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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

Middle Man Concept for In-Orbit Collision Risks Mitigation, CAESAR and CARA Examples

This paper describes the conjunction analysis which has to be performed using data provided by JSpOC. This description not only demonstrates that Collision Avoidance is a 2- step process (close approach detection followed by risk evaluation for collision avoidance decision) but also leads to the conclusion that there is a need for a Middle Man role. After describing the Middle Man concept, this paper introduces two examples with their similarities and particularities: the American civil space effort delivered by the NASA CARA team (Conjunction Assessment Risk Analysis) and the French response CAESAR (Conjunction Assessment and Evaluation Service: Alerts and Recommendations). For both, statistics are presented and feedbacks discussed. All together, around 80 satellites are served by CARA and/or CAESAR. Both processes regularly evolve in order either to follow JSpOC upgrades or to improve analysis according to experience acquired during the past years.

conjunction↗
NASA NTRS1978

Multispectral scanner system parameter study and analysis software system description, volume 2

The author has identified the following significant results. The integration of the available methods provided the analyst with the unified scanner analysis package (USAP), the flexibility and versatility of which was superior to many previous integrated techniques. The USAP consisted of three main subsystems; (1) a spatial path, (2) a spectral path, and (3) a set of analytic classification accuracy estimators which evaluated the system performance. The spatial path consisted of satellite and/or aircraft data, data correlation analyzer, scanner IFOV, and random noise model. The output of the spatial path was fed into the analytic classification and accuracy predictor. The spectral path consisted of laboratory and/or field spectral data, EXOSYS data retrieval, optimum spectral function calculation, data transformation, and statistics calculation. The output of the spectral path was fended into the stratified posterior performance estimator.

Landgrebe, D. A.↗
DOE OSTI2021

Constraining the hadronic spectrum and repulsive interactions in a hadron resonance gas via fluctuations of conserved charges

We simultaneously incorporate two common extensions of the hadron resonance gas model, namely the addition of extra, unconfirmed resonances to the particle list and the excluded volume repulsive interactions. We emphasize the complementary nature of these two extensions and identify combinations of conserved charge susceptibilities that allow to constrain them separately. In particular, ratios of second-order susceptibilities like $\chi_{11}^{BQ}/\chi_2^B$ and $\chi_{11}^{BS}/\chi_2^B$ are sensitive only to the baryon spectrum, while fourth-to-second order ratios like $\chi_4^B/\chi_2^B$, $\chi_{31}^{BS}/\chi_{11}^{BS}$, or $\chi_{31}^{BQ}/\chi_{11}^{BQ}$ are mainly determined by repulsive interactions. Analysis of the available lattice results suggests the presence of both the extra states in the baryon-strangeness sector and the repulsive baryonic interaction, with indications that hyperons have a smaller repulsive core than non-strange baryons. Furthermore, the modified hadron resonance gas model presented here significantly improves the description of lattice QCD susceptibilities at chemical freeze-out and can be used for the analysis of event-by-event fluctuations in heavy-ion collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Kinetics-Informed Neural Networks

Chemical kinetics and reaction engineering consists of the phenomenological framework for the disentanglement of reaction mechanisms, optimization of reaction performance and the rational design of chemical processes. Here, we utilize feed-forward artificial neural networks as basis functions to solve ordinary differential equations (ODEs) constrained by differential algebraic equations (DAEs) that describe microkinetic models (MKMs). We present an algebraic framework for the mathematical description and classification of reaction networks, types of elementary reaction, and chemical species. Under this framework, we demonstrate that the simultaneous training of neural nets and kinetic model parameters in a regularized multi-objective optimization setting leads to the solution of the inverse problem through the estimation of kinetic parameters from synthetic experimental data. We analyze a set of scenarios to establish the extent to which kinetic parameters can be retrieved from transient kinetic data, and assess the robustness of the methodology with respect to statistical noise. Furthermore, this approach to inverse kinetic ODEs can assist in the elucidation of reaction mechanisms based on transient data.

36 MATERIALS SCIENCE↗
NASA NTRS1973

Parametric description of thermospheric ion composition results.

