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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

Capture of planetesimals into a circumterrestrial swarm

The lunar origin model considered involves processing of protolunar material through a circumterrestrial swarm of particles. Once such a swarm has formed, it can gain mass by capturing infalling planetesimals and ejecta from giant impacts on the Earth, although the angular momentum supply from these sources remains a problem. Examined is the first stage of formation of a geocentric swarm by capture of planetesimals from initialy heliocentric orbits. The only plausible capture mechanism that is not dependent on very low approach velocities is the mutual collision of planetesimals passing within Earth's sphere of influence. This capture scenario was tested directly by many body numerical integration of planetesimal orbits in near Earth space. Results agree that the systematic contribution of angular momentum is insufficient to maintain an orbiting swarm under heavy bombardment. Thus, a circumterrestrial swarm can be formed rather easily, but is hard to sustain because the mean net angular momentum of a many body swarm is small.

Weidenschilling, S. J.↗
NASA NTRS1996

IMACCS: A Progress Report on NASA/GSFC's COTS-Based Ground Data Systems, and their Extension into New Domains

The integrated monitoring, analysis and control commercial off-the-shelf system (IMACCS) for the provision of real-time satellite command and telemetry support, orbit and attitude determination, events prediction and data trend analysis, is considered. The upgrades made to the original commercial, off-the-shelf (COTS) prototype are described. These upgrades include automation capability, and spacecraft integration and testing capability. A further extension to the prototype is the establishment of a direct radio frequency interface to a spacecraft. The systems development approach employed is described.

Scheidker, E. J.↗
DOE OSTI2025

Accelerating the discovery of low-energy structure configurations: A computational approach that integrates first-principles calculations, Monte Carlo sampling, and Machine Learning

Finding Minimum Energy Configurations (MECs) is essential in fields such as physics, chemistry, and materials science, as they represent the most stable states of the systems. In particular, identifying such MECs in multi-component alloys considered candidate PFMs is key because it determines the most stable arrangement of atoms within the alloy, directly influencing its phase stability, structural integrity, and thermo-mechanical properties. However, since the search space grows exponentially with the number of atoms considered, obtaining such MECs using computationally expensive first-principles DFT calculations often results in a cumbersome task. To escape the above compromise between physical fidelity and computational efficiency, we have developed a novel physics-based data-driven approach that combines Monte Carlo sampling, first-principles DFT calculations, and Machine Learning to accelerate the discovery of MECs in multi-component alloys. More specifically, we have leveraged well-established Cluster Expansion (CE) techniques with Local Outlier Factor models to establish strategies that enhance the reliability of the CE method. In this work, we demonstrated the capabilities of the proposed approach for the particular case of a tungsten-based quaternary high-entropy alloy. However, the method is applicable to other types of alloys and enables a wide range of applications.

36 MATERIALS SCIENCE↗
NASA NTRS2015

GCR Simulator Development Status at the NASA Space Radiation Laboratory

There are large uncertainties connected to the biological response for exposure to galactic cosmic rays (GCR) on long duration deep space missions. In order to reduce the uncertainties and gain understanding about the basic mechanisms through which space radiation initiates cancer and other endpoints, radiobiology experiments are performed with mono-energetic ions beams. Some of the accelerator facilities supporting such experiments have matured to a point where simulating the broad range of particles and energies characteristic of the GCR environment in a single experiment is feasible from a technology, usage, and cost perspective. In this work, several aspects of simulating the GCR environment at the NASA Space Radiation Laboratory (NSRL) are discussed. First, comparisons are made between direct simulation of the external, free space GCR field, and simulation of the induced tissue field behind shielding. It is found that upper energy constraints at NSRL limit the ability to simulate the external, free space field directly (i.e. shielding placed in the beam line in front of a biological target and exposed to a free space spectrum). Second, a reference environment for the GCR simulator and suitable for deep space missions is identified and described in terms of fluence and integrated dosimetric quantities. Analysis results are given to justify the use of a single reference field over a range of shielding conditions and solar activities. Third, an approach for simulating the reference field at NSRL is presented. The approach directly considers the hydrogen and helium energy spectra, and the heavier ions are collectively represented by considering the linear energy transfer (LET) spectrum. While many more aspects of the experimental setup need to be considered before final implementation of the GCR simulator, this preliminary study provides useful information that should aid the final design. Possible drawbacks of the proposed methodology are discussed and weighed against alternative simulation strategies.

Slaba, T. C.↗
NASA NTRS2016

Rough Surfaces: Is the Dark Stuff Just Shadow?: "Who knows what evil lurks in the hearts of men? The shadow knows!"

