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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

In situ deformation of antigorite-olivine two-phase mixtures: Implications for dynamics and seismic anisotropy in the mantle wedge

Water released from hydrous minerals in subducting slabs reacts with the overlying plate, resulting in widespread serpentinization in the mantle wedge. Deformation of serpentinized peridotites has been invoked to explain forearc seismic anisotropy, yet studies of the mechanical properties and deformation behaviors of serpentine-bearing multiphase aggregates remain limited. Here we deformed olivine-antigorite mixtures containing 70, 50, and 20 vol.% of antigorite at 2.5 – 7.6 GPa, 673 K and strain rates of ∼10 –5 –10 –4 s –1 . Elasto-viscoplastic self-consistent simulations, constrained by synchrotron X-ray diffraction (XRD) data, were used to estimate lattice strain, stress–strain partitioning, crystallographic preferred orientations (CPO) development, and aggregate strength. Selected run products were also analyzed by electron backscatter diffraction for comparison with the CPO results obtained from XRD experiments. We found olivine transitions from A- or B-type to C-type when antigorite fraction drops to 20 vol.%, coinciding with a microstructural change from interconnected weak layers to a load-bearing framework (LBF). An additional run on a sample Atg50/Ol50 with preexisting microstructures suggested the formation of LBF was promoted by these microstructures, although the preexisting antigorite CPO has been overprinted at 20.8 % strain and could be erased completely by subsequent deformation in nature. Estimated viscosity of the two-phase mixtures suggests that low-degree serpentinization (≤20 %) in the mantle wedge may increase the strength of olivine-rich peridotite and hinder slab-mantle decoupling, whereas high-degree serpentinization (≥50–70 %) weakens the peridotite and favors decoupling if sufficient viscosity contrast (>10) develops. Seismic anisotropy shows a nonlinear dependence on antigorite fraction: antigorite CPO governs the anisotropy of the mixtures with ≥50 vol.% antigorite, whereas olivine CPO dominates at low fractions (∼20 vol.%). The presence of pre-existing microstructures reduces seismic anisotropy of the deformed mixtures, however the persistence of pre-existing CPO in actively subducting slabs remains uncertain, making their significance over geological timescales questionable.

Crystallographic preferred orientation↗
DOE OSTI2025

Explainable AI for Multivariate Time Series Pattern Exploration: Latent Space Visual Analytics With Temporal Fusion Transformer and Variational Autoencoders in Power Grid Event Diagnosis

Detecting and analyzing complex patterns in multivariate time-series data is crucial for decision-making in urban and environmental system operations. However, challenges arise from the high dimensionality, intricate complexity, and interconnected nature of complex patterns, which hinder the understanding of their underlying physical processes. Existing AI methods often face limitations in interpretability, computational efficiency, and scalability, reducing their applicability in real-world scenarios. This paper proposes a novel visual analytics framework that integrates two generative AI models, Temporal Fusion Transformer (TFT) and Variational Autoencoders (VAEs), to reduce complex patterns into lower-dimensional latent spaces and visualize them in 2D using dimensionality reduction techniques such as PCA, t-SNE, and UMAP with DBSCAN. These visualizations, presented through coordinated and interactive views and tailored glyphs, enable intuitive exploration of complex multivariate temporal patterns, identifying patterns’ similarities and uncover their potential correlations for a better interpretability of the AI outputs. The framework is demonstrated through a case study on power grid signal data, where it identifies multi-label grid event signatures, including faults and anomalies with diverse root causes. Additionally, novel metrics and visualizations are introduced to validate the models and assess the performance, efficiency, and consistency of latent maps generated by VAE, which have been utilized in prior studies for latent space cartography and used as a benchmark in this study, and the emerging TFT architecture under various configurations. These analyses provide actionable insights for model parameter tuning and reliability improvements. Comparative results highlight that TFT achieves shorter run times and superior scalability to diverse time-series data shapes compared to VAE. This work advances fault diagnosis in multivariate time series, fostering explainable AI to support critical system operations.

