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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

Mean-field theory for the structure of strongly interacting active liquids

Active systems, which are driven out of equilibrium by local non-conservative forces, exhibit unique behaviors and structures with potential utility for the design of novel materials. An important and difficult challenge along the path toward this goal is to precisely predict how the structure of active systems is modified as their driving forces push them out of equilibrium. Here, we use tools from liquid-state theories to approach this challenge for a classic minimal active matter model. First, we construct a nonequilibrium mean-field framework that can predict the structure of systems of weakly interacting particles. Second, motivated by equilibrium solvation theories, we modify this theory to extend it with surprisingly high accuracy to systems of strongly interacting particles, distinguishing it from most existing similarly tractable approaches. Furthermore, our results provide insight into spatial organization in strongly interacting out-of-equilibrium systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1992

Simulation model of a twin-tail, high performance airplane

The mathematical model and associated computer program to simulate a twin-tailed high performance fighter airplane (McDonnell Douglas F/A-18) are described. The simulation program is written in the Advanced Continuous Simulation Language. The simulation math model includes the nonlinear six degree-of-freedom rigid-body equations, an engine model, sensors, and first order actuators with rate and position limiting. A simplified form of the F/A-18 digital control laws (version 8.3.3) are implemented. The simulated control law includes only inner loop augmentation in the up and away flight mode. The aerodynamic forces and moments are calculated from a wind-tunnel-derived database using table look-ups with linear interpolation. The aerodynamic database has an angle-of-attack range of -10 to +90 and a sideslip range of -20 to +20 degrees. The effects of elastic deformation are incorporated in a quasi-static-elastic manner. Elastic degrees of freedom are not actively simulated. In the engine model, the throttle-commanded steady-state thrust level and the dynamic response characteristics of the engine are based on airflow rate as determined from a table look-up. Afterburner dynamics are switched in at a threshold based on the engine airflow and commanded thrust.

Buttrill, Carey S.↗
NASA NTRS1994

IR excitation of contaminant water by oxygen for the space shuttle at low Earth orbit altitude

As the water outgas of a space shuttle passes through the rarefied atmosphere at orbital altitude, collisions occur between the gases with sufficient energy to excite infrared-active water molecules to various vibrational and rotational states. An infrared contaminant model (IR model) has been developed to study the shuttle-induced excitation and emission of water molecules outgassed from the space shuttle. The focus of the first application of the model is translation-to-vibration (T-V) energy transfer since estimates suggest that this process should dominate the production of vibrationally excited H2O under typical low Earth orbit conditions. Using the velocity and position distribution functions of interacting neutral gases obtained from a neutral gases interaction model, the spatial distributions of excitation and IR radiation from contaminant water are computed, and typical results are presented. Infrared spectral data (450 - 2500/cm), measured by the Cryogenic Infrared Radiance Instrumentation for Shuttle (CIRRIS-1A) sensor on STS-39 (April 28 to May 6, 1991) at an altitude near 265 km, are used to test model predictions. The dependence of the radiant emission structure and brightness on outgassing rates and altitudes is discussed. The time history of the contaminant water outgassing rate is inferred for STS-39, and it is compared with the mass-spectrometer-based results for STS-4 (June 26 to July 4, 1982). Also, estimates of H2O column density at mission elapsed time (MET) 50 hours are compared for missions STS-2, STS-3, STS-4, and STS-39.

Zhou, D. K.↗
DOE OSTI2023

Observation and Modeling of the Thermal Runaway of High-Capacity Pouch Cells Due to an Internal Short Induced by an Indenter

Owing to the complexity of coupling mechanical and electrical solvers for finite element analysis (FEA) of mechanical abuse of a battery, the simulation should be performed by incorporating a local short circuit model activated based on the status of battery elements. However, the approach should also consider various other conditions of the battery simulated, such as the initial state of charge (SOC), for precise simulations of the internal short. This study proposes an approach developed with a mechanical model and single-particle battery model, along with a reaction kinetics model for thermal abuse using LS-DYNA. Several key parameters were selected, such as the activation criteria, kinetic abuse and element integration points during the internal short circuit induced by the indenter. The impact of these key parameters in the FEA on thermal runaway response for various initial SOCs from 25 to 100 % were analyzed. The FEA results obtained were compared against experimental results with various parameters such as activation criterion of internal short, kinetic abuse based on accelerating rate calorimetry (ARC) data. Finally, the root causes of the discrepancy between the FEA and experimental results are discussed regarding integration point what solver can make difference during calculation.