Remote observations of the surfaces of airless planetary objects are fundamental to inferring the physical structure and compositional makeup of the surface material. A number of forward models have been developed to reproduce the photometric behavior of these surfaces, based on specific, assumed structural properties such as macroscopic roughness and associated shadowing. Most work of this type is applied to geometric albedos, which are affected by complicated effects near zero phase angle that represent only a tiny fraction of the net energy reflected by the object. Other applications include parameter fits to resolved portions of some planetary surface as viewed over a range of geometries. The spherical albedo of the entire object (when it can be determined) captures the net energy balance of the particle more robustly than the geometric albedo. In most treatments involving spherical albedos, spherical albedos and particle phase functions are often treated as if they are independent, neglecting the effects of roughness. In this paper we take a different approach. We note that whatever function captures the phase angle dependence of the brightness of a realistic rough, shadowed, flat surface element relative to that of a smooth granular surface of the same material, it is manifested directly in both the integral phase function and the spherical albedo of the object. We suggest that, where broad phase angle coverage is possible, spherical albedos may be easily corrected for the effects of shadowing using observed (or assumed) phase functions, and then modeled more robustly using smooth-surface regolith radiative transfer models without further imposed (forward-modeled) shadowing corrections. Our approach attributes observed "power law" phase functions of various slope (and "linear" ranges of magnitude-vs.-phase angle) to shadowing, as have others, and goes on to suggest that regolith-model-based inferences of composition based on shadow-uncorrected spherical albedos overestimate the amount of absorbing material contained in the regolith.

geometric albedos↗
NASA NTRS1994

Numerical Simulations of Self-Focused Pulses Using the Nonlinear Maxwell Equations

This paper will present results in computational nonlinear optics. An algorithm will be described that solves the full vector nonlinear Maxwell's equations exactly without the approximations that are currently made. Present methods solve a reduced scalar wave equation, namely the nonlinear Schrodinger equation, and neglect the optical carrier. Also, results will be shown of calculations of 2-D electromagnetic nonlinear waves computed by directly integrating in time the nonlinear vector Maxwell's equations. The results will include simulations of 'light bullet' like pulses. Here diffraction and dispersion will be counteracted by nonlinear effects. The time integration efficiently implements linear and nonlinear convolutions for the electric polarization, and can take into account such quantum effects as Kerr and Raman interactions. The present approach is robust and should permit modeling 2-D and 3-D optical soliton propagation, scattering, and switching directly from the full-vector Maxwell's equations. Abstract of a proposed paper for presentation at the meeting NONLINEAR OPTICS: Materials, Fundamentals, and Applications, Hyatt Regency Waikaloa, Waikaloa, Hawaii, July 24-29, 1994, Cosponsored by IEEE/Lasers and Electro-Optics Society and Optical Society of America

Goorjian, Peter M.↗
NASA NTRS1994

Numerical Simulations of Light Bullets, Using the Full Vector, Time Dependent, Nonlinear Maxwell Equations

This paper will present results in computational nonlinear optics. An algorithm will be described that solves the full vector nonlinear Maxwell's equations exactly without the approximations that are currently made. Present methods solve a reduced scalar wave equation, namely the nonlinear Schrodinger equation, and neglect the optical carrier. Also, results will be shown of calculations of 2-D electromagnetic nonlinear waves computed by directly integrating in time the nonlinear vector Maxwell's equations. The results will include simulations of 'light bullet' like pulses. Here diffraction and dispersion will be counteracted by nonlinear effects. The time integration efficiently implements linear and nonlinear convolutions for the electric polarization, and can take into account such quantum effects as Kerr and Raman interactions. The present approach is robust and should permit modeling 2-D and 3-D optical soliton propagation, scattering, and switching directly from the full-vector Maxwell's equations.

Goorjian, Peter M.↗
NASA NTRS1995

Numerical Simulations of Light Bullets, Using The Full Vector, Time Dependent, Nonlinear Maxwell Equations

This paper will present results in computational nonlinear optics. An algorithm will be described that solves the full vector nonlinear Maxwell's equations exactly without the approximations that we currently made. Present methods solve a reduced scalar wave equation, namely the nonlinear Schrodinger equation, and neglect the optical carrier. Also, results will be shown of calculations of 2-D electromagnetic nonlinear waves computed by directly integrating in time the nonlinear vector Maxwell's equations. The results will include simulations of 'light bullet' like pulses. Here diffraction and dispersion will be counteracted by nonlinear effects. The time integration efficiently implements linear and nonlinear convolutions for the electric polarization, and can take into account such quantum effects as Karr and Raman interactions. The present approach is robust and should permit modeling 2-D and 3-D optical soliton propagation, scattering, and switching directly from the full-vector Maxwell's equations.