Explainable AI↗
DOE OSTI2020

Multiscale and Multivariate Transportation System Visualization for Shopping District Traffic and Regional Traffic

In this paper, we present a suite of visualization techniques for sensor-based transportation system data at different scales to facilitate the exploration of interconnected traffic dynamics at intersections and highways. Additionally, these techniques are designed for analyzing multivariate traffic data from radar-based highway sensors and camera-based intersection sensors recording turn movements and vehicle speed, in the Chattanooga Metropolitan Area, with the capability of (a) revealing multiscale mobility patterns using different levels of data aggregation (e.g., individual sensor for microscale, multiple sensors along a corridor for mesoscale, and a larger number of sensors across the region for macroscale visualization) at different intervals (e.g., 5-min intervals, time of day, full day, and day-of-the-week), and (b) exploring the spatial variation of multiple traffic-related variables (e.g., volumes, speeds, turn movements, and traffic light colors) provided by the sensors. We close with a case study to demonstrate the effectiveness of our multiscale and multivariate visualization techniques. At microscale, we focused on intersection data from a shopping district around Shallowford Road in East Chattanooga. For mesoscale visualization, we studied the Shallowford Road corridor and an adjacent stretch of I-75. At macroscale, we included highway data from the Chattanooga Metropolitan Area. All visualizations were integrated into a web-based situational awareness tool to promote user access and interaction. At a minimum, each visualization provides the option for selecting dates for real-time (depending on sensor availability) and historical data, and additional information on hovering, though most provide more detailed information, including different views of the selected data, or interactive highlights.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2019

Experimental Study on Mitigation of Lifetime-Limiting Dielectric Cracking in Extreme Temperature 4H-SiC JFET Integrated Circuits

While NASA Glenn Research Center's "Generation 10" 4H-SiC Junction Field Effect Transistor (JFET) integrated circuits (ICs) have uniquely demonstrated 500 °C electrical operation for durations of over a year, this experimental work has also revealed that physical cracking of chip dielectric passivation layers ultimately limits extreme-environment operating lifetime [1-3]. The prevention of such dielectric passivation cracks should therefore improve IC high temperature durability and yield, leading to more beneficial technology adoption into aerospace, automotive, and energy systems. This report describes Generation 10.2, 11.1, and 11.2 die tested under unbiased and unpackaged accelerated age testing at 500 °C, 600 °C, 720 °C, and 800 °C in air-atmosphere ovens for 100- and 200-hour duration. Additional samples were separately subjected to 10 thermal cycles between the same high temperatures (with 10-hour high-temperature soak each cycle) and 50 °C. It is shown that having two stoichiometric Si3N4 layers in the interconnect dielectric stack substantially decreases the amount of dielectric cracking observed following these oven tests.

Spry, D. J.↗
DOE OSTI2020

Load Composition Analysis in Support of the NERC Load Modeling Task Force. 2019-2020 Field Test of the Composite Load Model

In 2015, NERC’s reliability standards were revised to require the use of dynamic load models in transmission planning studies. To comply with the standards, planners must use load models that explicitly represent the dynamic behavior of the different constituents of load at each load bus within their transmission planning models. The most important of these constituents are motor-driven and power electronics-based loads. Collectively, these representations are known as composite load models. In anticipation of the compliance date for the new standards, NERC’s Load Modeling Task Force (LMTF), in 2019, initiated a field test of composite load models involving the regional reliability planning entities. In support of the field test, DOE and BPA researchers developed region-specific composite load models that could be assigned to each non-industrial load bus in the planning models for each of the North American interconnections. Separate models were developed for each hour of a summer peak day, a winter peak day, and a spring light-load day. This report is the technical documentation for the load composition analysis that was conducted to develop these non-industrial composite load models.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Chicken Production and Human Clinical Escherichia coli Isolates Differ in Their Carriage of Antimicrobial Resistance and Virulence Factors

