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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

X-ray Micro-Computed Tomography for Structural Analysis of All-Solid-State Battery at Pouch Cell Level

Characterizing the microstructure of all-solid-state batteries (ASSBs) during fabrication and operation is vital for their advancement, particularly as scaling to pouch cell levels introduces challenges in probing large-scale microstructural evolution. This work highlights the potential of synchrotron X-ray micro-computed tomography (sXCT) as a nondestructive, rapid (<30 min), and high-resolution technique for visualizing and quantifying key microstructural features, including overhang, porosity, contact loss, active surface area, and tortuosity, in all-solid-state pouch cells. The large field of view (up to millimeters) of sXCT enables detailed analysis at an industry-relevant scale, bridging the gap between laboratory research and commercial applications. Furthermore, integrating realistic sXCT-derived 3D models into multiphysics simulations could provide insights into chemo-mechanical degradation, particularly at the edges of the pouch cells, offering a pathway for designing robust, high-performance ASSBs. This perspective establishes sXCT as an indispensable tool for advancing both the understanding and the engineering of next-generation energy storage systems.

25 ENERGY STORAGE↗
DOE OSTI2021

Physics-informed machine learning

Despite great progress in simulating multiphysics problems using the numerical discretization of partial differential equations (PDEs), one still cannot seamlessly incorporate noisy data into existing algorithms, mesh generation remains complex, and high-dimensional problems governed by parameterized PDEs cannot be tackled. Moreover, solving inverse problems with hidden physics is often prohibitively expensive and requires different formulations and elaborate computer codes. Machine learning has emerged as a promising alternative, but training deep neural networks requires big data, not always available for scientific problems. Instead, such networks can be trained from additional information obtained by enforcing the physical laws (for example, at random points in the continuous space-time domain). Such physics-informed learning integrates (noisy) data and mathematical models, and implements them through neural networks or other kernel-based regression networks. Moreover, it may be possible to design specialized network architectures that automatically satisfy some of the physical invariants for better accuracy, faster training and improved generalization. Furthermore, we review some of the prevailing trends in embedding physics into machine learning, present some of the current capabilities and limitations and discuss diverse applications of physics-informed learning both for forward and inverse problems, including discovering hidden physics and tackling high-dimensional problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Direct observation of the local microenvironment in inhomogeneous CO 2 reduction gas diffusion electrodes via versatile pOH imaging

In this study, we report how the micrometer-scale morphology of a carbon dioxide reduction (CO 2 R) gas diffusion electrode (GDE) affects the mass transport properties and with it, the local CO 2 R performance. We developed a technique to probe the microenvironment in a CO 2 R GDE via local pOH imaging with time- and three-dimensional spatial, micrometer-scale resolution. The local activity of hydroxide anions (OH - ), represented by the pOH value, around a GDE in contact with an aqueous electrolyte is a crucial parameter that governs the catalytic activity and CO 2 R selectivity. Here, we use fluorescence confocal laser scanning microscopy (CLSM) to create maps of the local pOH around a copper GDE by combining two ratiometric fluorescent dyes, one of which is demonstrated as a pOH sensor for the first time in this work. We observe that the local pOH decreases when current is applied due to the creation of OH - as a byproduct of CO 2 R. Interestingly, the pOH is lower inside microtrenches compared to the electrode surface and decreases further as trenches become more narrow due to enhanced trapping of OH - . We support our experimental results with multiphysics simulations that correlate exceptionally well with measurements. These simulations additionally suggest that the decreased pOH inside microcavities in the surface of a CO 2 R GDE leads to locally enhanced selectivity towards multicarbon (C 2+ ) products. This study suggests that narrow microstructures on the length scale of 5 μm in a GDE surface serve as local CO 2 R hotspots, and thus highlights the importance of a GDE's micromorphology on the CO 2 R performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Preliminary benchmarks and analysis of boundary conditions in a trenched microstructured silicon radiation detector

Microstructured neutron detectors have the benefit of enhanced neutron detection efficiency as compared to planar devices, achieved by etching 6 LiF-filled trenches on the top surface of a silicon PIN diode. This sensor geometry results in a complex electric field distribution and depletion characteristics within the diode under reverse bias. For the first time on record, the effects of a fixed oxide charge on the microstructured device depletion characteristics and mobile carrier transport is investigated. Prototype detectors were fabricated with non-conformal surface doping. Capacitance voltage and current voltage measurements were performed for these prototypes and compared with COMSOL Multiphysics simulations. A spectral response from an 241Am alpha particle source was acquired and analyzed. It was found that monoenergetic alpha particles produce three prominent peaks in the pulse height spectrum output by the device. The peaks were confirmed by simulations to correlate with dead layers and incident trajectories into the microstructure. It was also found that significant differences in pulse rise time result, corresponding with events arriving in a low-field region in the fins and a high-field region in the bulk. Geant4 was utilized for radiation transport, interaction modeling, and benchmarking the spectral data. The results of this simulation work provide confidence in the ability to attain and benchmark electrical characteristics and spectral data for semiconductor radiation detectors employing complex microstructures.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Multifrequency eddy-current detection of fast transient thermal signatures for in situ monitoring applications

