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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 OSTI2022

Spectral form factor in sparse SYK models

We investigate the spectral form factor of the sparse Sachdev-Ye-Kitaev model. We use numerical methods to establish that at intermediate times the connected part of the spectral form factor is the dominant one. These connected contributions arise from fluctuations around the disconnected geometry, not from a new saddle point. A similar effect was previously conjectured in SYK but required a value of N out of reach of current numerical simulations.

2D Gravity↗
DOE OSTI2022

Athermal glass work at the nanoscale: Engineered electron-beam-induced viscoplasticity for mechanical shaping of brittle amorphous silica

Amorphous silica deforms viscoplastically at elevated temperatures, which is common for brittle glasses. The key mechanism of viscoplastic deformation involves interatomic bond switching, which is thermally activated. Here, for this study, we precisely control the mechanical shaping of brittle amorphous silica at the nanoscale via engineered electron–matter interactions without heating. We observe a ductile plastic deformation of amorphous silica under a focused scanning electron beam with low acceleration voltages (few to tens of kilovolts) during in-situ compression studies, with unique dependence on the acceleration voltage and beam current. By simulating the electron–matter interaction, we show that the deformation of amorphous silica depends strongly on the volume where inelastic scattering occurs. The electron–matter interaction via e-beam irradiation alters the Si–O interatomic bonds, enabling the high-temperature deformation behavior of amorphous silica to occur athermally. Finally, by systematically controlling the electron–matter interaction volume, it is possible to mechanically shape the brittle amorphous silica on a small scale at room temperature to a level comparable to glass shaping at high temperatures. The findings can be extended to develop new fabrication processes for nano- and microscale brittle glasses.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A machine learning approach to predict thermal expansion of complex oxides

Although it is of scientific and practical importance, the state-of-the-art of predicting the thermal expansion of oxides over broad temperature and composition ranges by physics-based atomistic simulations is currently limited to qualitative agreements. We present an emerging machine learning (ML) approach to accurately predict the thermal expansion of cubic oxides with a dataset consisting of experimentally measured lattice parameters while using the metal cation polyhedron and temperature as descriptors. High-fidelity ML models that can accurately predict temperature- and composition-dependent lattice parameters of cubic oxides with isotropic thermal expansions have been successfully trained. The ML-predicted thermal expansions of oxides not included in the training dataset have shown good agreement with available experiments. The limitations of the current approach and challenges to go beyond cubic oxides with isotropic thermal expansion are also briefly discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Thickness threshold study of polyaniline-based lightning strike protection coating for carbon/glass fiber reinforced polymer composites

Different polyaniline (PANI) based lightning strike protection (LSP) coating thicknesses were tested against simulated lightning strike tests to evaluate the threshold thickness of the coating. A series of lightning strike tests were performed on carbon/glass fiber reinforced polymer (CFRP/GFRP) composites subjected to simulated lightning currents ranging from 40 to 100 kA. Five LSP-coated specimens were considered herein: two CFRP and three GFRP composites. A minimum of ~ 345 μm thick PANI-based LSP coating on CFRP and GFRP composites under a 40 kA peak current retained 83 % and 100 % residual strength, respectively. Additionally, GFRP specimens tested against 60 and 100 kA peak currents exhibited 100 % residual strength. Finally, this study proposes that a PANI-based LSP coating is suitable for protecting GFRP composites, while the careful design is necessary for CFRP composites to avoid any catastrophic failure.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A New Ecosystem Model for Arctic Phytoplankton Phenology From Ice‐Covered to Open‐Water Periods: Implications for Future Sea Ice Retreat Scenarios

