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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 1,621 records · Page 90
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Davis Computational Spectroscopy Workflow—From Structure to Spectra

Here, we describe an automated workflow that connects a series of atomic simulation tools to investigate the relationship between atomic structure, lattice dynamics, materials properties, and inelastic neutron scattering (INS) spectra. Starting from the atomic simulation environment (ASE) as an interface, we demonstrate the use of a selection of calculators, including density functional theory (DFT) and density functional tight binding (DFTB), to optimize the structures and calculate interatomic force constants. We present the use of our workflow to compute the phonon frequencies and eigenvectors, which are required to accurately simulate the INS spectra in crystalline solids like diamond and graphite as well as molecular solids like rubrene. We have also implemented a machine-learning force field based on Chebyshev polynomials called the Chebyshev interaction model for efficient simulation (ChIMES) to improve the accuracy of the DFTB simulations. We then explore the transferability of our DFTB/ChIMES models by comparing simulations derived from different training sets. We show that DFTB/ChIMES demonstrates ~100× reduction in computational expense while retaining most of the accuracy of DFT as well as yielding high accuracy for different materials outside of our training sets. The DFTB/ChIMES method within the workflow expands the possibilities to use simulations to accurately predict materials properties of increasingly complex structures that would be unfeasible with ab initio methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Modeling the dynamical coupling between fires and atmospheric hydrodynamics [Slides]

The role of physic process-based modeling in wildfire behavior research : Fire experiments and field observations; Process-based fire behavior modeling; Models can help test our understanding; Models can assist in the development of hypotheses, which can be tested with observations; Models can allow scenario and sensitivity explorations when observations are difficult; It is important to keep in mind the assumptions/approximations of model formulations (only partial physics).

58 GEOSCIENCES↗
NASA NTRS1993

Critical comparison of second-order closures with direct numerical simulations of homogeneous turbulence

Recently, several models have been proposed for closing the second-moment equations, in which the velocity-pressure gradient tensor and the dissipation rate tensor are two of the most important terms. In the literature, these correlation tensors are usually decomposed into a so-called rapid term and a return-to-isotropy term. Models of these terms have been used in global flow calculations together with other modeled terms. However, their individual behaviors in different flows have not been fully examined because they are unmeasurable in the laboratory. Recently, the development of direct numerical simulation (DNS) of turbulence has given us the possibility to do this kind of study. With direct numerical simulation, we may use the solution to calculate exactly the values of these correlation terms and then directly compare them with the values from their modeled formulations. In this paper, we make direct comparisons of five representative rapid models and eight return-to-isotropy models using the DNS data of 45 homogeneous flows, which were done by Rogers et al. (1986) and Lee and Reynolds (1985). The purpose of these direct comparisons is to explore the performance of these models in different flows and identify the ones that give the best performance. The paper also describes the modeling procedure, model constraints, and the various evaluated models. The detailed results of the direct comparisons are discussed, and a few concluding remarks on turbulence models are given.

Shih, Tsan-Hsing↗
NASA NTRSDate not supplied

Fast and Precise Trajectory Simulation for Entry, Descent, and Landing Using A Multi-Model Monte Carlo Approach

Predicting landing radius and other quantities of interest (QoI) for entry, descent, and landing (EDL) applications requires a viable uncertainty propagation method for quantifying the impact of uncertainties in wind pattern variations, atmospheric uncertainties, etc. While standard MC simulation is the defacto standard for providing robust and unbiased predictions,it is often infeasible for expensive, high-fidelity EDL models. Low-fidelity models are commonly constructed to replace the high-fidelity model in MC simulation for computational speedup,but at the expense of accuracy and unbiasedness. Emerging multi-model MC methods are bridging this gap by combining predictions from two or more models of varying fidelity and computational cost for efficient and unbiased uncertainty propagation. This work explores the use of multi-model MC for increasing the speed and precision of trajectory simulation for EDL. It is shown that combining a high-fidelity EDL model with low-fidelity models (e.g,data-driven, reduced physics) yields substantial computational speedup versus standard MCwith only the high-fidelity model. Moreover, the unbiasedness of multi-model MC predictions is highlighted by showing increased accuracy versus an approach that leverages a low-fidelity surrogate model alone.