ENERGY STORAGE↗
DOE OSTI2025

A Model Intercomparison Study of Aerosol‐Cloud‐Turbulence Interactions in a Cloud Chamber: 1. Model Results

This study presents the first model intercomparison of aerosol‐cloud‐turbulence interactions in a controlled cloudy Rayleigh‐Bénard Convection chamber environment, utilizing the Pi Chamber at Michigan Technological University. We analyzed simulated cloud chamber‐averaged statistics of microphysics and thermodynamics in a warm‐phase, cloudy environment under steady‐state conditions at varying aerosol injection rates. Simulation results from seven distinct models (DNS, LES, and a 1D turbulence model) were compared. Our findings demonstrate that while all models qualitatively capture observed trends in droplet number concentration, mean radius, and droplet size distributions at both high and low aerosol injection rates, significant quantitative differences were observed. Notably, droplet number concentrations varied by over two orders of magnitude between models for the same injection rates, indicating sensitivities to the model treatments in droplet activation and removal and wall fluxes. Furthermore, inconsistencies in vertical relative humidity profiles and in achieving steady‐state liquid water content suggest the need for further investigation into the mechanisms driving these variations. Despite these discrepancies, the models generally reproduced consistent power‐law relationships between the microphysical variables. This model intercomparison underscores the importance of controlled cloud chamber experiments for validating and improving cloud microphysical parameterizations. Recommendations for future modeling studies are also highlighted, including constraining wall conditions and processes, investigating droplet/aerosol removal (including sidewall losses), and conducting simplified experiments to isolate specific processes contributing to model divergence and reduce model uncertainties.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2020

An Obscured, Seyfert 2-like State of the Stellar-mass Black Hole GRS 1915+105 Caused by Failed Disk Winds

We report on Chandra grating spectra of the stellar-mass black hole GRS 1915+105 obtained during a novel, highly obscured state. As the source entered this state, a dense, massive accretion disk wind was detected through strong absorption lines. Photoionization modeling indicates that it must originate close to the central engine, orders of magnitude from the outer accretion disk. Strong, nearly sinusoidal flux variability in this phase yielded a key insight: the wind is blueshifted when its column density is relatively low, but redshifted as it approaches the Compton-thick threshold. At no point does the wind appear to achieve the local escape velocity; in this sense, it is a “failed wind.” Later observations suggest that the disk ultimately fails to keep even the central engine clear of gas, leading to heavily obscured and Compton-thick states characterized by very strong Fe K emission lines. Indeed, these later spectra are successfully described using models developed for obscured active galactic nuclei (AGNs). We discuss our results in terms of the remarkable similarity of GRS 1915+105 deep in its “obscured state” to Seyfert 2 and Compton-thick AGNs, and we explore how our understanding of accretion and obscuration in massive black holes is impacted by our observations.

Black holes↗
DOE OSTI2026

Multi-physics Preconditioning for Thermally Activated Batteries

Thermal batteries, also known as molten-salt batteries, are single-use reserve power systems activated by pyrotechnic heat generation, which transitions the solid electrolyte into a molten state. The simulation of these batteries relies on multiphysics modeling to evaluate performance and behavior under various conditions. This paper presents advancements in scalable preconditioning strategies for the Thermally Activated Battery Simulator (TABS) tool, enabling efficient solutions to the coupled electrochemical systems that dominate computational costs in thermal battery simulations. We propose a hierarchical block Gauss-Seidel preconditioner implemented through the Teko package in Trilinos, which effectively addresses the challenges posed by tightly coupled physics, including charge transport, porous flow, and species diffusion. The preconditioner leverages scalable subblock solvers, including smoothed aggregation algebraic multigrid (SA-AMG) methods and domain-decomposition techniques, to achieve robust convergence and parallel scalability. Strong and weak scaling studies demonstrate the solver’s ability to handle problem sizes up to 51.3 million degrees of freedom on 2048 processors, achieving near sub-second setup and solve times for the end-to-end electrochemical solve. These advancements significantly improve the computational efficiency and turnaround time of thermal battery simulations, paving the way for higher-resolution models and enabling the transition from 2D axisymmetric to full 3D simulations.

