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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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587 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Development of an Amine Oxide Polyzwitterion Brush Martini Model with Polarizable Water and Ions

Abstract In order to accurately simulate the fouling process of proteins onto polyzwitterion brushes, models that accurately capture the hydration properties and chain conformations of such brushes must first be established. We developed a Martini coarse-grained (CG) model for amine oxide polyzwitterion (PNOMA) brushes, a promising class of antifouling materials, in polarizable water and ions by fitting to all-atom bond and angle distributions, monomer hydration free energy, monomer–monomer distance potential of mean force (PMF), and monomer–salt radial distribution functions (RDFs). Martini 2.2P was selected for compatibility with the established polarizable water and ion models. For comparison with PNOMA, we also constructed models for conventional sulfobetaine (PSBMA) and phosphorylcholine (PMPC) polyzwitterions and the polycation PMETAC using established nonbonded bead types from the literature and refitting bond and angle potentials. We simulated each polymer brush chemistry for varying grafting density and chain length, validating brush height scaling relations against experimental data. The CG models captured the relative hydration strengths among different polyzwitterion chemistries, and brush heights extrapolated to higher molecular weights are in agreement with experimental ellipsometry data. We find that chain swelling of the superhydrophilic PNOMA brushes lies between that of the traditional polyzwitterions PSBMA/PMPC and the polycation PMETAC. For PNOMA brushes in NaCl solution, simulated brush height decreases with salt concentration due to the selectively strong interactions between amine oxide and sodium ions.

Walker, Christopher C. [Oak Ridge National Laborat↗
DOE OSTI2025

Machine Learning for Predicting Multipactor Susceptibility in Planar RF Structures

Multipactor discharge is a persistent challenge in high-power microwave (HPM) and accelerator systems, where secondary electron avalanches can cause heating, vacuum degradation, and failure. This work presents the first supervised machine learning (ML) framework for multipactor prediction, trained on high-fidelity 3D Particle-in-Cell (PIC) simulation data in planar geometries. The model maps operational, geometric, and material-dependent secondary electron yield (SEY) parameters to the time-averaged electron growth rate, enabling rapid reconstruction of susceptibility charts. Among the models evaluated, tree-based ensemble methods such as Random Forest and Extra Trees demonstrate superior generalization to unseen materials compared to neural networks such as multilayer perceptron (MLP). Performance metrics, including Intersection over Union (IoU), Structural Similarity Index Measure (SSIM), and Pearson correlation, show close agreement with simulation benchmarks. Principal Component Analysis attributes generalization limits to material feature-space disjointedness.

43 PARTICLE ACCELERATORS↗
DOE OSTI2026

Multiscale and multidimensional modeling of particle acceleration and transport in solar flares

Multi-messenger, multi-viewpoint, and time-resolved observations of solar flares are now providing unprecedented constraints on particle acceleration sites, energy conversion, and energy transport. The interpretation of current observations, including microwave imaging spectroscopy from EOVSA, hard x-ray (HXR) imaging from Solar Orbiter/STIX, gamma-ray diagnostics from Fermi, and in situ measurements from Parker Solar Probe and Solar Orbiter, collectively demands modeling frameworks that go beyond traditional spatially unresolved, one-zone models or single-mechanism descriptions. This review surveys multiscale and multidimensional modeling approaches, including kinetic, magnetohydrodynamic (MHD), and macroscopic particle models, that are being developed to meet the need. Kinetic simulations reveal that three-dimensional (3D) effects, including field-line chaos and self-generated turbulence, are essential for sustained power-law particle acceleration. MHD simulations now capture flux-rope eruptions, plasmoid-unstable current sheets, and turbulent flare regions in realistic magnetic topologies. Macroscopic models coupling MHD with energetic-particle models produce spatially resolved electron distributions and synthetic HXR and microwave emissions for direct comparison with observations. Despite these advances, outstanding challenges remain in bridging kinetic and global scales, improving MHD simulations and macroscopic particle models, and achieving quantitative model-observation closure.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Modeling Occupant Core Temperatures Across the Boston Building Stock to Advance Public Health