James E. Warner↗
DOE OSTI2025

Topological Mixed Valence Model for Twisted Bilayer Graphene

Song and Bernevig (SB) have recently proposed a topological heavy-fermion description of the physics of magic angle twisted bilayer graphene (MATBG), involving the hybridization of flat-band electrons with a relativistic conduction sea. Here, we explore the consequences of this model, seeking a synthesis of understanding drawn from heavy-fermion physics and MATBG experiments. Our work identifies a key discrepancy between measured and calculated on-site Coulomb interactions, implicating renormalization effects that are not contained in the current model. With these considerations in mind, we consider a SB model with a single, renormalized on-site interaction between the f electrons, containing a phenomenological heavy-fermion binding potential on the moiré A A sites. This feature allows the simplified model to capture the periodic reset of the chemical potential with filling and the observed stability of local moment behavior. We argue that a two-stage Kondo effect will develop in MATBG as a consequence of the relativistic conduction band: Kondo I occurs at high temperatures, establishing a coherent hybridization at the Γ points and a non-Fermi liquid of incoherent fermions at the moiré K points; at much lower temperatures, Kondo II leads to a Fermi liquid in the flat band. Utilizing an auxiliary-rotor approach, we formulate a mean-field treatment of MATBG that captures this physics, describing the evolution of the normal state across a full range of filling factors. By contrasting the relative timescales of phonons and valence fluctuations in bulk heavy-fermion materials with that of MATBG, we are led to propose a valley-polaron origin to the Coulomb renormalization and the heavy-fermion binding potential identified from experiment. We also discuss the possibility that the two-fluid, non-Fermi liquid physics of the relativistic Kondo lattice is responsible for the strange-metal physics observed in MATBG. Published by the American Physical Society 2025

Lau, Liam L. H. (ORCID:0000000166039088)↗
NASA NTRS2005

A Web-based Collaborative Tool for Mars Analog Data Exploration

Solving today's complex research and modeling challenges are dependent on our ability to discover, access, integrate, and share information from multiple sources. The planetary sciences community is no exception'; over the last few years, the need for data mining and exploration tools that can expedite comparative studies between Martian and terrestrial analogs sites and aid the interpretation of Mars data sets has become evident. Data sharing maximizes scientific return from studies and data sets.

Necsoiu, M.↗
NASA NTRS2021

Recent Advancements in Modeling and Simulation of Entry Systems at NASA

This paper describes recent development of modeling and simulation technologies for entry systems in support of NASA’s exploration missions. Mission-tailored research and development in modeling of entry systems occurs across the Agency (e.g., within the Orion and Mars 2020 Programs), however the aim of this paper is to discuss the broad, cross-mission research conducted by NASA’s Entry Systems Modeling (ESM) Project, which serves as the Agency’s only concerted effort toward advancing entry systems across a range of technical disciplines. Technology development in ESM is organized and prioritized from a system-level perspective, resulting in four broad technical areas of investment: (1) Predictive material modeling, (2) Shock layer kinetics and radiation, (3) Computational and experimental aerosciences, and (4) Guidance, navigation, and control. Investments in thermal protection material modeling are geared toward high-fidelity, predictive models capable of handling complex structures, with an eye toward optimizing design performance and quantifying thermal protection system reliability. New computational tools have been developed to characterize material properties and behavior at the microstructural level, and experimental techniques (molecular beam scattering, micro-computed tomography, among others) have been developed to measure material kinetics, morphology, and other parameters needed to inform and validate detailed simulations. Advancements have also been made in macrostructural simulation capability to enable 3-D system-scale calculations of material response with complex topological features, including differential recession of tile gaps. Research and development in the area of shock layer kinetics has focused on air and CO2-based atmospheres. Capacity and capability of the NASA Ames Electric Arc Shock Tube (EAST) have been expanded in recent years and analysis of resulting data has led to several improvements in kinetic models, while simultaneously reducing uncertainties associated with radiative heat transfer predictions. First-principles calculations of fundamental kinetic, thermodynamic, and transport data, along with state-specificmodels for non-equilibrium flow regimes, have also yielded new insights and have the potential to vastly improve model fidelity. Aerosciences is a very broad area of interest in entry systems, yet a number of important challenges are being addressed: Coupled fluid-structure simulations of parachute inflation and dynamics; Experimental and computational studies of vehicle dynamics; Multi-phase flow with dust particles to simulate entry environments at Mars during dust storms; Studies of roughness-induced heating augmentation relevant to tiled and woven thermal protection systems; and Advanced numerical methods to optimize computational analyses for desired accuracy versus cost. Guidance and control in the context of entry systems has focused on development of methods for multi-axis control (i.e. pitch and yaw, rather than bank angle alone) of spacecraft during entry and descent. With precision landing requirements driven by Mars human exploration goals, recent efforts have yielded 6-DOF models of multi-axis control with propulsive descent of both inflatable and rigid ellipsled-like architectures. Results for both configurations have demonstrated the ability to land within the 50-meter precision requirement demanded by Mars human exploration missions, while also reducing propellant requirements by enabling more efficient control through entry and descent. Ongoing research in GN&C is developing mechanical specifications for the systems and establishing engineering feasibility.