Goorjian, Peter M.↗
NASA NTRS1994

Numerical Simulations of Light Bullets, Using The Full Vector, Time Dependent, Nonlinear Maxwell Equations

This paper will present results in computational nonlinear optics. An algorithm will be described that solves the full vector nonlinear Maxwell's equations exactly without the approximations that are currently made. Present methods solve a reduced scalar wave equation, namely the nonlinear Schrodinger equation, and neglect the optical carrier. Also, results will be shown of calculations of 2-D electromagnetic nonlinear waves computed by directly integrating in time the nonlinear vector Maxwell's equations. The results will include simulations of 'light bullet' like pulses. Here diffraction and dispersion will be counteracted by nonlinear effects. The time integration efficiently implements linear and nonlinear convolutions for the electric polarization, and can take into account such quantum effects as Kerr and Raman interactions. The present approach is robust and should permit modeling 2-D and 3-D optical soliton propagation, scattering, and switching directly from the full-vector Maxwell's equations.

Goorjian, Peter M.↗
DOE OSTI2024

Improved Characterization of Soil Organic Matter by Integrating FT-ICR MS, Liquid Chromatography Tandem Mass Spectrometry, and Molecular Networking: A Case Study of Root Litter Decay under Drought Conditions

Understanding of how soil organic matter (SOM) chemistry is altered in a changing climate has advanced considerably; however, most SOM components remain unidentified, impeding the ability to characterize a major fraction of organic matter and predict what types of molecules, and from which sources, will persist in soil. Here we present a novel approach to better characterize SOM extracts by integrating information from three types of analyses, and we deploy this method to characterize decaying root-detritus soil microcosms subjected to either drought or normal conditions. To observe broad differences in composition, we employed direct infusion Fourier-transform ion cyclotron resonance mass spectrometry (DI-FT-ICR MS). We complemented this with liquid chromatography tandem mass spectrometry (LC-MS/MS) to identify components by library matching. Since libraries contain only a small fraction of SOM components, we also used fragment spectral cosine similarity scores to relate unknowns and library matches through molecular networks. This integrated approach allowed us to corroborate DI-FT-ICR MS molecular formulas using library matches, which included fungal metabolites and related polyphenolic compounds. We also inferred structures of unknowns from molecular networks and improved LC-MS/MS annotation rates from ~5 to 35% by considering DI-FT-ICR MS molecular formula assignments. Under drought conditions, we found greater relative amounts of lignin-like vs condensed aromatic polyphenol formulas and lower average nominal oxidation state of carbon, suggesting reduced decomposition of SOM and/or microbes under stress. Our integrated approach provides a framework for enhanced annotation of SOM components that is more comprehensive than performing individual data analyses in parallel.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Fourier Neural Networks as Function Approximators and Differential Equation Solvers

We present a Fourier neural network (FNN) that can be mapped directly to the Fourier decomposition. The choice of activation and loss function yields results that replicate a Fourier series expansion closely while preserving a straightforward architecture with a single hidden layer. The simplicity of this network architecture facilitates the integration with any other higher-complexity networks, at a data pre- or postprocessing stage. We validate this FNN on naturally periodic smooth functions and on piecewise continuous periodic functions. We showcase the use of this FNN for modeling or solving partial differential equations with periodic boundary conditions. The main advantages of the current approach are the validity of the solution outside the training region, interpretability of the trained model, and simplicity of use.

Fourier decomposition↗
DOE OSTI2024

Neural network interatomic potential-driven analysis of phase stability in Ti–V alloys at the atomistic scale

The evolution of the ω phase in titanium–vanadium (Ti–V) alloys is critical for their mechanical properties, particularly in aerospace and biomedical applications. Here, this study employs a Rapid Artificial Neural Network (RANN) potential to model the ω phase evolution at the atomistic level, demonstrating a high degree of consistency with experimental observations, unlike the Modified Embedded Atom Method (MEAM), which fails to capture this phase transformation accurately. RANN simulations replicate key phenomena such as the nucleation of α precipitates at ω/β interfaces and accurate lattice orientations, enhancing our understanding of phase stability and transformation kinetics. The findings affirm that RANN potentials can significantly improve the prediction accuracy of complex material behaviors, offering a powerful tool for designing advanced materials with tailored properties such as solute effect in various stacking fault energies. This approach not only bridges the gap between theoretical predictions and empirical data but also sets a new direction for future research in materials science, emphasizing the integration of machine learning techniques in the development and optimization of new alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Markov Decision Processes for Intelligent, Risk-Informed Asset-Management Decision-Making

Advanced nuclear reactors are a promising option for aiding the world in achieving its net-zero carbon emission goals, however, there are significant challenges to attaining and maintaining economic competitiveness with other sources of electricity. To improve the economic competitiveness of advanced reactor designs, a project was initiated to explore the use of Markov Decision Processes (MDPs) to guide asset-management decision-making during advanced reactor operation. MDPs are a powerful tool for optimizing decision-making in complex environments and their application to advanced reactors can aid in planning maintenance and repair activities to minimize downtime and maximize generation. The described approach expands on previous work regarding the use of MDPs for operational decision-making through the direct incorporation of real-time plant information. The integral MDP analysis includes information from online component diagnostic tools and the plant’s real-time generation risk assessment (GRA) and probabilistic risk assessment (PRA), which evaluate plant risk from both an economic and safety perspective. The result is an asset-management optimization framework that is based on real-time data regarding plant component status and the current best-estimate of plant risk. The paper presents an overview of the theoretical framework to incorporate the different information pathways into an integral MDP analysis, along with example analyses.