Contamination of food animal products by Escherichia coli is a leading cause of foodborne disease outbreaks, hospitalizations, and deaths in humans. Chicken is the most consumed meat both in the United States and across the globe according to the U.S. Department of Agriculture. Although E. coli is a ubiquitous commensal bacterium of the guts of humans and animals, its ability to acquire antimicrobial resistance (AMR) genes and virulence factors (VFs) can lead to the emergence of pathogenic strains that are resistant to critically important antibiotics. Thus, it is important to identify the genetic factors that contribute to the virulence and AMR of E. coli. In this study, we performed in-depth genomic evaluation of AMR genes and VFs of E. coli genomes available through the National Antimicrobial Resistance Monitoring System GenomeTrackr database. Our objective was to determine the genetic relatedness of chicken production isolates and human clinical isolates. To achieve this aim, we first developed a massively parallel analytical pipeline (Reads2Resistome) to accurately characterize the resistome of each E. coli genome, including the AMR genes and VFs harbored. We used random forests and hierarchical clustering to show that AMR genes and VFs are sufficient to classify isolates into different pathogenic phylogroups and host origin. We found that the presence of key type III secretion system and AMR genes differentiated human clinical isolates from chicken production isolates. These results further improve our understanding of the interconnected role AMR genes and VFs play in shaping the evolution of pathogenic E. coli strains.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Near surface structure of ultrathin epitaxial Ru films on graphene/amorphous SiO 2 revealed by azimuthal RHEED

Ru has been considered as an alternative metallic candidate for future local interconnects. The 2D reciprocal space map constructed from the azimuthal reflection high-energy electron diffraction patterns reveals that ultrathin Ru(0001) is epitaxially grown on transferred graphene on amorphous SiO 2 through quasi-van der Waals interaction. The in-plane and out-of-plane lattice constants are measured from streaks’ separation and intensity modulations along streaks, respectively. Weak and broad rings indicate that a low density of nanoscale polycrystals exist on the surface. In this work, The intensities of 00 and non-00 diffraction spots vs. azimuthal angles in the 2D map show a few degrees out-of-plane and in-plane angular misorientations among grains, respectively. As the film thickness decreases these angular misorientations increase. Transmission electron microscopy carried out in this study also provides precise values of lattice constant and sub-grain sizes in the films. These findings show that ultrathin Ru film is epitaxial but not exactly single crystalline.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Preferred Void Orientation in Uniaxially Pressed PBX 9502

Ultra- and small-angle neutron scattering techniques were used to study the morphology of voids in directions parallel and perpendicular to the compaction plane of a uniaxially pressed cylinder of PBX 9502. Two-dimensional scattering patterns from samples cut parallel to the compaction plane had circular equal-intensity contours, implying that along this view the voids are circular or randomly oriented. Identical measurements of samples cut perpendicular to the compaction plane produced elliptical equal-intensity contours, indicating preferred orientation of voids. Analysis of the two dimensional scattering patterns confirmed that the voids are non-spherical with an average aspect ratio of 1.20, flattened so that the larger dimensions of the voids lie within the compaction plane. Model analysis of the combined ultra- and small-angle neutron scattering curves revealed that the PBX 9502 porosity is interconnected, in the form of aggregates comprised of non-spherical, primary voids. The volume dimension was found to be the same in both directions, indicating that the aggregate is randomly oriented throughout the sample, and that it is the primary voids that are preferentially oriented. Furthermore, void interfaces with the surrounding matrix were found to be rough or polydisperse, with a common roughness dimension or polydispersity in all directions.

42 ENGINEERING↗
NASA NTRS2006

Evaluation of Open Cell Foam Heat Transfer Enhancement for Liquid Rocket Engine

As NASA pursues the exploration mission, advanced propulsion for the next generation of spacecraft will be needed. These new propulsion systems will require higher performance and increased durability, despite current limitations on materials. A break-through technology is needed in the thrust chamber. In this paper the idea of using a porous metallic foam is examined for its potential cooling enhancement capabilities. The goal is to increase the chamber wall cooling without creating an additional pressure drop penalty. A feasibility study based on experiments at laboratory-scale conditions was performed and analysis at rocket conditions is underway. In the experiment, heat transfer and pressure drop data were collected using air as the coolant in a copper or nickel foam filled annular channel. The foam-channel performance was evaluated based on comparison with conventional microchannel cooling passages under equal pressure drop conditions. The heat transfer enhancement of the foam channel over the microchannel ranges from 130% to 172%. The enhancement is relatively independent of the pressure drop and increases with decreasing pore size. A direct numerical simulation model of the foam heat exchange has been built. The model is based on the actual metal foam microstructure of thin ligaments (0.2- 0.3 mm in diameter) that form a network of interconnected open-cells. The cell dimension is around 2 mm. The numerical model was built using the FLUENT CFD code. Comparison of the pressure drop results predicted by the current model with those experimental data of Leong and Jin [8] shows favorable comparisons. Pressure drop predictions have been made using hydrogen as a coolant at typical rocket conditions. Conjugate heat transfer analysis using the foam filled channel is planned for the future.