In recent history, extreme heat has been the cause of most deaths from a natural disaster. Exposure to extreme heat can aggravate preexisting conditions, increase hospitalization, and even cause death. Thus, modeling the thermal resilience of households across the United States will allow for a quantitative assessment of the health and safety risks posed by extreme heat. For the first time, we simulate occupant comfort in representative households across Boston by combining the granular results of the ResStock(TM) model with a two-node heat strain model. This model calculates occupants' core body temperature in each simulated household over a year. We compare the simulated core temperatures to two public health metrics: hyperthermia and heat stroke. Our results show for households in Boston that do not have or use aid conditioning, thousands potentially experience many dangerous heat events each summer and these events can last for more than a day at a time. These heat events peak during the late afternoon and evening, just as residents are coming home, cooking meals, and trying to go to sleep. We have found that multi-family buildings, renters, and low-income homes in more airtight and insulated homes are the most at risk for these events. These results demonstrate the scale and urgency of exposure to extreme heat.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Machine learning the electric field response of condensed phase systems using perturbed neural network potentials

Abstract The interaction of condensed phase systems with external electric fields is of major importance in a myriad of processes in nature and technology, ranging from the field-directed motion of cells (galvanotaxis), to geochemistry and the formation of ice phases on planets, to field-directed chemical catalysis and energy storage and conversion systems including supercapacitors, batteries and solar cells. Molecular simulation in the presence of electric fields would give important atomistic insight into these processes but applications of the most accurate methods such as ab-initio molecular dynamics (AIMD) are limited in scope by their computational expense. Here we introduce Perturbed Neural Network Potential Molecular Dynamics (PNNP MD) to push back the accessible time and length scales of such simulations. We demonstrate that important dielectric properties of liquid water including the field-induced relaxation dynamics, the dielectric constant and the field-dependent IR spectrum can be machine learned up to surprisingly high field strengths of about 0.2 V Å −1 without loss in accuracy when compared to ab-initio molecular dynamics. This is remarkable because, in contrast to most previous approaches, the two neural networks on which PNNP MD is based are exclusively trained on molecular configurations sampled from zero-field MD simulations, demonstrating that the networks not only interpolate but also reliably extrapolate the field response. PNNP MD is based on rigorous theory yet it is simple, general, modular, and systematically improvable allowing us to obtain atomistic insight into the interaction of a wide range of condensed phase systems with external electric fields.

Science & Technology - Other Topics↗
NASA NTRS1982

Spacecraft thermal balance testing using infrared sources

A thermal balance test (controlled flux intensity) on a simple black dummy spacecraft using IR lamps was performed and evaluated, the latter being aimed specifically at thermal mathematical model (TMM) verification. For reference purposes the model was also subjected to a solar simulation test (SST). The results show that the temperature distributions measured during IR testing for two different model attitudes under steady state conditions are reproducible with a TMM. The TMM test data correlation is not as accurate for IRT as for SST. Using the standard deviation of the temperature difference distribution (analysis minus test) the SST data correlation is better by a factor of 1.8 to 2.5. The lower figure applies to the measured and the higher to the computer-generated IR flux intensity distribution. Techniques of lamp power control are presented. A continuing work program is described which is aimed at quantifying the differences between solar simulation and infrared techniques for a model representing the thermal radiating surfaces of a large communications spacecraft.

G. B. T. Tan↗
NASA NTRSDate not supplied

Multiscale Modeling of Fracture Strength in Fibrous Thermal Protection System Materials

This work presents a multiscale modeling approach to predict the fracture strength of fibrous Thermal Protection System (TPS) materials. The model assumes that system failure is initiated at the joints between individual fibers. We investigated three distinct TPS compositions: amorphous silica, alumina and aluminosilicate fibers. Molecular dynamics (MD) simulations were employed to determine the fracture strength values of these fiber joints for both material systems. These fracture strength values were then integrated into simulations of 3D randomly populated fiber structures, where tensile load transfer occurs through the fiber joints. These microscale properties are upscaled through a renormalization approach [1] to predict macroscale tensile strength of 3D random fiber networks, accounting for joint-dominated failure and effective load-bearing area. The study concludes by demonstrating the resulting strength variation as a function of material composition, fiber density, and morphology. We also show validation of results by comparing them against explicit fiber finite element (FE) modeling [2] where fiber joint fracture is represented by cohesive elements.

