate the capabilities of the current solver and the method. Here, a single-plate simulation with various boundary conditions as well as a five-plate simulation are presented. Finally, use of the monolithic solver provides stable solutions for the large deflections and the tight coupling of the fluid and structure and the maximum deflections are captured accurately.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Multiphysics Analyses of the Protected and Unprotected Loss of Forced Cooling Accidents in the HTR-PM

Here, we present the multiphysics simulation results for the protected pressurized and depressurized loss of forced cooling (PLOFC and DLOFC) events in the High-Temperature gas-cooled Reactor--Pebble-bed Module (HTR-PM) equilibrium core using the Griffin-Pronghorn coupled code system. Additionally, this paper discusses the strategy for estimating the spontaneous fission neutron source needed for unprotected events and re-criticality calculations. The solutions of the protected PLOFC and DLOFC events were verified against similar solutions obtained for temperature evolutions from the open literature. Both the average and maximum pebble surface temperatures behaved as expected during the DLOFC and remained below 1800 K. The PLOFC results are highly dependent on the ability to resolve the natural circulation in the core, which is impacted by the mesh resolution in Pronghorn. Furthermore, we present the results of the unprotected DLOFC transient to predict the timing of the re-criticality event, which occurred 47 hours after the onset of the transient, and the new steady-state power of 1.3 MW.

42 - ENGINEERING↗

Packaging Development for a 1200V SiC BiDFET Switch Using Highly Thermally Conductive Organic Epoxy Laminate

A novel 1.2 kV/10A, 4H-SiC monolithic, bidirectional switch has been developed for use in cycloconverter applications to facilitate high-frequency direct AC-to-AC power conversion and enables new power converter topologies. A new packaging solution, utilizing a 100 µm flexible polyimide organic laminate substrate is developed to mitigate thermo-mechanical stress during power cycling and enable smaller form factor and lower cost. Multiphysics simulations and static tests were conducted to show performance characterization of the module and compare it against metallic substrates. A new organic laminate epoxy resin composite dielectric (ERCD) is also evaluated for superior thermal performance and shows 63% reduction in junction to case resistance compared to DBC substrates.

Silicon Carbide, Bi-directional switch, BiDFET, MO↗

Thermal Analysis of a Polypropylene Capacitor for Resonant Tuning Networks in WPT Applications

This study presents the thermal analysis of polypropylene capacitors operating at high frequencies and high currents used in the resonant tuning networks for electric vehicle (EV) wireless charging systems. The thermal analysis and performance results of the CELEM polypropylene capacitors are presented at different currents for a polyphase wireless power transfer (WPT) system while the study can be expanded to other capacitors by different manufacturers. Thermal equivalent circuit of the capacitor is derived and required cold plate size and design calculations are conducted by modeling the polypropene capacitor in MATLAB. The polypropene capacitor's finite element analysis (FEA) model is developed using COMSOL Multiphysics simulation software, and the thermal characteristics and analysis of the capacitor are presented in this paper.

Aktas, Ahmet↗

Photovoltaic Material Characterization With Steady State and Transient Photoluminescence

Here, we develop an approach to characterize the surface and bulk properties for thin films of photovoltaic materials by combining two experimental photoluminescence (PL) techniques with one multiphysics simulation. This contactless, in-line characterization technique allows reliable extraction of key lifetime parameters. In this study, we first discuss the strengths and weaknesses of both steady-state and transient PL techniques (specifically, steady-state PL excitation spectroscopy and time-resolved PL) and show that combining them with numerical simulation can be used to extract surface and bulk lifetimes self consistently. The method is applied to InP thin films grown with a novel vapor– liquid–solid method. Lastly, the InP thin film tested is found to have a bulk Shockley–Read–Hall (SRH) lifetime of 12 ns and a front surface recombination velocity of 5 × 10 4 cm/s.