Chung, J. N.↗
NASA NTRSDate not supplied

Estimation of End-of-Life Solar Absorptivity for Complex, Multi-Phased Space Missions

Solar absorptivity degradation over time is an important contributor to the thermal performance of a spacecraft at the end of its life. When environments are complex and include many different factors known to impact solar absorptivity degradation, such as UV, charged particles, contamination, or lunar dust coverage, combining data from several different studies can be done to estimate total degradation. While the most conservative way is to stack delta absorptivity from each factor to come up with a total delta, this may be overly conservative for long or complex missions with multiple mission phases. As absorptivity increases the rate of degradation decreases, and synergistic effects need to be taken into account. In this report an alternate method is proposed using Gateway materials as an example. This method determines which environmental factor will be dominant at what time (such as contamination or charged particles) and uses that degradation rate for that mission phase. For the next mission phase, the new absorptivity can be used instead of the original BOL absorptivity to determine degradation rate. This approach prevents overestimating optical degradation when considering degradation from interconnected sources.

Brandon Michael Hoffmann↗
NASA NTRS2024

Estimation of End-of-Life Solar Absorptivity for Complex, Multi-Phased Space Missions

Solar absorptivity degradation over time is an important contributor to the thermal performance of a spacecraft at the end of its life. When environments are complex and include many different factors known to impact solar absorptivity degradation, such as UV, charged particles, contamination, or lunar dust coverage, combining data from several different studies can be done to estimate total degradation. While the most conservative way is to stack delta absorptivity from each factor to come up with a total delta, this may be overly conservative for long or complex missions with multiple mission phases. As absorptivity increases the rate of degradation decreases, and synergistic effects need to be taken into account. In this report an alternate method is proposed using Gateway materials as an example. This method determines which environmental factor will be dominant at what time (such as contamination or charged particles) and uses that degradation rate for that mission phase. For the next mission phase, the new absorptivity can be used instead of the original BOL absorptivity to determine degradation rate. This approach prevents overestimating optical degradation when considering degradation from interconnected sources.

thermo-optical properties↗
NASA NTRS1990

A transient plasticity study and low cycle fatigue analysis of the Space Station Freedom photovoltaic solar array blanket

The Space Station Freedom photovoltaic solar array blanket assembly is comprised of several layers of materials having dissimilar elastic, thermal, and mechanical properties. The operating temperature of the solar array, which ranges from -75 to +60 C, along with the material incompatibility of the blanket assembly components combine to cause an elastic-plastic stress in the weld points of the assembly. The weld points are secondary structures in nature, merely serving as electrical junctions for gathering the current. The thermal mechanical loading of the blanket assembly operating in low earth orbit continually changes throughout each 90 min orbit, which raises the possibility of fatigue induced failure. A series of structural analyses were performed in an attempt to predict the fatigue life of the solar cell in the Space Station Freedom photovoltaic array blanket. A nonlinear elastic-plastic MSC/NASTRAN analysis followed by a fatigue calculation indicated a fatigue life of 92,000 to 160,000 cycles for the solar cell weld tabs. Additional analyses predict a permanent buckling phenomenon in the copper interconnect after the first loading cycle. This should reduce or eliminate the pulling of the copper interconnect on the joint where it is welded to the silicon solar cell. It is concluded that the actual fatigue life of the solar array blanket assembly should be significantly higher than the calculated 92,000 cycles, and thus the program requirement of 87,500 cycles (orbits) will be met. Another important conclusion that can be drawn from the overall analysis is that, the strain results obtained from the MSC/NASTRAN nonlinear module are accurate to use for low-cycle fatigue analysis, since both thermal cycle testing of solar cells and analysis have shown higher fatigue life than the minimum program requirement of 87,500 cycles.