Jaehyun Cho↗
NASA NTRSDate not supplied

Swamp Works Regolith Compaction Technologies

While the level of compaction below the lunar surface increases quickly after only a few cm of depth, in many cases during a construction mission there will be a need to excavate and transport regolith to a new location for cut-and-fill or horizontal construction of structures such as berms. In these cases to achieve high levels of bulk density, compaction must be per-formed. Additionally, in some cases surface technologies such as systems that sinter/melt the surface may desire the maximum possible compaction at the sur-face to improve melting/heating performance and the final material strength properties. Kennedy Space Center’s (KSC) Swamp Works has developed two means of compaction, lunar and mar-tian compaction. Planetary Autonomous Compaction Technology (PACT) which is part of the Multifunction End Effector for Regolith Compaction Acquisition and Transfer (MEERCAT) robotic arm end effector system’s capabilities and the Site Preparation Tooling for Operations on Mobility Platforms (STOMP) vibratory roller compactor. PACT on MEERCAT has been demonstrated to a TRL 5 and STOMP to a TRL 4 in ambient testing. The results of PACT on MEERCAT and STOMP testing will be shared with results for various simulants including BP-1, ICN-LHT-1G (aka CSM-LHT-1G), RDW-LHT-1GH (a simulant developed for the Mason Tipping Point to match characteristics of ICN-LHT-1G), and Exolith LHS-1E. This will also include discussions on methods used to verify relative density before and after compaction and means to verify density effects below depth. To calculate relative density, maximum and minimum densities for simulants were taken from literature and additional lab testing (publication in work).

redwire↗
DOE OSTI2026

Precise Modeling of a Complex Solenoidal Magnetic Field Using a Combination of Analytic Functions and a PINN

We demonstrate an iterative approach to modeling a sparsely measured magnetic field in a large-bore solenoid. This approach uses a hybrid of traditional and machine learning techniques. The traditional technique is a linear least-squares fit using a series solution to Laplace's equation, while the machine learning technique involves the training of a physics-informed neural network (PINN) on the least-squares fit residuals. We use a newly defined activation function "DELTAsnake," a modification to the snake activation function proposed by Ziyin et al. that allows for stronger curvature and non-monotonicity. The combined model approximately obeys Maxwell's equations to a level sufficient for producing high quality physics simulations and analysis. Our approach is applied to a highly realistic calculation of the expected magnetic field in the Mu2e experiment's Detector Solenoid which includes a simple model for the expected statistical measurement uncertainties. Using ten toy measurement simulations, we demonstrate the capabilities of our model in comparison to the least-squares method alone; the least-squares method alone results in a reduced chi-squared statistic of ${2.15 \pm 0.01}$, while our approach improves the reduced chi-square to ${1.034 \pm 0.005}$. Furthermore, for an average toy simulation, we show that the range of the RMS of the three field component residuals reduces from ${0.07-0.37}$ Gauss to ${0.05-0.07}$ Gauss. We find that this novel method is robust against a realistic systematic uncertainty deriving from Hall probe calibration bias and can be used to significantly reduce the number of measurements required to achieve an accurate model.

Kampa, Cole [Caltech] (ORCID:0000000192972920)↗
DOE OSTI2026

Evolution of the Antarctic Ice Sheet from 2000–2300 and beyond: model sensitivity and uncertainty analysis using MPAS-Albany Land Ice