36 MATERIALS SCIENCE↗

SURROGATE MODEL DEVELOPMENT AND VALIDATION FOR RELIABILITY ANALYSIS OF REACTOR PRESSURE VESSELS

In nuclear light water reactors (LWRs), the reactor coolant, core and shroud are contained within a massive, thick walled steel vessel known as a reactor pressure vessel (RPV). Given the tremendous size of these structures, RPVs typically contain a large population of pre-existing flaws introduced in the manufacturing process. After many years of operation, irradiation-induced embrittlement makes these vessels increasingly susceptible to fracture initiation at the locations of the pre-existing flaws. Because of the uncertainty in the loading conditions, flaw characteristics and material properties, probabilistic methods are widely accepted and used in assessing RPV integrity. The Fracture Analysis of Vessels – Oak Ridge (FAVOR) computer program developed by researchers at Oak Ridge National Laboratory is widely used for this purpose. This program can be used in order to perform deterministic and probabilistic risk-informed analyses of the structural integrity of an RPV subjected to a range of thermal-hydraulic events. FAVOR uses a one-dimensional representation of the global response of the RPV, which is appropriate for the beltline region, which experiences the most embrittlement, and employs an influence coefficient technique to rapidly compute stress intensity factors for axis-aligned surface-breaking flaws. The Grizzly code is currently under development at Idaho National Laboratory (INL) to be used as a general multiphysics simulation tool to study a variety of degradation mechanisms in nuclear power plant components. The first application of Grizzly has been to study fracture in embrittled RPVs. Grizzly can be used to model the thermo-mechanical response of an RPV under transient conditions observed in a pressurized thermal shock (PTS) scenario. The global response of the vessel provides boundary conditions for local 3D models of the material in the vicinity of a flaw. Fracture domain integrals are computed to obtain stress intensity factors, which can in turn be used to assess whether a fracture would initiate at a pre-existing flaw. To use Grizzly for probabilistic analysis, it is necessary to have a way to rapidly evaluate stress intensity factors. To accomplish this goal, a reduced order model (ROM) has been developed to efficiently represent the behavior of a detailed 3D Grizzly model used to calculate fracture parameters. This approach uses the stress intensity factor influence coefficient method that has been used with great success in FAVOR. Instead of interpolating between tabulated solutions, as FAVOR does, the ROM approach uses a response surface methodology to compute fracture solutions based on a sampled set of results used to train the ROM. The main advantages of this approach are that the process of generating the training data can be fully automated, and the procedure can be readily used to consider more general flaw configurations. This paper demonstrates the procedure used to generate a ROM to rapidly compute stress intensity factors for axis-aligned flaws. The results from this procedure are in good agreement with those produced using the traditional influence coefficient interpolation procedure, which gives confidence in this method. This paves the way for applying this procedure for more general flaw configurations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

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

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

42 ENGINEERING↗

Two-Level Sketching Alternating Anderson Acceleration for Complex Physics Applications

We present a novel two-level sketching extension of the Alternating Anderson–Picard (AAP) method for accelerating fixed-point iterations in challenging single- and multiphysics simulations governed by discretized PDEs. Our approach combines a static, physics-based projection that reduces the least-squares (LS) problem to the most informative field (e.g., via Schur-complement insight) with a dynamic, algebraic sketching stage driven by a backward stability analysis under Lipschitz continuity. We introduce inexpensive estimators for stability thresholds and cache-aware randomized selection strategies to balance computational cost against memory access overhead. The resulting algorithm solves reduced LS systems in place, minimizes memory footprints, and seamlessly alternates between low-cost Picard updates and Anderson mixing. Implemented in Julia, our two-level sketching AAP achieves up to 50% time-to-solution reductions compared to standard Anderson acceleration—without degrading convergence rates—on benchmark problems including Stokes, 𝑝-Laplacian, bidomain, and Navier–Stokes formulations at varying problem sizes. These results demonstrate the method’s robustness, scalability, and potential for integration into high-performance scientific computing frameworks. Our implementation is available open source in the AAP.jl library.

Barnafi, Nicolas [University of Chile, Santiago]↗

Discovery of Probabilistic Dirichlet-to-Neumann Maps on Graphs

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

Dirichlet-to-Neumann map↗

Trilinos: Enabling Scientific Computing across Diverse Hardware Architectures at Scale

Trilinos is a community-developed, open-source software framework that facilitates building large-scale, complex, multiscale, multiphysics simulation code bases for scientific and engineering problems. Since the Trilinos framework has undergone substantial changes to support new applications and new hardware architectures, this document is an update to “An Overview of the Trilinos project” by Heroux et al. (ACM Transactions on Mathematical Software, 31(3):397–423, 2005). It describes the design of Trilinos, introduces its new organization in product areas, and highlights established and new features available in Trilinos. Particular focus is put on the modernized software stack based on the Kokkos ecosystem to deliver performance portability across heterogeneous hardware architectures. This article also outlines the organization of the Trilinos community and the contribution model to help onboard interested users and contributors.