Results of an attempt to accumulate an ion composition data base for an international reference ionosphere (IRI) with the aid of polar-orbiting satellites. A progress report is presented on the preparation of the results from the Bennett RF ion spectrometer experiment on Ogo 4 and 6 using the most extensive set of thermospheric ion composition data yet available. An example of the pole-to-pole distributions of all ions detected by the spectrometer on Ogo 6 is given which shows considerable structure resulting from both altitude and latitude variations. Also, an example is given of the type of analysis made possible by the combined scope of the Ogo ion composition data base and the IRI statistical sorting routine.

Taylor, H. A., Jr.↗
NASA NTRS1977

Seismic energy transmission in an intensively scattering environment

In order to account for some special features of lunar seismograms, namely, the gradual build-up of the signal, the extremely prolonged tail, and the lack of apparent coherence among three orthogonal components of ground motion, a statistical approach is proposed for describing transmission of seismic energy through a medium in which strong scattering takes place. A seismic diffusion theory is presented for a medium with randomly distributed scatterers of a given size distribution. A solution of the resulting diffusion equation for an impulsive energy source gives a curve which fairly closely reproduces the envelope of typical lunar impact seismograms. Since the model is based on constant diffusivity, long-range transmission will require a combination of diffusion and wave propagation treatments for accurate description.

Nakamura, Y.↗
NASA NTRS1982

Aspects of clear air turbulence severity forecasting and detection

Factors influencing the accuracy of the forecasts of incidences of clear air turbulence (CAT) are discussed, along with techniques for improved verification. Descriptive ranking terms for the intensity of CAT events, ranging from light to extreme, are developed, and meteorological parameters used for predictions are reviewed, including jetstream core location, vertical and horizontal wind shears, stable layers, tropopause height, trough speed, 500-mb vorticity, surface fronts, pressure centers and cyclogenesis, and wind speeds near mountain ridges. Methods of remote detection of CAT, particularly by using radiometry sensitive to the IR water vapor band, are noted to have had some success in detecting actual CAT events and decreasing false alarms. Statistical aspects of CAT encounter severity are discussed, including the establishment of confidence intervals for thresholds of detection of CATs of varying intensities.

Ehernberger, L. J.↗
DOE OSTI2025

Time-domain theory of transient heat conduction in the local limit

Ultrafast and nanoscale heat conduction demands a unified theoretical framework that rigorously bridges macroscopic transport equations with microscopic material properties derived from statistical physics. Existing empirical generalizations of Fourier's law often lack a solid microscopic foundation, failing to connect observed non-Fourier behavior with underlying atomic-scale mechanisms. In this work, we present a time-domain theory of transient heat conduction rooted in Zwanzig's statistical theory of irreversible processes. Central to this framework is the time-domain transport function $\overleftrightarrow{𝑍}$⁡(𝑡) defined through equilibrium time-correlation functions of heat fluxes. This function generalizes the conventional concept of steady-state thermal conductivity, governing the transition of conduction dynamics from onset second sound type wave propagation at finite speeds to diffusion-dominated behavior across broad temporal and spatial scales. Unlike phonon hydrodynamic models that rely on mesoscopic constructs such as phonon drift velocity, our approach provides a quantitative and microscopic description of intrinsic memory effects in transient heat fluxes and applies universally to bulk materials at any temperature or length scale. By integrating atomistic-scale first-principles calculations with continuum-level macroscopic equations, this framework offers a robust foundation for numerical simulations of transient temperature fields. Furthermore, it facilitates the interpretation and design of transient thermal grating experiments using nanometer-scale heat sources and ultrafast laser systems in the extreme ultraviolet and x-ray wavelength ranges, advancing our understanding of heat dissipation dynamics.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1984

A statistical evaluation of the advantages of Landsat Thematic Mapper data in comparison to Multispectral Scanner data

On July 16, 1982, the second decade of land remote sensing from space was inaugurated with the successful launch of Landsat-4. This satellite carries the Multispectral Scanner (MSS) and a new sensor, the Thematic Mapper (TM). The TM represents the result of an effort in which all of the major improvements in remote-sensing capability were simultaneously integrated into one system. An experiment was developed and conducted to quantify the effect of each TM sensor parameter on classification accuracy. This paper discusses the experimental design and summarizes the results obtained using TM data acquired over the Washington, DC area on November 2, 1982. Attention is given to a study site/data description, the experimental design, photointerpretation and digitization, spectral simulation, radiometric simulation, and spatial simulation.