Abstract To predict ecosystem change in the Arctic Ocean, understanding Arctic phytoplankton phenology is essential. We develop a marine ecosystem model focusing on phytoplankton dynamics and the competition for multiple resources based on knowledge from in situ data obtained in the Chukchi Sea. The model is designed to include the unique ecological characteristics of the Arctic Ocean. To the best of our knowledge, this is the first model successfully simulating the current paradigm for Arctic phytoplankton phenology, including both under‐ice blooms and succession of phytoplankton groups. Sensitivity experiments show that the dominance of diatoms can be sustained by lateral transport of a high‐silicate water mass (Pacific Winter Water). Experiments for future scenarios show that sea ice retreat drives a decrease in large diatoms and an increase in the other relatively small non‐diatom groups. These results suggest that dominant phytoplankton groups can be shifted from diatoms to non‐diatoms under ongoing Arctic Ocean sea ice retreat.

Choi, Jang‐Geun↗
DOE OSTI2023

Field-free spin-orbit torque switching assisted by in-plane unconventional spin torque in ultrathin [Pt/Co] N

Electrical manipulation of magnetization without an external magnetic field is critical for the development of advanced non-volatile magnetic-memory technology that can achieve high memory density and low energy consumption. Several recent studies have revealed efficient out-of-plane spin-orbit torques (SOTs) in a variety of materials for field-free type-z SOT switching. Here, we report on the corresponding type-x configuration, showing significant in-plane unconventional spin polarizations from sputtered ultrathin [Pt/Co] N , which are either highly textured on single crystalline MgO substrates or randomly textured on SiO 2 coated Si substrates. The unconventional spin currents generated in the low-dimensional Co films result from the strong orbital magnetic moment, which has been observed by X-ray magnetic circular dichroism (XMCD) measurement. The x-polarized spin torque efficiency reaches up to −0.083 and favors complete field-free switching of CoFeB magnetized along the in-plane charge current direction. Micromagnetic simulations additionally demonstrate its lower switching current than type-y switching, especially in narrow current pulses. Our work provides additional pathways for electrical manipulation of spintronic devices in the pursuit of high-speed, high-density, and low-energy non-volatile memory.

42 ENGINEERING↗
DOE OSTI2022

Physics-informed machine learning with differentiable programming for heterogeneous underground reservoir pressure management

Abstract Avoiding over-pressurization in subsurface reservoirs is critical for applications like CO $$_2$$ 2 sequestration and wastewater injection. Managing the pressures by controlling injection/extraction are challenging because of complex heterogeneity in the subsurface. The heterogeneity typically requires high-fidelity physics-based models to make predictions on CO $$_2$$ 2 fate. Furthermore, characterizing the heterogeneity accurately is fraught with parametric uncertainty. Accounting for both, heterogeneity and uncertainty, makes this a computationally-intensive problem challenging for current reservoir simulators. To tackle this, we use differentiable programming with a full-physics model and machine learning to determine the fluid extraction rates that prevent over-pressurization at critical reservoir locations. We use DPFEHM framework, which has trustworthy physics based on the standard two-point flux finite volume discretization and is also automatically differentiable like machine learning models. Our physics-informed machine learning framework uses convolutional neural networks to learn an appropriate extraction rate based on the permeability field. We also perform a hyperparameter search to improve the model’s accuracy. Training and testing scenarios are executed to evaluate the feasibility of using physics-informed machine learning to manage reservoir pressures. We constructed and tested a sufficiently accurate simulator that is 400 000 times faster than the underlying physics-based simulator, allowing for near real-time analysis and robust uncertainty quantification.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Experimental Validation of Thermal Scattering Evaluations

In order to test the performance of new neutron thermal scattering law (TSL) evaluations it is desirable to have experimental data that is highly sensitive to the TSL and provides high fidelity information on the energy dependent performance of TSL evaluations. Three relevant experiments are discussed including: accurate thermal total cross section measurements, thermal neutron die-away experiments, and neutron leakage experiments. The experimental setups and results are reviewed, and examples provided for some moderators including polyethylene, Plexiglas, and YHx. For the experiments preformed thus far, there is generally good agreement between the measured total cross section and simulations using current TSL evaluations, however in certain energy ranges differences were observed. Similarly, neutron die-away and leakage measurements for samples at room temperature are in good agreement with data computed from TSLs, however leakage measurements for polyethylene at 29K show discrepancies with TSL evaluations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Experimental observations of detached bow shock formation in the interaction of a laser-produced plasma with a magnetized obstacle