Armand, Sasan C.↗
DOE OSTI2025

A Computational Framework to design 3D stiffness gradient acoustic metamaterials for impedance matching

Acoustic waves play a crucial role in various applications, including medical imaging, non-destructive testing, and sonar systems. One of the significant challenges in these applications is impedance matching, which is essential for minimizing reflections and maximizing the transfer of acoustic energy between different media. Acoustic metamaterials offer a promising solution to this challenge. In addition to impedance control, gradient stiffness can enhance structural efficiency and enable spatial control of wave propagation, making it a valuable feature in acoustic metamaterial design. In this pa- per, we present our developed computational method to design 3D stiffness gradient acoustic metamaterials for impedance matching. The key steps in our approach include generating initial designs using a periodic covariance function to provide unit cells that are both periodic on the boundaries and randomly formed inside the unit cell. Furthermore, we integrated manufacturing constraints into the design process, ensuring that the structures are interconnected for fabrication. We propose two computational optimization algorithms: GenUnit, based on a non-dominated sorting genetic algorithm (NSGA-II), and MLMatch, which leverages differentiable machine learning. The two approaches are not separate contributions but complementary com- ponents of a unified framework. GenUnit requires no training data and directly interfaces with physics-based simulations, making it highly accurate but slower for large-scale exploration. In contrast, MLMatch is data-hungry during training but, once trained, enables near-instantaneous inference and broad design-space coverage. Together, they form a hybrid strategy: ML- Match rapidly explores the global design space, and GenUnit provides local refinement with high-fidelity accuracy. This balance between training cost, inference time, and precision is the motivation for including both methods in the same study. We applied this dual-algorithm framework to generate two metallic-based metamaterial designs that match the acoustic impedance of water while exhibiting a controlled gradient in stiffness (from stiff to soft). The stiffness gradient is particularly advantageous in applications where one side of the structure must interface with soft or sensitive surfaces, such as human tissue or delicate components. Here, this work paves the way for improved materials in various acoustic applications, particularly in ultrasound devices, by providing better impedance.

Metamaterial↗
DOE OSTI2024

Unveiling mesoscopic structures in distorted lamellar phases through deep learning-based small angle neutron scattering analysis

Hypothesis: The formation of distorted lamellar phases, distinguished by their arrangement of crumpled, stacked layers, is frequently accompanied by the disruption of long-range order, leading to the formation of interconnected network structures commonly observed in the sponge phase. Nevertheless, traditional scattering functions grounded in deterministic modeling fall short of fully representing these intricate structural characteristics. Our hypothesis posits that a deep learning method, in conjunction with the generalized leveled wave approach used for describing structural features of distorted lamellar phases, can quantitatively unveil the inherent spatial correlations within these phases. Experiments and Simulations: This report outlines a novel strategy that integrates convolutional neural networks and variational autoencoders, supported by stochastically generated density fluctuations, into a regression analysis framework for extracting structural features of distorted lamellar phases from small angle neutron scattering data. To evaluate the efficacy of our proposed approach, we conducted computational accuracy assessments and applied it to the analysis of experimentally measured small angle neutron scattering spectra of AOT surfactant solutions, a frequently studied lamellar system. Findings: The findings unambiguously demonstrate that deep learning provides a dependable and quantitative approach for investigating the morphology of wide variations of distorted lamellar phases. It is adaptable for deciphering structures from the lamellar to sponge phase including intermediate structures exhibiting fused topological features. In conclusion, this research highlights the effectiveness of deep learning methods in tackling complex issues in the field of soft matter structural analysis and beyond.