Williams, D. L.↗
DOE OSTI2024

Data and scripts associated with a manuscript on residence time distribution simulation in two 10-kilometer long river sections

This data package is associated with the publication “On the Transferability of Residence Time Distributions in Two 10-km Long River Sections with Similar Hydromorphic Units” submitted to the Journal of Hydrology (Bao et al. 2024).Quantifying hydrologic exchange fluxes (HEFs) at the stream-groundwater interface, along with their residence time distributions (RTDs) in the subsurface, is crucial for managing water quality and ecosystem health in dynamic river corridors. However, directly simulating high-spatial resolution HEFs and RTDs can be a time-consuming process, particularly for watershed-scale modeling. Efficient surrogate models that link RTDs to hydromorphic units (HUs) may serve as alternatives for simulating RTDs in large-scale models. One common concern with these surrogate models, however, is the transferability of the relationship between the RTDs and HUs from one river corridor to another. To address this, we evaluated the HEFs and the resulting RTD-HU relationships for two 10-kilometer-long river corridors along the Columbia River, using a one-way coupled three-dimensional transient surface-subsurface water transport modeling framework that we previously developed. Applying this framework to the two river corridors with similar HUs allows for quantitative comparisons of HEFs and RTDs using both statistical tests and machine learning classification models. This data package includes the model inputs files and the simulation results data. This data package contains 10 folders. The modeling simulation results data are in the folders 100H_pt_data and 300area_pt_data, for the study domain Hanford 100H and 300 area respectively. The remaining eight folders contain the scripts and data to generate the manuscript figures. The file-level metadata file (Bao_2024_Residence_Time_Distribution _flmd.csv) includes a list of all files contained in this data package and descriptions for each. The data dictionary file (Bao_2024_Residence_Time_Distribution _dd.csv) includes column header definitions and units of all tabular files.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Evaluation of obstacle modelling approaches for resource assessment and small wind turbine siting: case study in the northern Netherlands

Abstract. Growth in adoption of distributed wind turbines for energy generation is significantly impacted by challenges associated with siting and accurate estimation of the wind resource. Small turbines, at hub heights of 40 m or less, are greatly impacted by terrestrial obstacles such as built structures and vegetation that can cause complex wake effects. While some progress in high-fidelity complex fluid dynamics (CFD) models has increased the potential accuracy for modelling the impacts of obstacles on turbulent wind flow, these models are too computationally expensive for practical siting and resource assessment applications. To understand the efficacy of available models in situ, this study evaluates classic and commonly used methods alongside new state-of-the-art lower-order models derived from CFD simulations and machine learning approaches. This evaluation is conducted using a subset of an extensive original dataset of measurements from more than 300 operational wind turbines in the northern Netherlands. The results show that data-driven methods (e.g. machine learning and statistical modelling) are most effective at predicting production at real sites with an average error in annual energy production of 2.5 %. When sufficient data may not be available de novo to support these data-driven approaches, models derived from high-fidelity simulations show promise and reliably outperform classic methods. On average these models have 6.3 %–11.5 % error compared with 26 % for classic methods and 27 % baseline error for reanalysis data without obstacle correction. While more performant on average, these methods are also sensitive to the quality of obstacle descriptions and reanalysis inputs.

17 WIND ENERGY↗
NASA NTRS2010

A Computational Approach for Probabilistic Analysis of LS-DYNA Water Impact Simulations

NASA s development of new concepts for the Crew Exploration Vehicle Orion presents many similar challenges to those worked in the sixties during the Apollo program. However, with improved modeling capabilities, new challenges arise. For example, the use of the commercial code LS-DYNA, although widely used and accepted in the technical community, often involves high-dimensional, time consuming, and computationally intensive simulations. Because of the computational cost, these tools are often used to evaluate specific conditions and rarely used for statistical analysis. The challenge is to capture what is learned from a limited number of LS-DYNA simulations to develop models that allow users to conduct interpolation of solutions at a fraction of the computational time. For this problem, response surface models are used to predict the system time responses to a water landing as a function of capsule speed, direction, attitude, water speed, and water direction. Furthermore, these models can also be used to ascertain the adequacy of the design in terms of probability measures. This paper presents a description of the LS-DYNA model, a brief summary of the response surface techniques, the analysis of variance approach used in the sensitivity studies, equations used to estimate impact parameters, results showing conditions that might cause injuries, and concluding remarks.