The magnetic field produced by planets with active dynamos, like the Earth, can exert sufficient pressure to oppose supersonic stellar wind plasmas, leading to the formation of a standing bow shock upstream of the magnetopause, or pressure-balance surface. Scaled laboratory experiments studying the interaction of an inflowing solar wind analog with a strong, external magnetic field are a promising new way to study magnetospheric physics and to complement existing models, although reaching regimes favorable for magnetized shock formation is experimentally challenging. This paper presents experimental evidence of the formation of a magnetized bow shock in the interaction of a supersonic, super-Alfvenic plasma with a strongly magnetized obstacle at the OMEGA laser facility. The solar wind analog is generated by the collision and subsequent expansion of two counterpropagating, laser-driven plasma plumes. The magnetized obstacle is a thin wire, driven with strong electrical currents. Hydrodynamic simulations using the FLASH code predict that the colliding plasma source meets the criteria for bow shock formation. Spatially resolved, optical Thomson scattering measures the electron number density, and optical emission lines provide a measurement of the plasma temperature, from which we infer the presence of a fast magnetosonic shock far upstream of the obstacle. Proton images provide a measure of large-scale features in the magnetic field topology, and reconstructed path-integrated magnetic field maps from these images suggest the formation of a bow shock upstream of the wire and as a transient magnetopause. Finally, we compare features in the reconstructed fields to two-dimensional MHD simulations of the system.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

A trapping tolerant drain current based temperature measurement of β -Ga 2 O 3 MOSFETs

The drain current temperature dependence is an efficient way to determine the channel temperature in semiconductor devices; however, it has been challenging to use due to the potential interference of trapping effects. A trapping tolerant method is proposed, illustrated here for Ga 2 O 3 MOSFETs, making in situ temperature measurements possible, allowing a thermal resistance of 59 K∙mm/W to be measured in Ga 2 O 3 MOSFETs. However, neglecting the effect of trapping causes an error of ~15% in the channel temperature measured using the drain current. 3D simulations show that the measured channel temperature is the average temperature value between source and drain contact.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Collective neural network behavior in a dynamically driven disordered system of superconducting loops

Collective properties of complex systems composed of many interacting components such as neurons in our brain can be modeled by artificial networks based on disordered systems. We show that a disordered neural network of superconducting loops with Josephson junctions can exhibit computational properties like categorization and associative memory in the time evolution of its state in response to information from external excitations. Superconducting loops can trap multiples of fluxons in many discrete memory configurations defined by the local free energy minima in the configuration space of all possible states. A memory state can be updated by exciting the Josephson junctions to fire or allow the movement of fluxons through the network as the current through them surpasses their critical current thresholds. Simulations performed with a lumped element circuit model of a 4-loop network show that information written through excitations is translated into stable states of trapped flux and their time evolution. Experimental implementation on a high-Tc superconductor YBCO-based 4-loop network shows dynamically stable flux flow in each pathway characterized by the correlations between junction firing statistics. Neural network behavior is observed as energy barriers separating state categories in simulations in response to multiple excitations, and experimentally as junction responses characterizing different flux flow patterns in the network. The state categories that produce these patterns have different temporal stabilities relative to each other and the excitations. This provides strong evidence for time-dependent (short-to-long-term) memories, that are dependent on the geometrical and junction parameters of the loops, as described with a network model.