aerothermodynamics↗
DOE OSTI2023

Accelerating Markov Chain Monte Carlo sampling with diffusion models

Global fits of physics models require efficient methods for exploring high-dimensional and/or multimodal posterior functions. We introduce a novel method for accelerating Markov Chain Monte Carlo (MCMC) sampling by pairing a Metropolis-Hastings algorithm with a diffusion model that can draw global samples with the aim of approximating the posterior. We briefly review diffusion models in the context of image synthesis before providing a streamlined diffusion model tailored towards low-dimensional data arrays. We then present our adapted Metropolis-Hastings algorithm which combines local proposals with global proposals taken from a diffusion model that is regularly trained on the samples produced during the MCMC run. Our approach leads to a significant reduction in the number of likelihood evaluations required to obtain an accurate representation of the Bayesian posterior across several analytic functions, as well as for a physical example based on a global fit of parton distribution functions. Our method is extensible to other MCMC techniques, and we briefly compare our method to similar approaches based on normalising flows. A code implementation can be found at https://github.com/NickHunt-Smith/MCMC-diffusion.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Cosmic Signatures of Fundamental Physics (Final Technical Report)

Cosmology is the study of the history of the Universe. Major topics of current cosmology research include the nature of the dark energy which today is causing the Universe to accelerate, and the nature of cosmic inflation which is our best theory of the very early evolution of the Universe. Each of these topics can be explored with modern cosmological data, and rely on our theories of fundamental physics to operate. Research supported by this grant has led to advances in all these areas. We developed specific models of cosmic inflation and explored potential observations signatures. We explored observational constraints on the number of dimensions of space, which in certain modern theories can take in different values, and developed the specific “brane theories” of dark energy. The possibility that novel quantum effects (“quantum entanglement”) during cosmic inflation could lead to interesting observable phenomena was also explored.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1991

A critical comparison of second order closures with direct numerical simulation of homogeneous turbulence

Recently, several second order closure models have been proposed for closing the second moment equations, in which the velocity-pressure gradient (and scalar-pressure gradient) tensor and the dissipation rate tensor are two of the most important terms. In the literature, these correlation tensors are usually decomposed into a so called rapid term and a return-to-isotropy term. Models of these terms have been used in global flow calculations together with other modeled terms. However, their individual behavior in different flows have not been fully examined because they are un-measurable in the laboratory. Recently, the development of direct numerical simulation (DNS) of turbulence has given us the opportunity to do this kind of study. With the direct numerical simulation, we may use the solution to exactly calculate the values of these correlation terms and then directly compare them with the values from their modeled formulations (models). Here, we make direct comparisons of five representative rapid models and eight return-to-isotropy models using the DNS data of forty five homogeneous flows which were done by Rogers et al. (1986) and Lee et al. (1985). The purpose of these direct comparisons is to explore the performance of these models in different flows and identify the ones which give the best performance. The modeling procedure, model constraints, and the various evaluated models are described. The detailed results of the direct comparisons are discussed, and a few concluding remarks on turbulence models are given.

Shih, Tsan-Hsing↗
NASA NTRS2011

Computational Validation of a Two-Dimensional Semi-Empirical Model for Inductive Coupling in a Conical Pulsed Inductive Plasma Thruster

A two-dimensional semi-empirical model of pulsed inductive thrust efficiency is developed to predict the effect of such a geometry on thrust efficiency. The model includes electromagnetic and gas-dynamic forces but excludes energy conversion from radial motion to axial motion, with the intention of characterizing thrust efficiency loss mechanisms that result from a conical versus a at inductive coil geometry. The range of conical pulsed inductive thruster geometries to which this model can be applied is explored with the use of finite element analysis. A semi-empirical relation for inductance as a function of current sheet radial and axial position is the limiting feature of the model, restricting the applicability as a function of half cone angle to a range from ten degrees to about 60 degrees. The model is nondimensionalized, yielding a set of dimensionless performance scaling parameters. Results of the model indicate that radial current sheet motion changes the axial dynamic impedance parameter at which thrust efficiency is maximized. This shift indicates that when radial current sheet motion is permitted in the model longer characteristic circuit timescales are more efficient, which can be attributed to a lower current sheet axial velocity as the plasma more rapidly decouples from the coil through radial motion. Thrust efficiency is shown to increase monotonically for decreasing values of the radial dynamic impedance parameter. This trend indicates that to maximize the radial decoupling timescale should be long compared to the characteristic circuit timescale.