Horta, Lucas G.↗
NASA NTRSDate not supplied

Architectures of Exoplanetary Systems: Towards a Multi-planet Model for Reproducing the Planet Radius Valley and Intra-system Size Similarity

Multi-planet systems provide crucial insights into the architectures and correlations within planetary systems, which in turn offer clues into their formation and evolution histories. Through the thousands of exoplanet candidates that it discovered, NASA's Kepler mission revealed that systems with multiple transiting planets are common. We describe a new model for inferring the exoplanet population observed by Kepler, which combines a semi-parametric description of planetary systems with a prescription for envelope mass-loss due to photoevaporation. This new model is a"hybrid" of the maximum AMD (angular momentum deficit) model in which the orbital excitations of the planets are drawn by distributing the system's critical AMD (He et al. 2020), and a photoevaporation model for sculpting the observed radius valley (Neil & Rogers 2020). This is an update to the SysSim suite of exoplanet population models derived from forward modeling the Kepler detection pipeline. The hybrid model is constrained by the observed statistics of multi-transiting systems, including additional constraints from the distribution of planet radii and their intra-system size patterns. This model is capable of producing a planet radius valley as well as a preference for planet size similarity. However, we find that the Kepler catalog exhibits features that are even more significant (i.e., it has a deeper observed radius valley and stronger size similarity) than the best-fit model. We use this model to infer the intrinsic planet radius valley as well as the distribution of primordial planet masses and core masses.

kepler↗
DOE OSTI2024

Quantitative Insight to Fission Gas Pores Distribution in Irradiated Annular U-10Zr Metallic Fuel Using Machine Learning

Metallic fuels, particularly U-10Zr and its performance in reactor irradiation conditions, have been thoroughly investigated and are a promising candidate for next-generation sodium-cooled fast spectrum nuclear reactors. Irradiation in reactors can lead to the formation of fission gas and increased pore formation which can significantly impact fuel performance. Due to the large number of pores and various phases formed in metallic fuel during irradiation, a quantitative description of fission gas pores as a function of irradiation conditions is not yet available, undermining the fidelity of fuel performance modeling to support fuel qualification. It has been difficult to clearly detect pore boundaries and distinguish matrix phases from fission gas pores using optical microscopy by using simple threshold methods working with low magnification images. The pre-trained deep learning model for fission gas pore detection was applied to ~10,260 high magnification scanning electron microscopy images. The model increased the accuracy of fission gas pore segmentation to obtain statistical features, which cannot be processed manually. A pre-trained decision tree model was used to classify pores as isolated or connected pores, providing new insight into the correlation between the movement of lanthanides, solid fission products, and the radial temperature gradient developed in fuel irradiation conditions. This paper emphasizes the potential that artificial intelligence-based machine learning models have to accelerate qualification and support nuclear fuel development.

36 MATERIALS SCIENCE↗
NASA NTRS2004

Novel Image Processing Interface to Relate DSB Spatial Distribution from Immunofluorescence Foci Experiments to the State-of-the-Art Models of DNA Breakage

A recently developed software (NASARadiationTrackImage) allows a quick and automatic segmentation of foci that indicate spatial localization of specific proteins that are visualized by immunofluorescence. Of interest are the spatial and temporal distribution of foci such as gammaH2AX, a signal of the phosphorylation of a variant of the histone H2A that has been shown to correspond to DSBs, or proteins involved in DSB processing, such as ATM, Rad51, and p53, following exposures of human cells to high charge and energy (HZE) ion irradiation. Experimental data are recorded as sets of two-dimensional images in color with cells and foci of gammaH2AX, ATM, Rad51 or others shown. Different cells, levels of radiation and timing after radiation were recorded. The software allows us to calculate the number of foci per cell, overall intensity of light in foci and their spatial organization. A simple statistical model allows for testing of foci overlap (eclipse). A more complex statistical model previously known as DNAbreak simulates track structure and random chromosome geometry. It has one adjustable parameter corresponding to an average intensity of DSB creation in cubic micrometers of DNA volume per particle track or unit dose. Its limitation is the low-resolution limit both in physical space and DSB's along DNA. It works adequately on the scale of a cell and provides further insights on how the geometry of tracks and DNA affects genomic damage of the cell and subsequent repair. Future developments of the model for the description of the time evolution of DNA damage response proteins, and more robust track structure models will be discussed.