36 MATERIALS SCIENCE↗
DOE OSTI2024

One-Pot Self-Assembly of Sequence-Controlled Mesoporous Heterostructures via Structure-Directing Agents

Multimaterial heterostructures have led to characteristics surpassing the individual components. Nature controls the architecture and placement of multiple materials through biomineralization of nanoparticles (NPs); however, synthetic heterostructure formation remains limited and generally departs from the elegance of self-assembly. Here, in this study, a class of block polymer structure-directing agents (SDAs) are developed containing repeat units capable of persistent (covalent) NP interactions that enable the direct fabrication of nanoscale porous heterostructures, where a single material is localized at the pore surface as a continuous layer. This SDA binding motif (design rule 1) enables sequence-controlled heterostructures, where the composition profile and interfaces correspond to the synthetic addition order. This approach is generalized with 5 material sequences using an SDA with only persistent SDA-NP interactions (“P-NP 1 –NP 2 ”; NP i = TiO 2 , Nb 2 O 5 , ZrO 2 ). Expanding these polymer SDA design guidelines, it is shown that the combination of both persistent and dynamic (noncovalent) SDA-NP interactions (“PD-NP 1 –NP 2 ”) improves the production of uniform interconnected porosity (design rule 2). The resulting competitive binding between two segments of the SDA (P- vs D-) requires additional time for the first NP type (NP 1 ) to reach and covalently attach to the SDA (design rule 3). The combination of these three design rules enables the direct self-assembly of heterostructures that localize a single material at the pore surface while preserving continuous porosity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

High Energy Physics Network Requirements Review: Two-Year Update

The Energy Sciences Network (ESnet) is the high-performance network user facility for the US Department of Energy (DOE) Office of Science (SC) and delivers highly reliable data transport capabilities optimized for the requirements of data-intensive science. In essence, ESnet is the circulatory system that enables the DOE science mission by connecting all its laboratories and facilities in the US and abroad. ESnet is funded and stewarded by the Advanced Scientific Computing Research (ASCR) program and managed and operated by the Scientific Networking Division at Lawrence Berkeley National Laboratory (LBNL). ESnet is widely regarded as a global leader in the research and education networking community. ESnet interconnects DOE national laboratories, user facilities, and major experiments so that scientists can use remote instruments and computing resources as well as share data with collaborators, transfer large datasets, and access distributed data repositories. ESnet is specifically built to provide a range of network services tailored to meet the unique requirements of the DOE’s data-intensive science. In July 2023, the Energy Sciences Network (ESnet) and the High Energy Physics program (HEP) of the DOE SC organized an interim ESnet requirements review of HEP-supported activities, to follow up on the work started during the 2020 HEP Network Requirements Review. Preparation for these events included checking back with the key stakeholders: program and facility management, research groups, and technology providers. Each stakeholder group was asked to prepare updates to their previously submitted case study documents, so that ESnet could update the understanding of any changes to the current, near-term, and long-term status, expectations, and processes that will support the science activities of the program.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Calibration of a mesoscale tritium transport model for ceramic breeder materials in TMAP8 using experimental data

Due to the scarcity of the long-term external tritium supply, lithium-containing breeder materials are used in the blanket of fusion reactors to produce tritium faster than the deuterium-tritium fusion reaction consumes it. A cellular breeder is a promising material with higher lithium density and thermal conductivity than conventional ceramic pebbles and enhanced tritium extraction with interconnected pores. Although several experimental and modeling efforts have improved our understanding of tritium transport, the exact mechanisms governing tritium release from breeder materials are still unknown. As a result, current models cannot reliably assess the tritium breeding capabilities of cellular breeder materials. This work presents a tritium transport multiphysics model and calibrates it using experimental data of deuterium absorption and desorption from cellular breeder materials at different temperatures and pressures. This model accounts for ceramic and pore diffusion, trapping and detrapping, and several surface reactions at the pore surface. After calibrating the model and performing sensitivity analysis, we discuss pre-dominant mechanisms governing tritium release from cellular breeder materials. The model is part of the Tritium Migration Analysis Program [TMAP8], a multiscale, multiphysics framework for tritium transport based on the finite element multiphysics framework MOOSE. This study demonstrates some of TMAP8’s capabilities and provides insight into the mechanisms governing tritium transport in cellular ceramic breeder materials.

08 HYDROGEN↗