Grabaskas, David↗
DOE OSTI2026

Fidelity-preserving enhancement of ptychography with foundational text-to-image models

Ptychographic phase retrieval enables high-resolution imaging of complex samples but often suffers from artifacts such as grid pathology and multislice crosstalk, which degrade reconstructed images. We propose a plug-and-play (PnP) framework that integrates physics model-based phase retrieval with text-guided image editing using foundational diffusion models. By employing the alternating direction method of multipliers, our approach ensures consensus between data fidelity and artifact removal subproblems, maintaining physical consistency while enhancing image quality. Artifact removal is achieved using a text-guided diffusion image editing method (LEDITS++) with a pre-trained foundational diffusion model, allowing users to specify artifacts for removal in natural language. Demonstrations on simulated and experimental datasets show significant improvements in artifact suppression and structural fidelity, validated by metrics such as peak signal-to-noise ratio and diffraction pattern consistency. This work highlights the combination of text-guided generative models and model-based phase retrieval algorithms as a transferable and fidelity-preserving method for high-quality diffraction imaging.

image editing↗
NASA NTRS1973

Orbit improvement from satellite imaging data obtainable from outer planet missions.

Equations of motion are established for a dynamical system in which a spacecraft flies close to and interacts with an outer planet and one or more of its satellites. For the computation of the state and mass partials needed in a simultaneous orbit correction of n interacting bodies, a notably compact set of variational equations is derived. The above system of differential equations is integrated numerically on a computer. Spacecraft-satellite direction measurements accurate to plus or minus 10 sec were simulated along three representative trajectories (Mariner/Jupiter/Saturn 1977 missions) approaching Io, Titan, and Iapetus to within 41000, 13000, and 7000 km, respectively. The paper concludes with a brief discussion of the need for future work on the orbits of the satellites of the outer planets.

Aksnes, K.↗
NASA NTRS1983

Guidelines for composite materials research related to general aviation aircraft

Guidelines for research on composite materials directed toward the improvement of all aspects of their applicability for general aviation aircraft were developed from extensive studies of their performance, manufacturability, and cost effectiveness. Specific areas for research and for manufacturing development were identified and evaluated. Inputs developed from visits to manufacturers were used in part to guide these evaluations, particularly in the area of cost effectiveness. Throughout the emphasis was to direct the research toward the requirements of general aviation aircraft, for which relatively low load intensities are encountered, economy of production is a prime requirement, and yet performance still commands a premium. A number of implications regarding further directions for developments in composites to meet these requirements also emerged from the studies. Chief among these is the need for an integrated (computer program) aerodynamic/structures approach to aircraft design.

Dow, N. F.↗
NASA NTRS1989

Advanced applications of BEM to inelastic analysis of solids

Newly evolved boundary element solution algorithms are utilized for solving a range of elastoplastic and thermoplastic problems. The first algorithm is the typical iterative procedure in which the unknown boundary solution and the initial stress (or strain) rates are found together in an incremental iterative fashion. The second one is a variable stiffness type approach in which the incremental boundary solution is obtained in a direct (noniterative) manner. The third procedure differs from the two prior algorithms in that volume integration is not needed to incorporate the nonlinear effects in the analysis. Instead, initial stress rates are introduced in the boundary element system by way of particular integrals. The methodology is used in a general purpose, multiregion system that employs quadratic isoparametric shape functions to model the geometry and field variables of the body and can admit up to 15 substructured areas of different material properties.

Banerjee, P. K.↗
NASA NTRSDate not supplied

Extending an Economical Third-Order Inviscid Nodal-Gradient Cell-Centered Finite-Volume Method to Mixed-Element Grids

In this paper, we extend an economical third-order nodal-gradient cell-centered finite-volume method, originally developed for tetrahedral grids, to mixed-element grids. It is shown that the efficient quadratic interpolation formula essential to eliminating second derivatives from a third-order accurate discretization can be easily extended to an arbitrary cell type. For the surface flux integration, we consider a split-face approach, where a quadrilateral face is split into two triangles, and the third-order method for tetrahedra is directly applied. Also, we derive a second-derivative-free, high-order, volume quadrature formula for an arbitrary cell. Numerical results are presented for accuracy verification and applications with three-dimensional nontetrahedral grids.

Computational Fluid Dynamics↗