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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

RE-INTEGRATE EMT Simulation Software: Graph Convolutional Network for Sparse Matrix Pattern Detection

The increasing complexity of power networks, driven by proliferation of inverters, presents analytical challenges that simplified models often fail to capture, necessitating Electromagnetic Transient (EMT) simulations. EMT models are represented as discretized differential-algebraic equations (DAEs), forming a linear system Ax = b that is computationally intensive to solve. Due to inherent sparsity of adjacency matrix A, distinct patterns emerge that, when accurately identified, enable efficient solver selection to minimize computation time. However, identifying ideal pattern is complicated by numerous reordering algorithms and limited structural insights. To address this, we introduce a Graph Convolutional Network (GCN) model for classifying sparse matrix patterns common in power system analysis. The model, achieving 96% test accuracy, is validated using PV plant models of 125 MW capacities connected to New England 39-bus transmission system (TS), and further scaled to a 4,992-bus network with 384 PV plants, yielding 191, 616 × 191, 616 sized A matrix. For all cases, the GCN model accurately identifies the matrix’s intrinsic sparse pattern, demonstrating its potential to enhance solver performance in EMT analysis.

Hossain, Md Rifat [Florida International Universit↗
DOE OSTI2025

A Parameter-masked Mock Data Challenge for Beyond-two-point Galaxy Clustering Statistics

The past few years have seen the emergence of a wide array of novel techniques for analyzing high-precision data from upcoming galaxy surveys, which aim to extend the statistical analysis of galaxy clustering data beyond the linear regime and the canonical two-point (2pt) statistics. We test and benchmark some of these new techniques in a community data challenge named “Beyond-2pt,” initiated during the Aspen 2022 Summer Program “Large-Scale Structure Cosmology beyond 2-Point Statistics,” whose first round of results we present here. The challenge data set consists of high-precision mock galaxy catalogs for clustering in real space, in redshift space, and on a light cone. Participants in the challenge have developed end-to-end pipelines to analyze mock catalogs and extract unknown (“masked”) cosmological parameters of the underlying ΛCDM models with their methods. The methods represented are density-split clustering, nearest neighbor statistics, BACCO power spectrum emulator, void statistics, LEFTfield field-level inference using effective field theory (EFT), and joint power spectrum and bispectrum analyses using both EFT and simulation-based inference. In this work, we review the results of the challenge, focusing on problems solved, lessons learned, and future research needed to perfect the emerging beyond-2pt approaches. The unbiased parameter recovery demonstrated in this challenge by multiple statistics and the associated modeling and inference frameworks supports the credibility of cosmology constraints from these methods. The challenge data set is publicly available, and we welcome future submissions from methods that are not yet represented.

Krause, Elisabeth [Univ. of Arizona, Tucson, AZ (U↗
DOE OSTI2024

Laser Shock Modeling Archival Discussion

The purpose of this discussion is to provide archival information related to the Laser Shock finite element modeling effort. As discussed in Laser Shock System, Assessing bond strength in layered materials (see Section 8.0), the Laser Shock System creates a high-amplitude shockwave on the frontside of a structure (i.e. an aluminum 6061-T6 plate for this discussion) via a high-energy pulsed laser. The shock wave is monitored on the back surface of the structure as a velocity time history. It is a compressive wave as it comes to the back surface but reflects as a tensile wave. If a bond exists in the structure and the reflected tensile wave exceeds its interface threshold stress, then bond rupture occurs. The desire of the Laser Shock effort is to establish (with multiple tests) an ultimate bond strength which can be used for fuel plate design calculations. In this process, the finite element modeling effort is the catalyst to mimic the Laser Shock tests and provide the damage information at the bond that is useful for fuel plate design calculations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Nanopore Confinement of C-H-O Mixed-Volatile Fluids Relevant to Subsurface Energy Systems

The overarching goal of OU’s contribution to the project was to use novel computational approaches to quantify the effect of variable nanopore features (pore size, volume, topology, and chemistry) and the presence of water or salt solutions on the sorption and transport of carbon-bearing fluids. To achieve this goal OU collaborators tested test two related hypotheses: • The transport of water and aqueous electrolytes in nanopores is controlled by pore size, pore wall composition, and the type of salt – structure-maker (e.g., CaCl 2 ) versus structure-breaker (e.g., NaCl) that affect the hydrogen-bonding network. • The structure, solubility, and transport of carbon-bearing molecules in water or aqueous electrolyte-filled nanopores are controlled by the substrate type including degree of hydration, and pore features, and regulated by the hydration structure of the guest molecules.