We present a description of the Antarctic Ice Sheet model configuration submitted to the ISMIP6-Antarctica-2300 experiment using the MPAS-Albany Land Ice model, along with three new sets of simulations: (1) a set of extended simulations to 2500 for three forced experiments and to 2775 for the control experiment; (2) a sensitivity analysis of our model configuration to parameters controlling basal sliding and sub-shelf melt, and to model structural choices including the choice of the energy and stress balances; and (3) a 72-member ensemble run on graphics processing units (GPUs) and analysis of variance to determine the primary sources of uncertainty in our ice-sheet model projections. Our extended simulations predict rapid retreat beginning after 2300 for SSP1-2.6 forcing and after 2500 for present-day (control) forcing, primarily in the Amundsen Sea Embayment. We find that varying the sub-shelf melt parameter between the 5th to 95th percentile values for a mean-Antarctic calibration target results in an up to ∼ ± 40 % change in sea-level contribution relative to our baseline simulations that used the median value. Using a linear basal sliding law reduces sea-level contribution by 51 %–73 % relative to our baseline nonlinear sliding law with an exponent of 1/5. When using basal sliding law exponents of 1/3 and 1/10, the overall difference from our baseline simulations at 2300 is on the order of 10 %. The Amundsen Sea Embayment region displays a strongly non-linear dependence of mass loss on the sliding law exponent, with no discernible relationship between the sliding law exponent and the mass loss by 2300, while the sectors feeding the Ross and Filchner-Ronne ice shelves exhibit more mass loss with a more-plastic sliding law. Our model fidelity sensitivity experiments reveal a 9 %–31 % increase in sea-level contribution when using a depth-integrated stress balance approximation relative to our three-dimensional solver, while using a fixed-in-time temperature field increases sea-level contribution by 14 %–88 % relative to two thermomechanically coupled configurations. Our 72-member ensemble and analysis of variance show that the uncertainty in long-term projections is dominated by the choice of Earth system model forcing and the presence or absence of hydrofracture forcing, rather than uncertainty in sliding and sub-shelf melt parameters.

58 GEOSCIENCES↗
NASA NTRS1985

Battery-Charge-State Model

Charge-state model for lead/acid batteries proposed as part of effort to make equivalent of fuel gage for battery-powered vehicles. Models based on equations that approximate observable characteristics of battery electrochemistry. Uses linear equations, easier to simulate on computer, and gives smooth transitions between charge, discharge, and recuperation.

Vivian, H. C.↗
NASA NTRSDate not supplied

Thermal Data-driven Model Reduction for Enhanced Battery Health Monitoring

Electric aviation faces a major challenge of avoiding potentially catastrophic consequences of the battery’s thermal runaway while keeping the weight of the battery low. Detection of early warning signals of battery failures requires accurate monitoring of the battery’s health throughout its lifespan. However, identifying the parameters of the battery from field data is notoriously difficult. We investigate this problem within the framework of modeling the temperature dynamics of a Li-ion cell during tests simulating loading in electric aircraft flights. It is found that the parameters of a higher-fidelity physics-based thermal model cannot be identified from the simulated flight data. To resolve this issue, we reduce the higher-fidelity thermal model to a model with fewer parameters. The resulting reduced-order model can predict temperature dynamics accurately and is identifiable throughout the cell’s lifespan which allows using the model’s parameters to monitor the state-of-health of the aging cell and detect anomalies in thermal behavior.

Li ion batteries↗
NASA NTRS2026

Swamp Works Regolith Compaction Technologies

While the level of compaction below the lunar surface increases quickly after only a few cm of depth, in many cases during a construction mission there will be a need to excavate and transport regolith to a new location for cut-and-fill or horizontal construction of structures such as berms. In these cases to achieve high levels of bulk density, compaction must be per-formed. Additionally, in some cases surface technolo-gies such as systems that sinter/melt the surface may desire the maximum possible compaction at the sur-face to improve melting/heating performance and the final material strength properties. Kennedy Space Center’s (KSC) Swamp Works has developed two means of compaction, lunar and mar-tian compaction. Planetary Autonomous Compaction Technology (PACT) which is part of the Multifunction End Effector for Regolith Compaction Acquisition and Transfer (MEERCAT [1]) robotic arm end effector system’s capabilities and the Site Preparation Tooling for Operations on Mobility Platforms (STOMP [2]) vibratory roller compactor. PACT on MEERCAT has been demonstrated to a TRL 5 and STOMP to a TRL 4 in ambient testing. The results of PACT on MEERCAT and STOMP testing will be shared with results for various simulants including BP-1, ICN-LHT-1G (aka CSM-LHT-1G), RDW-LHT-1GH (a simulant developed for the Mason Tipping Point to match characteristics of ICN-LHT-1G), and Exolith LHS-1E. This will also include discus-sions on methods used to verify relative density before and after compaction and means to verify density effects below depth. To calculate relative density, maximum and minimum densities for simulants were taken from literature [3] [4] [5] and additional lab test-ing (publication in work).