Eddy-current (EC) nondestructive evaluation has a long history of use in a variety of ex situ defect monitoring applications because of its exquisite sensitivity to local material variations. Due to the relationship between a material's conductivity and its temperature, EC methods have also been used to investigate quasistatic, long-range temperature variations in casting applications. However, these techniques remain underutilized for the measurement of rapidly varying, spatially nonuniform temperature distributions. In this work, we construct a model system capable of generating repeatable temperature transients in steel plates and measure real-time eddy-current signals with millisecond time resolution and spatial resolution of the order of 1 mm. Using a combination of Multiphysics simulations, fast thermal imaging, and time-resolved holographic interferometry, we tease apart contributions to the eddy-current signals arising from temperature variations and transient plate deformation. Finally, we perform a systematic study in which we vary the plate thickness and the eddy-current excitation frequency to demonstrate that eddy-current techniques can provide information about a three-dimensional, time-varying, subsurface thermal distribution, which is inaccessible to the traditional thermal imaging techniques.

Rosenberg, Ethan R. [Lawrence Livermore National L↗
DOE OSTI2026

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↗
DOE OSTI2020

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↗
DOE OSTI2024

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↗
DOE OSTI2023

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

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

42 ENGINEERING↗
DOE OSTI2026

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]↗
DOE OSTI2026

Discovery of Probabilistic Dirichlet-to-Neumann Maps on Graphs

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

Dirichlet-to-Neumann map↗
DOE OSTI2026

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↗
DOE OSTI2023

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↗
DOE OSTI2023

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↗
DOE OSTI2021

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), ↗
DOE OSTI2021

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 ↗
DOE OSTI2020

Charged Wellbore Casing Controlled Source Electromagnetics (CWC-CSEM) for Reservoir Imaging and Monitoring (Final report)

This project addresses the needs of the U.S. Department of Energy (DOE) to develop advanced monitoring technologies and protocols to track the fate of subsurface carbon dioxide (CO2) plumes for carbon storage. Specifically, the project seeks to develop and test a unique and novel system of technologies consisting of electromagnetic data acquisition, coupled multiphysics imaging, and reservoir model enhancement to understand the migration and long-term distribution of CO2 in the subsurface. The overarching objective is to develop an integrated approach for long term monitoring of carbon storage. The two main components of the project include the methodology development and the test of the method at a field site. The methodology component consists of 1) developing the field procedure and protocol for collecting time-lapse controlled-source electromagnetic (CSEM) data with source electric current injected into the subsurface through wellbore casings; 2) building of background 3D electrical conductivity utilizing multiple sources of data such as supplemental surface transient EM (TEM) surveys, well-logs, and seismic structural information, for enhancing CSEM signal from reservoir depths; and 3) coupled multiphysics simulations and inversion of CSEM data constrained by production data and by structural information from seismic imaging of the reservoir and overlying formations. The testing component used the field site of Bell Creek Oil Field, which served both as a field laboratory for the method development as well as a test site to evaluate the CSEM signal strengths and the methodology developed in this research project. We have accomplished all the proposed tasks and developed the methodology as planned. These include the procedure for time-lapse CSEM data acquisition, data processing techniques, integration with 3D conductivity model building, fast reservoir simulation for history matching using machine learning, and interpreting CSEM data with coupling to the reservoir modeling. Collectively, the outcome of these tasks form a coherent workflow that can be applied to monitor dedicated carbon storage in saline reservoirs. The testing component evaluated the applicability and limitations of the method, and concluded that the method would be ideal for monitoring dedicated carbon storage sites utilizing saline reservoirs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Expanded verification and validation studies of hypersonic aerodynamics with multiple physics-fidelity models

Hypersonic aerothermodynamics is an important domain of modern multiphysics simulation. The Multi-Fidelity Toolkit is a simulation tool being developed at Sandia National Laboratories to predict aerodynamic properties for compressible flows from a range of physics fidelities and computational speeds. These models include the Reynolds-averaged Navier–Stokes (RANS) equations, the Euler equations with momentum-energy integral technique (MEIT), and modified Newtonian aerodynamics with flat-plate boundary layer (MNA+FPBL) equations, and they can be invoked independently or coupled with hierarchical Kriging to interpolate between high-fidelity simulations using lower-fidelity data. However, as with any new simulation capability, verification and validation are necessary to gather credibility evidence. This work describes formal code- and solution-verification activities, as well as model validation with uncertainty considerations. Code verification activities on the MNA+FPBL model build on previous work by focusing on the viscous portion of the model. Viscous quantities of interest are compared against those from an analytical solution for flat-plate, inclined-plate, and cone geometries. The code verification methodology for the MEIT model is also presented. Test setup and results of code verification tests on the laminar and turbulent models within MEIT are shown. Solution-verification activities include grid-refinement studies on simulations that model the HIFiRE-1 wind tunnel experiments. These experiments are used for validation of all model fidelities. A thorough validation comparison with prediction error and uncertainty is also presented. Three additional HIFiRE-1 experimental runs are simulated in this study, and the solution verification and validation work examines the effects of the associated parameter changes on model performance. Finally, a study is presented that compares the computational costs and fidelities from each of the different models.

42 ENGINEERING↗