58 GEOSCIENCES↗
DOE OSTI2024

Thermal Conductivity Measurements on Irradiated TRISO Fuel at IMCL

INL is leading the development and testing of accident tolerant fuels: fuels that resist melting down and that contain radioactive byproducts, preventing their release into their environment. One such fuel, called TRi-structural ISOtropic particle fuel (TRISO) See Fig 1. Understanding how heat propagates through a fuel is essential to fuel development and qualification. When irradiated in a reactor the properties that affect heat transport change. Our objective is to quantify the change in thermal properties of TRISO after irradiation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

FPMS_XPeRT_INL_Poster

As nuclear energy expands and experimental programs increasingly rely on the facilities at Idaho National Laboratory (INL) for reactor and fuel testing, research capabilities must also expand to meet these demands. A new Fission Product Monitoring System (FPMS) has been deployed at the Advanced Test Reactor (ATR) at the Auxiliary Lead-out Experiment (ALE) House to support this expanding fuel testing mission. By tracking gaseous fission products releases from test fuel in near real-time, release rates, calculated from FPMS data, can be used to characterize the effectiveness of fuel cladding, especially for Tri-structural Isotropic (TRISO) fuel concepts. The new iteration of the FPMS supports up to 14 fission product monitors for online fission-product tracking via gamma-ray spectroscopy of the experiment’s effluent gas. Each monitor consists of a nominally 10% HPGe detector housed in a copper-lined lead shield with a warm gas trap. The new system features gamma-ray count rate information with a five-second temporal resolution and provides isotopic activity every five minutes, capable of resolving multiple overlapping fission product releases over a broad range of activities in near real-time. This work includes data from ATR cycle 175D data to demonstrate these capabilities. The hourly resolution data shows general trends and significant releases over the cycle, while the 5-minute resolution data allows for a more detailed examination of events due to unexpected particle releases.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2024

Metagenome-assembled genomes provide insight into the metabolic potential during early production of Hydraulic Fracturing Test Site 2 in the Delaware Basin

Demand for natural gas continues to climb in the United States, having reached a record monthly high of 104.9 billion cubic feet per day (Bcf/d) in November 2023. Hydraulic fracturing, a technique used to extract natural gas and oil from deep underground reservoirs, involves injecting large volumes of fluid, proppant, and chemical additives into shale units. This is followed by a “shut-in” period, during which the fracture fluid remains pressurized in the well for several weeks. The microbial processes that occur within the reservoir during this shut-in period are not well understood; yet, these reactions may significantly impact the structural integrity and overall recovery of oil and gas from the well. To shed light on this critical phase, we conducted an analysis of both pre-shut-in material alongside production fluid collected throughout the initial production phase at the Hydraulic Fracturing Test Site 2 (HFTS 2) located in the prolific Wolfcamp formation within the Permian Delaware Basin of west Texas, USA. Specifically, we aimed to assess the microbial ecology and functional potential of the microbial community during this crucial time frame. Prior analysis of 16S rRNA sequencing data through the first 35 days of production revealed a strong selection for a Clostridia species corresponding to a significant decrease in microbial diversity. Here, we performed a metagenomic analysis of produced water sampled on Day 33 of production. This analysis yielded three high-quality metagenome-assembled genomes (MAGs), one of which was a Clostridia draft genome closely related to the recently classified Petromonas tenebris. This draft genome likely represents the dominant Clostridia species observed in our 16S rRNA profile. Annotation of the MAGs revealed the presence of genes involved in critical metabolic processes, including thiosulfate reduction, mixed acid fermentation, and biofilm formation. These findings suggest that this microbial community has the potential to contribute to well souring, biocorrosion, and biofouling within the reservoir. Our research provides unique insights into the early stages of production in one of the most prolific unconventional plays in the United States, with important implications for well management and energy recovery.

natural gas↗
DOE OSTI2025

Interface-engineered (AlMnCoNiZn) 3 O 4 @PPy nanocomposites for superior lithium storage: Mechanism and performance