vibration↗
DOE OSTI2026

Modeling of a Four-Stage Linear Ionization Cooling Channel for a Muon Collider in G4Beamline

A previous study of an eight-stage rectilinear ionization cooling channel in the ICOOL software demonstrated a five-order-of-magnitude reduction in a muon beam’s 6D emittance. In this study, we look to compare the ways ICOOL and Muons, Inc.’s g4Beamline software model ionization cooling by comparing their modeling of the first four stages to this optimized cooling channel constructed in ICOOL. We begin by identifying the parameters used to construct the optimized ionization cooling channel in ICOOL. We then reconstruct this beam in g4Beamline with identical parameter specifications and simulate the cooling of an identical input beam. Finally, we compare the two simulations based on their beam transmission, longitudinal emittance, and transverse emittance along the channel length. Through this process, we demonstrate that G4Beamline accurately reproduces transverse cooling results but predicts systematically different longitudinal emittance evolution while maintaining similar overall cooling performance, reproducing a 97.9% reduction in 6D emittance over four stages.

Keeler, Dominic [Purdue U., West Lafayette] (ORCID↗
NASA NTRS1970

Development of a silver-zinc battery system

Summary report is described of historical documentation and detailed design data for development of silver-zinc battery for use on Surveyor spacecraft. Electrical and physical characteristics of battery models are included, along with data on qualification, acceptance, solar-thermal-vacuum, mission simulation testing, and actual flight performance.

Moses, A. J.↗
NASA NTRS1995

CAE for Thermal Management of Aerospace Electronic Boards Using the BETAsoft Program

Aerospace electronic boards require special attention to thermal management due to constraints such as their need to be light, small, and maintain high power densities. Also, cooling is mainly through conductive and radiative modes with minor or negligible convective cooling. Due to these particular requirements, thermal design has become an integrated part of the electronic design process in order to avoid expensive repeat prototyping and to ensure high reliability. To achieve high speed simulations, the BETAsoft code uses semi-empirical formulations and an advanced finite difference scheme that incorporates local adaptive grids. Detailed conduction, convection and radiation heat transfer is considered. Various benchmark verifications of the software simulation compared to infrared images typically prove to be within 10% of each other. The thermal analysis of a sample avionic card in a natural convection environment is shown. Then, the individual effects of attaching metal screws to the casing, increasing radiative emissivities of the casing, increasing the conductance of the wedge lock, adding an aluminum core to the board, adding metal strips in board layers, inserting conduction pads under components, and adding heat sinks to components are demonstrated.

Kimberly Bobish↗
NASA NTRS2026

Controlled Parametric Forcing During Directional Solidification of a Bulk Organic Alloy Under Microgravity

The response of dendritic microstructures to step-like pulling velocity conditions is investigated using microgravity directional solidification experiments conducted on DECLIC-DSI combined with phase-field simulations. Under a constant pulling velocity of 1.5 µm/s, the evolution toward steady-state growth is characterized in terms of primary spacing, dendrite drift, and tip dynamics. For the first time, side-view observations enabled direct measurement of tip radius and sidebranching frequency. When step-like oscillations of the pulling velocity are imposed, the dendritic array exhibits a strongly period-dependent response: short periods lead to rapid tip adaptation, whereas longer periods induce a phase lag between tip position and morphology, resulting in progressive tip flattening and, above a critical period, interface destabilization and dendrite splitting. Quantitative phase-field simulations, including a realistic thermal field and stochastic noise, reproduce the experimental observations and provide insight into the governing mechanisms, highlighting the role of characteristic relaxation times, sequence-dependent effects, and the irreversible reorganization of the microstructure following splitting.

Microgravity↗