Heterogeneous Hardware Architectures↗

Electrochemical Residence Time Distribution as a Diagnostic Tool for Redox Flow Batteries

The fluid dynamic and electrochemical performance of redox flow batteries (RFBs) stems from the relationship between the flow field and the porous electrode, whose interplay determines how active species move and react during device operation. While characterization techniques, such as residence time distribution, offer insights into species mobility within a reactive volume for a traditional chemical reactor, electrochemical reactors also enable simultaneous measurement of the redox reactions, unlocking another dimension of analysis. Herein, we demonstrate how potentiodynamic measurements, using injections of electrolyte examined through moment analysis, can provide electrode-specific performance scaling relationships across a matrix of carbon paper and cloth electrodes with flow through and interdigitated flow fields. We further combine experimental campaigns with multiphysics simulations to demonstrate how electrode surface area can be estimated with this technique, which we then validate with activated and unactivated commercial carbon cloth electrodes. These studies reveal the multiscale observations that potentiodynamic measurements afford, augmenting existing electrochemical techniques for holistic electrochemical reactor diagnostics.

Electrochemistry↗

Ocelot

Ocelot is a multiphysics simulation toolkit designed for studying FEL and storage ring based light sources. Ocelot is written in Python. Its central concept is the writing of python's scripts for simulations with the usage of Ocelot's modules and functions and the standard Python libraries.

Serkez, Svitozar↗

NED_Asteroid_Energy_Deposition

In the event of a potentially catastrophic asteroid impact, with sufficient warning time, deploying a nuclear device remains a powerful option for planetary defense if a kinetic impactor proves insufficient. Predicting the effectiveness of a potential nuclear deflection or disruption mission depends on accurate multiphysics simulations of the device's x-ray energy deposition into the asteroid and the resulting material ablation. These simulations span many orders of magnitude, require a variety of different complex physics packages, and are computationally expensive. Having an efficient and accurate way of modeling this system is necessary for exploring a mission's sensitivity to the asteroid's range of physical properties. To expedite future simulations, we present a completed x-ray energy deposition model developed using the radiation-hydrodynamics code Kull which can be used to initiate a nuclear mitigation mission hydrocode. The model spans a wide variety of possible mission initial conditions: four different asteroid-like materials (Silicon Dioxide, Forsterite, Iron, and Ice), two different source spectra (1 and 2 keV blackbodies), and then a broad range of radiation fluences (0.0001 to 1 kt per square meter), source durations (10 to 100 ns), and asteroid porosities (0 to 80 percent). Using blowoff momentum as the primary metric, the modelinitiated simulation results match the full radiation-hydrodynamics results to within 10 percent. Please reference the journal article: Burkey et al., X-Ray Energy Deposition Model for Simulating Asteroid Response to a Nuclear Planetary Defense Mitigation Mission, Planetary Science Journal, (2023) for more information.

Managan, RobertA↗

Griffin-m

Griffin-m is a MOOSE-based reactor multiphysics application that streamlines the analysis of a variety of nuclear multiphysics simulations, including steady-state and transient radiation transport, core performance, fuel depletion, criticality and decay heat calculations, reprocessing and post-irradiation examination. This streamlining is accomplished via enhanced flexibility of the tools, uniform syntax in the MOOSE framework, dynamic linking of all relevant physics and a single point of execution. The design for flexible multi-physics, multi-radiation, multi-scheme tasks demands and ultimately makes Griffin-m a highly extendable code system. A software quality assurance (SQA) procedure is enforced during Griffin-m development. The Griffin-m version will be the main production version and it includes the MCC3 code, which was originally developed at Argonne National Laboratory to prepare cross sections for fast reactors.