Hallock, Ashley K.↗
NASA NTRS2014

Implementing Badhwar-O'Neill Galactic Cosmic Ray Model for the Analysis of Space Radiation Exposure

For the analysis of radiation risks to astronauts and planning exploratory space missions, accurate energy spectrum of galactic cosmic radiation (GCR) is necessary. Characterization of the ionizing radiation environment is challenging because the interplanetary plasma and radiation fields are modulated by solar disturbances and the radiation doses received by astronauts in interplanetary space are likewise influenced. A model of the Badhwar‐O'Neill 2011 (BO11) GCR environment, which is represented by GCR deceleration potential theta, has been derived by utilizing all of the GCR measurements from balloons, satellites, and the newer NASA Advanced Composition Explorer (ACE). In the BO11 model, the solar modulation level is derived from the mean international sunspot numbers with time‐delay, which has been calibrated with actual flight instrument measurements to produce better GCR flux data fit during solar minima. GCR fluxes provided by the BO11 model were compared with various spacecraft measurements at 1 AU, and further comparisons were made for the tissue equivalent proportional counters measurements at low Earth orbits using the high‐charge and energy transport (HZETRN) code and various GCR models. For the comparison of the absorbed dose and dose equivalent calculations with the measurements by Radiation Assessment Detector (RAD) at Gale crater on Mars, the intensities and energies of GCR entering the heliosphere were calculated by using the BO11 model, which accounts for time‐dependent attenuation of the local interstellar spectrum of each element. The BO11 model, which has emphasized for the last 24 solar minima, showed in relatively good agreement with the RAD data for the first 200 sols, but it was resulted in to be less well during near the solar maximum of solar cycle 24 due to subtleties in the changing heliospheric conditions. By performing the error analysis of the BO11 model and the optimization in reducing overall uncertainty, the resultant BO13 model corrects the fit at solar maxima as well as being accurate at solar minima. The BO13 model is implemented to the NASA Space Cancer Risk model for the assessment of radiation risks. Overall cumulative probability distribution of solar modulation parameters represents the percentile rank of the average interplanetary GCR environment, and the probabilistic radiation risks can be assessed for various levels of GCR environment to support mission design and operational planning for future manned space exploration missions.

Kim, Myung-Hee Y.↗
NASA NTRS1990

Global models of Ne and Te at solar maximum based on DE-2 measurements

Newly developed global models of the electron density of (Ne) and (Te) in the F-region at solar maximum, based on Langmuir probe measurements from the Dynamics Explorer-2 satellite, are compared with solar minimum models that were developed earlier from Atmosphere Explorer data. Spherical harmonics are used in both models to describe the variations with geomagnetic latitude and local time, but the solar maximum model also includes longitudinal variations. The solar minimum models were for the fixed altitudes of 300 km and 400 km, while the solar maximum model covers all altitudes between 300 and 1000 km. In this paper, the global patterns of Ne and Te at 400 km at solar maximum and minimum are compared with the IRI model for the corresponding parts of the solar cycle. In most respects, the IRI model describes the empirical models quite well at both solar maximum and solar minimum.

Brace, L. H.↗
DOE OSTI2025

Bridging the Gap Between Astronomical Datasets: From Proof-of-Concept to AI Model Deployment with Domain Adaptation

Artificial Intelligence is transforming astrophysics, from studying stars and galaxies to analyzing cosmic large-scale structures. However, a critical challenge arises when AI models trained on simulations or past observational data are applied to new observation— leading to domain shifts, reduced robustness, and increased uncertainty of model predictions. This talk will explore these issues, highlighting examples such as galaxy morphology classification and cosmological parameter inference, where AI struggles to adapt across different datasets. We will discuss domain adaptation as a strategy to improve model generalization and mitigate biases—essential for making AI-driven discoveries reliable. Notably, these challenges extend beyond astrophysics, affecting AI applications across physics and other scientific domains. Addressing them is essential for maximizing AI’s impact in advancing scientific research.

Ćiprijanović, Aleksandra [Fermilab]↗
NASA NTRS2009

Lunar Surface Potential Increases during Terrestrial Bow Shock Traversals

Since the Apollo era the electric potential of the Moon has been a subject of interest and debate. Deployed by three Apollo missions, Apollo 12, Apollo 14 and Apollo 15, the Suprathermal Ion Detector Experiment (SIDE) determined the sunlit lunar surface potential to be about +10 Volts using the energy spectra of lunar ionospheric thermal ions accelerated toward the Moon. We present an analysis of Apollo 14 SIDE "resonance" events that indicate the lunar surface potential increases when the Moon traverses the dawn bow shock. By analyzing Wind spacecraft crossings of the terrestrial bow shock at approximately this location and employing current balancing models of the lunar surface, we suggest causes for the increasing potential. Determining the origin of this phenomenon will improve our ability to predict the lunar surface potential in support of human exploration as well as provide models for the behavior of other airless bodies when they traverse similar features such as interplanetary shocks, both of which are goals of the NASA Lunar Science Institute's Dynamic Response of the Environment At the Moon (DREAM) team.