25 ENERGY STORAGE↗
DOE OSTI2023

Advancing energy storage through solubility prediction: leveraging the potential of deep learning

Solubility prediction plays a crucial role in energy storage applications, such as redox flow batteries, because it directly affects the efficiency and reliability. Researchers have developed various methods that utilize quantum calculations and descriptors to predict the aqueous solubilities of organic molecules. Notably, machine learning models based on descriptors have shown promise for solubility prediction. As deep learning tools, graph neural networks (GNNs) have emerged to capture complex structure–property relationships for material property prediction. Specifically, MolGAT, a type of GNN model, was designed to incorporate n-dimensional edge attributes, enabling the modeling of intricacies in molecular graphs and enhancing the prediction capabilities. In a previous study, MolGAT successfully screened 23 467 promising redox-active molecules from a database of over 500 000 compounds, based on redox potential predictions. This study focused on applying the MolGAT model to predict the aqueous solubility (log S) of a broad range of organic compounds, including those previously screened for redox activity. The model was trained on a diverse sample of 8494 organic molecules from AqSolDB and benchmarked against literature data, demonstrating superior accuracy compared with other state of the art graph-based and descriptor-based models. Subsequently, the trained MolGAT model was employed to screen redox-active organic compounds identified in the first phase of high-throughput virtual screening, targeting favorable solubility in energy storage applications. The second round of screening, which considered solubility, yielded 12 332 promising redox-active and soluble organic molecules suitable for use in aqueous redox flow batteries. Thus, the two-phase high-throughput virtual screening approach utilizing MolGAT, specifically trained for redox potential and solubility, is an effective strategy for selecting suitable intrinsically soluble redox-active molecules from extensive databases, potentially advancing energy storage through reliable material development. This indicates that the model is reliable for predicting the solubility of various molecules and provides valuable insights for energy storage, pharmaceutical, environmental, and chemical applications.

25 ENERGY STORAGE↗
DOE OSTI2026

Facet-Dependent Water Inhibition of Alkanol Dehydration on TiO2 via Distinct Water–Alkanol Complexes

Water is ubiquitous in biomass-derived feeds, yet its molecular impact on oxygen-elimination reactions remains poorly understood, particularly for catalysts exposing different facets. Here, we utilize well-defined TiO2 nanocrystals with dominant (101) and (001) facets to reveal a pronounced facet-dependent effect of water, where inhibition for dehydration of isopropanol (IPA) on the TiO2(001) surface is about four times more severe than TiO2(101). Through a combination of in situ solid state NMR, in situ infrared spectroscopy, kinetics studies, and theoretical calculations, we demonstrate that this disparity arises from the formation of distinct alkanol-water complex intermediates. On TiO2(001), IPA undergoes dissociative adsorption to form an isopropoxide-H2O complex that readily drives the surface into a complex-dominated regime. This pathway increases the activation barrier for C–H cleavage by 40 kJ mol-1 by inducing a disordered transition state. In contrast, TiO2(101) favors molecular IPA adsorption with weak hydrogen bonding to water, resulting in a smaller complex formation constant and a much smaller activation barrier increase (25 kJ mol-1). By quantitatively linking facet-dependent complex coverage to transition-state destabilization, this work moves beyond simple site-blocking models and provides a conceptual framework for designing catalysts that remain active in water-containing environments

Hu, Wenda↗
DOE OSTI2023

Data-driven prediction of α IIb β 3 integrin activation paths using manifold learning and deep generative modeling