Ortensi, Javier [Idaho National Laboratory (INL), ↗

Godiva Experiments for the Nuclear Criticality Safety Program (NCSP)

Godiva IV is a fast burst critical assembly constructed of approximately 65 kg of highly enriched uranium (HEU) fuel alloyed with 1.5 percent molybdenum for strength. Godiva is one of the last such critical assemblies in the United States, and can be used for studies of super-prompt critical behavior as well as irradiations and demonstrations. A demonstration of a Godiva burst is usually performed as a highlight of the hands-on portion of the Criticality Safety Training Classes taught at the National Criticality Experiment Research Center (NCERC). The Godiva burst is used to demonstrate the concept of super-prompt critical and the time-scale of a criticality accident. In addition, several NCSP projects have been conducted on Godiva IV over the past two years. One experiment focused on collecting data to support multiphysics simulations using Photo-Doppler Velocimetry (PDV) to measure surface movement and gamma detectors to measure the burst output as the burst develops from background to peak over ten orders of magnitude. Another experiment was performed to demonstrate the functionality of the Criticality Accident Alarm System (CAAS) system developed for installation in the Y-12 Uranium Processing Facility (UPF). The system must not only respond to a criticality event and alarm, but must also be shown to operate in a high dose environment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A New On-the-Fly Sampling Method for Incoherent Inelastic Thermal Neutron Scattering Data in MCNP6

At thermal energies, the scattering of neutrons in a system is complicated by the comparable velocities of the neutron and target, resulting in competing upscattering and downscattering events. The neutron wavelength is also similar in size to the target's interatomic spacing making the scattering process a quantum mechanical problem. Because of the complicated nature of scattering at low energies, the thermal data files in ACE format used in continuous-energy Monte Carlo codes are quite large { on the order of megabytes for a single temperature and material. In this paper, a new storage and sampling method is introduced that is orders of magnitude less in size and is used to sample scattering parameters at any temperature on-the-fly. In addition to the reduction in storage, the need to pre-generate thermal scattering data tables at fine temperatures has been eliminated. This is advantageous for multiphysics simulations which may involve temperatures not known in advance. A new module was written for MCNP6 that bypasses the current S(α,β) table lookup in favor of the new format. The new on-the-fly sampling method was tested for graphite for two benchmark problems at ten temperatures: 1) an eigenvalue test with a fuel compact of uranium oxycarbide fuel homogenized into a graphite matrix, 2) a surface current test with a \broomstick" problem with a monoenergetic point source. The largest eigenvalue difference was 152pcm for T= 1200K. For the temperatures and incident energies chosen for the broomstick problem, the secondary neutron spectrum showed good agreement with the traditional S(α,β) sampling method. These preliminary results show that sampling thermal scattering data on-the-fly is a viable option to eliminate both the storage burden of keeping thermal data at discrete temperatures and the need to know temperatures before simulation runtime.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

SHARP pre-release v1.0 - Current Status and Documentation

The NEAMS Reactor Product Line effort aims to develop an integrated multiphysics simulation capability for the design and analysis of future generations of nuclear power plants. The Reactor Product Line code suite’s multi-resolution hierarchy is being designed to ultimately span the full range of length and time scales present in relevant reactor design and safety analyses, as well as scale from desktop to petaflop computing platforms. In this report, building on a several previous report issued in September 2014, we describe our continued efforts to integrate thermal/hydraulics, neutronics, and structural mechanics modeling codes to perform coupled analysis of a representative fast sodium-cooled reactor core in preparation for a unified release of the toolkit. The work reported in the current document covers the software engineering aspects of managing the entire stack of components in the SHARP toolkit and the continuous integration efforts ongoing to prepare a release candidate for interested reactor analysis users. Here we report on the continued integration effort of PROTEUS/Nek5000 and Diablo into the NEAMS framework and the software processes that enable users to utilize the capabilities without losing scientific productivity. Due to the complexity of the individual modules and their necessary/optional dependency library chain, we focus on the configuration and build aspects for the SHARP toolkit, which includes capability to autodownload dependencies and configure/install with optimal flags in an architecture-aware fashion. Such complexity is untenable without strong software engineering processes such as source management, source control, change reviews, unit tests, integration tests and continuous test suites. Details on these processes are provided in the report as a building step for a SHARP user guide that will accompany the first release, expected by Mar 2016.

Mahadevan, Vijay S.↗

Grizzly Usage and Theory Manual

Grizzly is a multiphysics simulation code for characterizing the behavior of nuclear power plant (NPP) structures, systems and components (SSCs) subjected to a variety of age-related aging mechanisms. Grizzly simulates both the progression of aging processes, as well as the capacity of aged components to safely perform. This initial beta release of Grizzly includes capabilities for engineering-scale thermo-mechanical analysis of reactor pressure vessels (RPVs). Grizzly will ultimately include capabilities for a wide range of components and materials. Grizzly is in a state of constant development, and future releases will broaden the capabilities of this code for RPV analysis, as well as expand it to address degradation in other critical NPP components.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