Josephson junctions↗
DOE OSTI2021

Core formation in high-z massive haloes: heating by post-compaction satellites and response to AGN outflows

ABSTRACT Observed rotation curves in star-forming galaxies indicate a puzzling dearth of dark matter in extended flat cores within haloes of mass ≥1012M⊙ at z ∼ 2. This is not reproduced by current cosmological simulations, and supernova-driven outflows are not effective in such massive haloes. We address a hybrid scenario where post-compaction merging satellites heat up the dark-matter cusps by dynamical friction, allowing active galactic nucleus (AGN)-driven outflows to generate cores. Using analytic and semi-analytic models (SatGen), we estimate the dynamical friction heating as a function of satellite compactness for a cosmological sequence of mergers. Cosmological simulations (VELA) demonstrate that satellites of initial virial masses >1011.3M⊙, which undergo wet compactions, become sufficiently compact for significant heating. Constituting a major fraction of the accretion on to haloes ≥1012M⊙, these satellites heat up the cusps in half a virial time at z ∼ 2. Using a model for outflow-driven core formation (CuspCore), we demonstrate that the heated dark-matter cusps develop extended cores in response to removal of half the gas mass, while the more compact stellar systems remain intact. The mergers keep the dark matter hot, while the gas supply, fresh and recycled, is sufficient for the AGN outflows. AGNs indeed become effective in haloes ≥1012M⊙, where the black hole growth is no longer suppressed by supernovae and its compaction-driven rapid growth is maintained by a hot circumgalactic medium. For simulations to reproduce the dynamical friction effects, they should resolve the compaction of the massive satellites and avoid artificial tidal disruption. AGN feedback could be boosted by clumpy black hole accretion and clumpy response to AGN.

Dekel, Avishai↗
DOE OSTI2023

Alpha heating of indirect-drive layered implosions on the National Ignition Facility

We report in order to understand how close current layered implosions in indirect-drive inertial confinement fusion are to ignition, it is necessary to measure the level of alpha heating present. To this end, pairs of experiments were performed that consisted of a low-yield tritium–hydrogen–deuterium (THD) layered implosion and a high-yield deuterium–tritium (DT) layered implosion to validate experimentally current simulation-based methods of determining yield amplification. The THD capsules were designed to reduce simultaneously DT neutron yield (alpha heating) and maintain hydrodynamic similarity with the higher yield DT capsules. The ratio of the yields measured in these experiments then allowed the alpha heating level of the DT layered implosions to be determined. The level of alpha heating inferred is consistent with fits to simulations expressed in terms of experimentally measurable quantities and enables us to infer the level of alpha heating in recent high-performing implosions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Impact of the Transformer Magnetizing Inductance on the Performance of the Dual-Active Bridge Converter

The magnetizing inductance of the high-frequency transformer in the dual-active bridge (DAB) converter is usually assumed to be much larger than its leakage inductance, thereby the magnetizing current can be negligible. However, ignoring the magnetizing current will lead to an error in the DAB converter design process. This paper analyzes the operation and performance of the DAB converter for a general case in which the transformer magnetizing inductance is taken into consideration. The analysis shows that the magnetizing inductance impacts the soft-switching region, the power transfer capability, and the leakage inductor current. A simulation case study is provided to verify the analysis. A DAB converter prototype is built to experimentally validate the analysis as well.

Yin, Shiyuan↗
DOE OSTI2025

Comparative Evaluation of the Single-Phase Shift and Extended-Phase Shift Control for Isolated DC-DC Converter

Abstract: This paper presents a comparative evaluation of the Single-Phase Shift (SPS) and Extended-Phase Shift (EPS) controls for the isolated DC-DC Converter. The analysis is based on the power regulation range, flexibility of operation, current stress on power devices, system efficiency while focusing on the issue of backflow power, control complexity, design and implementation overhead, and stability of the entire system. It is also examined how the backflow influences power circulation and increases current stress. Here, the Dual Active Bridge (DAB) Converter is employed to assess the performance of the control methods. Compared to SPS control, EPS offers a wider power regulation range, greater flexibility, lower current stress, and better system efficiency. However, EPS has increased control complexity, design and implementation overhead, and often requires sophisticated feedback control loops. The comparison is made through mathematical modeling of power transfer, backflow, and current stress. Simulation results validate the comparative analysis presented.