The practical application of graphite anodes in lithium-ion batteries (LIBs) is constrained by low specific capacity (372 mAh g -1 ) and sluggish kinetics. Here, to address these limitations, our present study focuses on high-entropy oxides (HEOs), which offer high theoretical capacity and structural stability. We synthesized spinel-structured (AlMnCoNiZn) 3 O 4 nanoparticles via a solution combustion method and fabricated an (AlMnCoNiZn) 3 O 4 @polypyrrole (PPy) nanocomposite through in-situ polymerization. Our electrochemical tests demonstrate that the PPy modification significantly enhances performance. While the pristine (AlMnCoNiZn) 3 O 4 delivered 445 mAh g −1 after 100 cycles at 100 mA g −1 and 350 mAh g −1 after 1000 cycles at 1000 mA g −1 , the (AlMnCoNiZn) 3 O 4 @PPy composite achieved 695 mAh g −1 after 100 cycles and maintained 675 mAh g −1 after 1000 cycles. Furthermore, the composite improved rate capacity at 1000 mA g −1 from 211 mAh g −1 to 403 mAh g −1 . This work highlights how conductive and flexible polymer modifications can dramatically improve the electrochemical properties of HEOs. The developed (AlMnCoNiZn) 3 O 4 @PPy composite provides a promising direction for designing advanced anodes to meet next-generation energy storage demands.

Anodes material↗
DOE OSTI2025

Accelerating Embedding Potential Optimization by Reconstructing the Pseudo-Valence Electron Density

Density functional embedding theory (DFET) enables use of electronic structure methods with higher accuracy than density functional theory in a local region, with applications thus far ranging from (photo/electro)catalysis to reactions in solution. DFET partitions a large collection of atoms into smaller groups that interact via a shared embedding (interaction) potential V emb , determined via functional optimization. The optimized effective potential (OEP) process used to optimize V emb is time-consuming and becomes a computational bottleneck due to sharp, oscillating features of V emb near nuclei. Here, similar to pseudopotential theory, by reconstructing electron densities used in the OEP process from smoother pseudo-valence-only (PVO) electron densities as proxies for total densities of the full system and subsystems, we can retain accuracy in the embedded electronic structure calculations while potentially reducing the overhead of V emb construction, within the projector augmented-wave (PAW) formalism. We explore three different chemical reactions as exemplars to test PVO–DFET, namely, H 2 dissociative adsorption on a Cu(111) surface, H 2 O adsorption on a Pt(111) surface, and aqueous [Ca 2+ –SO 4 2– ] ion-pair formation. The PVO approximation works well for all three systems with minimal loss of accuracy (∼10–70 meV error relative to the original exact-derivative (ED) approach) while accelerating V emb generation for the Cu and Pt systems respectively by 20× and 5×. Given proper numerical convergence parameters, the spatial distributions of differences between PVO- and ED-based V emb outside the core regions are small, explaining the exceptional agreement between the two approaches. Finally, we anticipate that this more efficient PVO–DFET approximation will be useful whenever computation of V emb is much more expensive than subsequent embedded high-level electron correlation calculations.

approximation↗
DOE OSTI2024

Learning a general model of single phase flow in complex 3D porous media

Modeling effective transport properties of 3D porous media, such as permeability, at multiple scales is challenging as a result of the combined complexity of the pore structures and fluid physics—in particular, confinement effects which vary across the nanoscale to the microscale. While numerical simulation is possible, the computational cost is prohibitive for realistic domains, which are large and complex. Although machine learning (ML) models have been proposed to circumvent simulation, none so far has simultaneously accounted for heterogeneous 3D structures, fluid confinement effects, and multiple simulation resolutions. By utilizing numerous computer science techniques to improve the scalability of training, we have for the first time developed a general flow model that accounts for the pore-structure and corresponding physical phenomena at scales from Angstrom to the micrometer. Using synthetic computational domains for training, our ML model exhibits strong performance (R 2 = 0.9) when tested on extremely diverse real domains at multiple scales.