Collier, Michael R.↗
NASA NTRS2019

Capturing Connections Between the Water, Energy, and Carbon Cycles with the NASA GEOS

Studying biosphere-atmosphere interactions is complex as water, energy and carbon cycles and their feedback processes have to be integrated. At NASA GMAO, we investigate these interactions with an Earth system model that allows us to explore and quantify relevant feedbacks associated with the exchanges of carbon, water, and energy fluxes within the atmosphere, within the land, and across the land-atmosphere interface. Current biosphere-atmosphere modeling research at GMAO includes a study to understand the relative contributions of land carbon flux variability and atmospheric dynamics to atmospheric CO2 variability in time and space. For this study, we use a unique capability of the NASA GEOS model, a "replay" mode that forces the model to reproduce the weather systems captured by the MERRA-2 reanalysis. Another study investigates the impact of imposed regional drought on land carbon fluxes and on subsequent atmospheric CO2 concentrations, thereby revealing interactions between the water and carbon cycles. Using the new coupled carbon-climate modeling capability, current GMAO efforts at subseasonal-to-seasonal forecasting are now being expanded, at least in research mode, to include forecasts of carbon and phenological state.

Lee, Eunjee↗
DOE OSTI2024

Deep energy-pressure regression for a thermodynamically consistent EOS model

Abstract In this paper, we aim to explore novel machine learning (ML) techniques to facilitate and accelerate the construction of universal equation-Of-State (EOS) models with a high accuracy while ensuring important thermodynamic consistency. When applying ML to fit a universal EOS model, there are two key requirements: (1) a high prediction accuracy to ensure precise estimation of relevant physics properties and (2) physical interpretability to support important physics-related downstream applications. We first identify a set of fundamental challenges from the accuracy perspective, including an extremely wide range of input/output space and highly sparse training data. We demonstrate that while a neural network (NN) model may fit the EOS data well, the black-box nature makes it difficult to provide physically interpretable results, leading to weak accountability of prediction results outside the training range and lack of guarantee to meet important thermodynamic consistency constraints. To this end, we propose a principled deep regression model that can be trained following a meta-learning style to predict the desired quantities with a high accuracy using scarce training data. We further introduce a uniquely designed kernel-based regularizer for accurate uncertainty quantification. An ensemble technique is leveraged to battle model overfitting with improved prediction stability. Auto-differentiation is conducted to verify that necessary thermodynamic consistency conditions are maintained. Our evaluation results show an excellent fit of the EOS table and the predicted values are ready to use for important physics-related tasks.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

Terrestrial case studies of ilmenite exploration and lunar implications

The Space Exploration Initiative (SEI) includes space resource utilization as one of the four architectures to achieve U.S. goals in space. Space resource utilization will make use of lunar resources to support long term activities on the lunar surface. Lunar ilmenite and regolith are two of the materials that can be mined and processed for lunar oxygen production. During this investigation, several sources were reviewed to assess terrestrial exploration methods used for locating ilmenite resources. These sources included published reports on terrestrial ilmenite exploration methods, analytical methods, case histories, chemical and physical properties, and associations with other minerals. Using a terrestrial analog and considering the differences between terrestrial and lunar environmental conditions, rocks, and minerals, exploration methods and analytical instruments can be recommended for a lunar orbiter and lander for assessing lunar resources. Twelve terrestrial case histories were reviewed to gain insight into ilmenite exploration on the Moon. All exploration case histories follow the same pattern. They begin with a model, use remote geophysical techniques, define regional sampling sites from the model and geophysics, narrow down the area of exploration based on the preceding work, collect more samples and cores, and perform laboratory analyses of samples. An important part of this process is the collection of samples to determine the correctness of the model. Surface and core samples are collected in areas expected to contain both high and low concentration of the commodity to test the model. After samples are analyzed and the area of mineralization is defined, reserves are calculated to determine the cost/benefit ratio, the necessary capacity of the processing plant, and the life of the mine. The exploration methods used for locating terrestrial ilmenite resources are reviewed with respect to the petrology, chemistry, and mineral associations of the terrestrial and lunar environments.

Feldman, S. C.↗