The integrin heterodimer is a transmembrane protein critical for driving cellular process and is a therapeutic target in the treatment of multiple diseases linked to its malfunction. Activation of integrin involves conformational transitions between bent and extended states. Some of the conformations that are intermediate between bent and extended states of the heterodimer have been experimentally characterized, but the full activation pathways remain unresolved both experimentally due to their transient nature and computationally due to the challenges in simulating rare barrier crossing events in these large molecular systems. An understanding of the activation pathways can provide new fundamental understanding of the biophysical processes associated with the dynamic interconversions between bent and extended states and unveil new putative therapeutic targets. In this work, we apply nonlinear manifold learning to coarse-grained molecular dynamics simulations of bent, extended, and two intermediate states of αI I b β3 integrin to learn a low-dimensional embedding of the configurational phase space. We then train deep generative models to learn an inverse mapping between the low-dimensional embedding and high-dimensional molecular space and use these models to interpolate the molecular configurations constituting the activation pathways between the experimentally characterized states. Furthermore, this work furnishes plausible predictions of integrin activation pathways and reports a generic and transferable multi-scale technique to predict transition pathways for biomolecular systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Distinguishing homolytic vs heterolytic bond dissociation of phenylsulfonium cations with localized active space methods

Modeling chemical reactions with quantum chemical methods is challenging when the electronic structure varies significantly throughout the reaction and when electronic excited states are involved. Multireference methods, such as complete active space self-consistent field (CASSCF), can handle these multiconfigurational situations. However, even if the size of the needed active space is affordable, in many cases, the active space does not change consistently from reactant to product, causing discontinuities in the potential energy surface. The localized active space SCF (LASSCF) is a cheaper alternative to CASSCF for strongly correlated systems with weakly correlated fragments. The method is used for the first time to study a chemical reaction, namely the bond dissociation of a mono-, di-, and triphenylsulfonium cation. LASSCF calculations generate smooth potential energy scans more easily than the corresponding, more computationally expensive CASSCF calculations while predicting similar bond dissociation energies. Furthermore, our calculations suggest a homolytic bond cleavage for di- and triphenylsulfonium and a heterolytic pathway for monophenylsulfonium.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRSDate not supplied

Extravehicular Mobility Unit System-Level Model (SINDA EMU) Usage for Operational Mitigations in Support of US EVA 80

During United States Extravehicular Activity 80 (US EVA 80), water was observed in the helmet of an Extravehicular Mobility Unit (EMU) during cabin repressurization. Through a comparative analysis and Test, Teardown, and Evaluation (TT&E) of this EMU, the most likely cause of the US EVA 80 water failure was determined to be sublimator carryover caused by a comparatively high latent load (water vapor production by the crewmember). High latent load can be reduced by the crewmember adjusting the thermal control valve (TCV) setting on the EMU to prevent the onset of significant sweating. To reduce the risk of high latent load leading to water in the helmet, a potential warning system was developed using the Systems Improved Numerical Differencing Analyzer EMU model (SINDA EMU). The goal of this warning system is to alert the crewmember when they are producing a high latent load and recommend adjustment of the TCV to increase cooling. This warning system was designed to ensure high risk conditions are avoided while simultaneously preventing a system that warns the crewmember too frequently. Theoretical tests of the warning system through modeling calculated that if the warning system were used during US EVA 80, the total latent load could have been reduced by up to 33% which would have significantly reduced the risk of water in the helmet. This analysis also investigated the effectiveness of the warning system on EVAs that occurred after US EVA 80.

Noah Andersen↗
NASA NTRS1990

The longitude dependence of the dayside F region trough - A detailed model-observation comparison

The nighttime main F-region trough extends into the sunlit afternoon sector. This trough feature exhibits both a strong magnetic-activity dependence and a longitude (UT) dependence. Whalen (1987), using IGY ionosonde data, showed that both of these effects are readly extracted from f0F2 observations. This study shows that the longitude effect is the same as that contained in the Utah State University time-dependent ionospheric model. It arises from the offset of the geomagnetic axis from the geographic axis. The magnetic-activity dependency is associated with the westward convection in the afternoon sector. It is also contained in the ionospheric model via the empirical magnetospheric convection model.