Amir, Aamir [The University of Alabama (UA)]↗
DOE OSTI2024

Deep Learning-enhanced Block-Diagram Modeling of Solar Power Systems

Data-driven models of power system inverter-based resources are desired to run simulations faster than with detailed electromagnetic transient models, to hide proprietary design details, to support control system design applications, and to aggregate the effects of distributed energy resources. This paper applies a customized Hammerstein Wiener framework to train block diagram models from thousands of electromagnetic transient simulations or experimental test records. The block diagram models integrate with larger grid simulations as voltagecontrolled current sources or current-controlled voltage sources for several simulators. Guidelines for block architecture and training are presented. Three-phase balanced, three-phase unbalanced, and single-phase examples all achieve an acceptable root mean square error of no more than 0.05 per-unit.

Mcdermott, Thomas E. [Private consulting company]↗
DOE OSTI2021

Finite Element Analysis (FEA) for Water-Foam Fracturing of Granite Rock

In addition to the foam data that were obtained from literature and that were collected from the current study, simulation data was also generated from finite element analysis (FEA) conducted in this study using COMSOL Multiphysics software. The FEA models were built to simulate the experiments conducted at Oak Ridge National Laboratory (ORNL) on cement and granite samples. In these FEA models, temperature was kept at ambient while the pressure profile resembled the loading conditions during the ORNL experiments, where pressure was either monotonically increased or applied cyclically. The cement material was used as a model material and was used to study Von Mises stress and tensile stress distribution for different bore hole length geometry using a parametric sweep with water as fracturing fluid using solid-fluid interaction module. For the granite material, FEA models were developed for stress analysis of cylindrical samples with water or foam fluids. The solid mechanics module in COMSOL was implemented to solve for Von Mises stress and tensile stress. The fluid-structure interaction module was implemented to solve for water-foam interaction on granite cylinder with addition of fluid-loading on structure, i.e., large deformation in solid mechanics with no impact on fluid deformation. Foam was considered as a pseudo single-phase compressible fluid for which material properties were calculated from water and gas (nitrogen) phases. The density of foam is calculated as a function of the densities of water and nitrogen, while viscosity is a function of temperature. Four types of FEA analyses were modelled: 1. Monotonic injection with water 2. Monotonic injection with foam 3. Cyclic injection with water 4. Cyclic injection with foam All the COMSOL files are converted to a zip file which is save in .mph.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

popclass: A Python Package for Classifying Microlensing Events

popclass is a Python package that provides a flexible, probabilistic framework for classifying the lens of a gravitational microlensing event. Gravitational microlensing occurs when a massive foreground object (e.g., a star, white dwarf or black hole) passes in front of and lenses the light from a distant background source. This causes an apparent brightening, and shift in position, of the background source. In most cases, characteristics of the microlensing signal do not contain enough information to definitively identify the lens type. Different lens types lie in different but overlapping regions of the characteristics of the microlensing signal. For example, black holes tend to be more massive than stars and therefore cause microlensing signals that are longer. Current Galactic simulations enable us to predict where different lens types lie in the observational space and can therefore be used to classify events (e.g., Lam et al., 2020). popclass allows the user to match the characteristics of a microlensing signal with a simulation of the Galaxy to calculate lens type probabilities for the event (see Figure 1). Constraints on any microlensing signal properties and any Galactic model can be used. popclass comes with an interface to ArviZ (Kumar et al., 2019) and PyMultiNest (Buchner et al., 2014) for microlensing signal constraints, as well as pre-loaded Galactic models, plotting functionality, and methods to quantify the classification uncertainty. The probabilistic framework for popclass was developed in Perkins et al. (2024), used in Fardeen et al. (2024) and has been applied to classifying events in Kaczmarek et al. (2025).

97 MATHEMATICS AND COMPUTING↗