36 MATERIALS SCIENCE↗
DOE OSTI2024

STUDIES ON PIPELINE POLYETHYLENES IN HYDROGEN GAS ENVIRONMENTS USING IN-SITU AND EX-SITU CHARACTERIZATION METHODS

Polymeric materials are commonplace in the natural gas infrastructure as distribution pipes, coatings, seals, and gaskets. Under the auspices of the U.S. Department of Energy HyBlend program, one of the means to reduce greenhouse gas emissions is with replacing natural gas, either partially or completely, with hydrogen. This approach makes it imperative that we conduct near-term and long-term materials compatibility research in these relevant environments. Insights into the effects of hydrogen and hydrogen gas blends on polymer integrity can be gained through both ex-situ and in-situ analytical methods. Our work represented here highlights a study of the behavior of pipeline polyethylene (PE) materials, including HDPE (Dow 2490 and GDB50) and MDPE (Ineos and legacy Dupont Aldyl A), when exposed to hydrogen by means of in-situ X-ray scattering and ex-situ Raman spectroscopy techniques. Samples were tested in ex-situ hydrogen and argon gas environments and in-situ hydrogen environments to identify differences due to permeation and solubility of these gases. These methods complemented each other because Raman spectroscopy could capture permanent effects after materials were removed from gaseous environments, and in-situ X-ray scattering analysis collected real-time data to elucidate the impact of the gas environment on polymer microstructure. Data collected revealed that the aforementioned polymers did not show significant changes in crystallinity and microstructure under the exposure conditions tested. Our findings from these studies will help establish real-time effects caused by hydrogen gas transport through pipeline polyethylenes by way of its influence on polymer structure and chemistry, which is directly related to pipeline mechanical strength and longevity of service.

Hydrogen materials compatibility, Natural gas pipe↗
DOE OSTI2026

Oil-impregnated densified wood veneer with high electrical insulation enabled by nanosized oil channels

Growing energy demands and renewable integration are stressing the aging power grid infrastructure. Lignocellulosic oil-impregnated paper is widely used in power transformers but suffers from critical limitations, such as low dielectric strength, mechanical strength, and thermal conductivity, causing premature transformer failures. Here, we demonstrate a superior electrically insulating oil-impregnated paper design using the naturally anisotropic structure of densified wood veneer to achieve nanosized channels of oil that efficiently disrupt electrical breakdown pathways. The developed oil-impregnated densified wood (ODW) creates aligned cellulose fibers with 166 ± 87–nanometer oil nanochannels, achieving record dielectric strength of 105 kilovolts per millimeter. The structure also delivers a mechanical strength of up to 384 megapascals and a thermal conductivity of 0.33 watts per meter per kelvin, enabling enhanced longevity upon thermal aging tests. The ODW could replace conventional transformer insulation to enhance power transformer performance and improve lifetime. Moreover, its anisotropic oil-filled nanochannel design offers a general strategy for hybrid dielectrics in medium- and high-voltage applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Impact of Silicon Impurity on the Hydrometallurgical Recovery of NCM622 Cathode

Hydrometallurgy is one of the best approaches to date for recycling LIBs due to its high efficiency, low energy usage, and industrial scalability. However, impurities have always been a thorny issue because they could have unintended impacts on the recovered cathode materials. This research marks the first systematic investigation into the influence of silicon impurity on the LiNi 0.6 Co 0.2 Mn 0.2 O 2 (NCM622) cathode obtained from hydrometallurgical recycling. Here we find that silicon nanoparticles will be nucleated at the center of the precursor particles during co-precipitation synthesis, and the silicon core will slowly dissolve in the surrounding ammonia, creating a special hollow structure in the particle. More importantly, the dissolution of silicon impurity will eventually lead to the deposition of silicates in the cathode material, which is an unfavorable result. Test data indicate that NCM622 cathode with 5 at% silicon has a capacity of 148.8 mAh g −1 after 100 cycles at 1/3 C, approximately 10 mAh g −1 lower than the virgin. Despite being relatively mild, the adverse influence of silicon impurity in hydrometallurgical recycling still requires attention.

25 ENERGY STORAGE↗
DOE OSTI2024

Learning a General Model of Single Phase Flow in Complex 3D Porous Media

Modeling effective transport properties of 3D porous media, such as permeability, at multiple scales is challenging as a result of the combined complexity of the pore structures and fluid physics—in particular, confinement effects which vary across the nanoscale to the microscale. While numerical simulation is possible, the computational cost is prohibitive for realistic domains, which are large and complex. Although machine learning (ML) models have been proposed to circumvent simulation, none so far has simultaneously accounted for heterogeneous 3D structures, fluid confinement effects, and multiple simulation resolutions. By utilizing numerous computer science techniques to improve the scalability of training, we have for the first time developed a general flow model that accounts for the pore-structure and corresponding physical phenomena at scales from Angstrom to the micrometer. Using synthetic computational domains for training, our ML model exhibits strong performance (R 2 = 0.9) when tested on extremely diverse real domains at multiple scales.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Microstructure Clones