Sojka, J. J.↗
DOE OSTI2025

Primary material supply configurations and domestic recycling for cost-effective battery material production in the US

Battery cathode active material costs hinge on regionally concentrated, price-volatile metal supply. Here. we construct a regional facility-level cost model based on over 80 global lithium, cobalt, and nickel mines, refineries, and battery-grade material plants. Our model yields aggregated lithium, nickel, manganese, and cobalt production material costs from 392 region-based supply configurations for five different cathode active materials. Focusing on the United States, all-domestic supply is 9–34% costlier than global average, increasing by cobalt content, while these shortfalls can be overcome by selective low-cost material imports. Furthermore, we analyze costs of two U.S.-based recycling facilities from primary data and techno-economic modelling and compare resulting cathode active material-level costs to primary supply. Although it is still significantly higher on cathode active material cost-level, rising end-of-life flows and lowered black-mass prices will, however, make secondary supply cost-competitive to domestic and foreign primary supply cost floors. Facility-level benchmarks reveal targeted import, scaling, and production cost optimization as levers for a resilient, cost-effective U.S. battery-material supply chain.

Energy↗
DOE OSTI2022

Snowmass2021 Computational Frontier White Paper: Cosmological Simulations and Modeling

Powerful new observational facilities will come online over the next decade, enabling a number of discovery opportunities in the "Cosmic Frontier", which targets understanding of the physics of the early universe, dark matter and dark energy, and cosmological probes of fundamental physics, such as neutrino masses and modifications of Einstein gravity. Synergies between different experiments will be leveraged to present new classes of cosmic probes as well as to minimize systematic biases present in individual surveys. Success of this observational program requires actively pairing it with a well-matched state-of-the-art simulation and modeling effort. Next-generation cosmological modeling will increasingly focus on physically rich simulations able to model outputs of sky surveys spanning multiple wavebands. These simulations will have unprecedented resolution, volume coverage, and must deliver guaranteed high-fidelity results for individual surveys as well as for the cross-correlations across different surveys. The needed advances are as follows: (1) Development of scientifically rich and broadly-scoped simulations, which capture the relevant physics and correlations between probes (2) Accurate translation of simulation results into realistic image or spectral data to be directly compared with observations (3) Improved emulators and/or data-driven methods serving as surrogates for expensive simulations, constructed from a finite set of full-physics simulations (4) Detailed and transparent verification and validation programs for both simulations and analysis tools. (Abridged)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Development of multi-scale computational frameworks to solve fusion materials science challenges

Over the past two decades, the US-DOE has funded multiple projects that rely on high-performance computing and exascale computing platforms to accelerate scientific discoveries and address grand scientific challenges, such as harnessing fusion energy. In this article, we review in detail one of these efforts aimed at enhancing our capability to model plasma-facing materials subject to plasma and high-energy ion/neutron irradiation. The plasma surface interactions project has built a multi-scale modeling framework where many of the plasma- and high-energy ion/neutron irradiation-induced effects occurring in tungsten are explored. Here, this knowledge is used to develop atomistically-informed, high-fidelity continuum and meso-scale models that can be validated against experiments. We review the developments within this project, with attention to experimental validation efforts, and specifically highlight activities associated with: helium bubble bursting and equation of state, and hydrogen-helium interactions in tungsten; atomistically-informed model development for beryllium-tungsten material mixing; coupling of scrape-of-layer plasma, sheath and material models; and coupling of stochastic cluster-dynamics and crystal plasticity models to address radiation effects in tungsten under stress. Finally, we present how the project is preparing for future computational architectures, for instance through efforts to adapt atomistic methods to exascale computing.

36 MATERIALS SCIENCE↗
NASA NTRS2005

IHY Modeling Support at the Community Coordinated Modeling Center

The Community Coordinated Modeling Center (CCMC) is a US inter-agency activity aiming at research in support of the generation of advanced space weather models. As one of its main functions, the CCMC provides to researchers the use of space science models, even if they are not model owners themselves. In particular, the CCMC provides to the research community the execution of "runs-onrequest" for specific events of interest to space science researchers. Through this activity and the concurrent development of advanced visualization tools, CCMC provides, to the general science community, unprecedented access to a large number of state-of-the-art research models. CCMC houses models that cover the entire domain from the Sun to the Earth. In this presentation, we will provide an overview of CCMC modeling services that are available to support activities during the International Heliospheric Year. In order to tailor CCMC activities to IHY needs, we will also invite community input into our IHY planning activities.

Chulaki, A.↗