Ponomarev, A. L.↗
NASA NTRS1980

Geodetic positioning using a global positioning system of satellites

Geodetic positioning using range, integrated Doppler, and interferometric observations from a constellation of twenty-four Global Positioning System satellites is analyzed. A summary of the proposals for geodetic positioning and baseline determination is given which includes a description of measurement techniques and comments on rank deficiency and error sources. An analysis of variance comparison of range, Doppler, and interferometric time delay to determine their relative geometric strength for baseline determination is included. An analytic examination to the effect of a priori constraints on positioning using simultaneous observations from two stations is presented. Dynamic point positioning and baseline determination using range and Doppler is examined in detail. Models for the error sources influencing dynamic positioning are developed. Included is a discussion of atomic clock stability, and range and Doppler observation error statistics based on random correlated atomic clock error are derived.

Fell, P. J.↗
NASA NTRS1999

User's Guide for Monthly Vector Wind Profile Model

The background, theoretical concepts, and methodology for construction of vector wind profiles based on a statistical model are presented. The derived monthly vector wind profiles are to be applied by the launch vehicle design community for establishing realistic estimates of critical vehicle design parameter dispersions related to wind profile dispersions. During initial studies a number of months are used to establish the model profiles that produce the largest monthly dispersions of ascent vehicle aerodynamic load indicators. The largest monthly dispersions for wind, which occur during the winter high-wind months, are used for establishing the design reference dispersions for the aerodynamic load indicators. This document includes a description of the computational process for the vector wind model including specification of input data, parameter settings, and output data formats. Sample output data listings are provided to aid the user in the verification of test output.

Adelfang, S. I.↗
DOE OSTI2023

Λ Baryon Production in ν¯µ Interactions in the MicroBooNE Detector

The Cabibbo suppressed production of $\Lambda$ baryons in anti-neutrino interactions with nuclei is a rare process that is yet to be measured with a modern neutrino detector with automated reconstruction. The cross section for this process is sensitive to a number of unique nuclear effects, most notably the secondary interactions of the produced hyperon while attempting to escape from the nucleus. Other interactions within the nuclear remnant can impact the estimation of neutrino energy in oscillation measurements, and thus an accurate description of the nuclear environment is required. The strangeness violating hyperon production process is only available to anti-neutrinos. The model of this interaction is implemented into the NuWro neutrino interaction Monte Carlo simulation, and some predictions are presented, focusing on the role of nuclear effects. This model introduces a hyperon-nucleus potential, which calculations from hypernuclear theory permit to be strongly repulsive in th e case of $\Sigma$ baryons. The presence of this potential is found to sculpt the shape of the differential cross section in some variables. The MicroBooNE detector will be described, followed by a description of a measurement of the flux averaged, restricted phase space cross section of Cabibbo suppressed $\Lambda$ baryon production. A sophisticated event selection is employed, as a very large quantity of background neutrino interactions must be removed to perform the measurement with any sensitivity. This selection introduces some novel techniques such as the island finding method, and achieves a background reduction of $\sim 10^6$, with an efficiency of around 7\%. The calculation of the systematic uncertainties will be explained, including two procedures explored to handle sources of background with extremely poor simulation statistics: an in-situ constraint using data from sidebands, and a visual inspection of the data and simulation to remove the troublesome background events. The sensitivity to the $\Lambda$ baryon production cross section is calculated in the form of Bayesian posterior probability distributions, combining the systematic uncertainties with data and simulation statistical uncertainties. As a rare process, the statistical uncertainties are highly non-Gaussian, and the Bayesian approach is applied to include the full shapes of these uncertainties. Data corresponding to $2.2 \times 10^{20}$ protons on target of neutrino mode running and $4.9 \times 10^{20}$ protons on target of anti-neutrino running is analysed. When the data was unblinded, five $\Lambda$ production candidates were selected from the data, consistent with the MC simulation prediction of $5.3 \pm 1.1$ events. The final estimated cross section is $1.8^{+2.0}_{-1.6} \times 10^{-40}$cm$^2/$Ar when employing the sideband constraint procedure. A similar result of $2.0^{+2.2}_{-1.8} \times 10^{-40}$cm$^2/$Ar is obtained when performing the visual scan instead. The methods used in t his analysis are intended to be easily exported to other LArTPC detectors such as the Short Baseline Near Detector.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