Microstructure drives component behavior. Contemporary crystal plasticity studies compare strain measurements of polycrystal specimens to models. Because each specimen is unique, it is impossible to know which differences are significant. In this project, we invented microstructure clones and explored their use in understanding crystal plasticity. Microstructure clones are specimens with nearly identical microstructures, which allows for multiple destructive tests of a microstructure, insight into how a specimen will deform, variability quantification, and the ability to measure the effects of microstructural changes. Several sets of microstructure clones, pure nickel tensile bars, were tested. The techniques of digital image correlation, crystal plasticity finite element analysis, high resolution electron backscatter diffraction, transmission electron microscopy, and dislocation dynamics were used to understand the structural behavior of these microstructures. This work reshapes the fields of crystal plasticity and structure-property relationships by providing a technique to control for specific variables, quantify microstructural stochasticity, and replicate experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Enhanced Design of Radiation Tolerant High-Temperature Structural Health Monitoring Sensors

Acoustic emission sensors are vital in the nuclear industry for real-time structural health monitoring and early detection of material degradation. By capturing high-frequency stress waves emitted from defects like cracks, corrosion, or fatigue, acoustic emission sensors enable non-invasive monitoring of critical components such as reactor vessels, piping, and containment structures. This technology supports predictive maintenance, enhances safety, and ensures regulatory compliance by providing early warnings of potential failures. It is also instrumental in research, particularly in material testing reactors, where it is used to monitor the behavior of fuels and materials under irradiation, by allowing the detection of cracking or other acoustic signals in real time. This enables the evaluation of performance and accident behavior of advanced fuel concepts.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2026

Advancing Detector R&D for High-Pressure Gaseous Argon TPCs in Precision Neutrino Physics

High-pressure gaseous argon time projection chambers (HPgTPCs) represent an emerging detector paradigm for neutrino physics, combining increased target density with the intrinsic tracking and low thresholds of gaseous detectors. This approach enables detailed reconstruction of exclusive final states, improved particle identification, and sensitivity to low-energy and rare processes — capabilities that are increasingly central to precision oscillation measurements and searches for beyond-the-Standard-Model signatures. This abstract presents an overview of ongoing detector R&D toward high-pressure gaseous argon TPC operation, with emphasis on micro-pattern gas detector (MPGD) charge amplification in argon-based mixtures. We report experimental characterization of triple-GEM structures at pressures relevant for neutrino applications, including studies of multiplication factor scaling, stability, and operational voltage envelopes across gas admixtures. Measurements performed at the TOAD and GORG test stands at Fermilab help define viable amplification and electronics noise regimes in conditions where higher density imposes stricter constraints on signal formation. These results provide essential input to the optimization of high-pressure gaseous argon detectors for future neutrino experiments, including near-detector concepts such as ND-GAr in DUNE Phase II near detector upgrade. More broadly, this program shows how dedicated detector R&D can expand the precision frontier in neutrino physics by enabling complementary reconstruction capabilities beyond conventional detectors.

McConnell, Brenna [Indiana U.] (ORCID:000900041138↗
DOE OSTI2025

Insights on the Influence of the Central-Cut Width of the Box Assembly with Removable Component on Its Dynamical Responses

This investigation focuses on the dynamical effects caused by varying the central-cut width within the Box Assembly with Removable Component (BARC) system. The central-cut widths included in this study are a 0.5″ cut, a 0.25″ cut, a thin 0.1″ cut, and a structure that did not have a cut at all. Finite element analysis was conducted to determine the mode shapes and natural frequencies of each of the BARC structures. Structural dynamics experiments were run to examine the effects of the central-cut width on the dynamical responses and nonlinear characteristics of the BARC system. Free vibration testing with an impact hammer was carried out to excite the system and extract the dominant frequencies and directions of the significant responses. A pseudorandom vibration test that allows for the qualitative determination of any nonlinear behavior within the system was performed. This type of behavior can include nonlinear softening, nonlinear hardening, and the most common, nonlinear damping due to the presence of several bolted-joint connections and the possible activation of geometric and inertia nonlinearities. To quantitatively investigate the impacts of the central-cut width on the dynamics of the system, swept sinusoidal testing was conducted. It is determined that almost all systems with central cuts demonstrate the presence of nonlinear softening, but at times, nonlinear hardening trends are seen, particularly in the 0.1″ cut and no-cut systems when testing harmonically. Each of the central-cut systems displays nonlinear damping, with the amount of damping generally increasing as the central cut decreases in size. The effect of the central cut of the BARC system on the mode-switching ability of the system is negligible; however, mode switching takes place when comparing the central-cut configurations to the no-cut one. These results show the significance of accurately measuring the central-cut width and how geometric uncertainty may change the dynamical responses and nonlinear properties of the system.

Padilla, Christopher (ORCID:000900033446732X)↗