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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 1,513 records · Page 84
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Virtual Sensors: Using Data Mining Techniques to Efficiently Estimate Remote Sensing Spectra

Various instruments are used to create images of the Earth and other objects in the universe in a diverse set of wavelength bands with the aim of understanding natural phenomena. These instruments are sometimes built in a phased approach, with some measurement capabilities being added in later phases. In other cases, there may not be a planned increase in measurement capability, but technology may mature to the point that it offers new measurement capabilities that were not available before. In still other cases, detailed spectral measurements may be too costly to perform on a large sample. Thus, lower resolution instruments with lower associated cost may be used to take the majority of measurements. Higher resolution instruments, with a higher associated cost may be used to take only a small fraction of the measurements in a given area. Many applied science questions that are relevant to the remote sensing community need to be addressed by analyzing enormous amounts of data that were generated from instruments with disparate measurement capability. This paper addresses this problem by demonstrating methods to produce high accuracy estimates of spectra with an associated measure of uncertainty from data that is perhaps nonlinearly correlated with the spectra. In particular, we demonstrate multi-layer perceptrons (MLPs), Support Vector Machines (SVMs) with Radial Basis Function (RBF) kernels, and SVMs with Mixture Density Mercer Kernels (MDMK). We call this type of an estimator a Virtual Sensor because it predicts, with a measure of uncertainty, unmeasured spectral phenomena.

Srivastava, Ashok N.↗
NASA NTRS1979

MSFC solar activity predictions for satellite orbital lifetime estimation

The procedure to predict solar activity indexes for use in upper atmosphere density models is given together with an example of the performance. The prediction procedure employs a least square linear regression model to generate the predicted smoothed vinculum R sub 13 and geomagnetic vinculum A sub p(13) values. Linear regression equations are then employed to compute corresponding vinculum F sub 10.7(13) solar flux values from the predicted vinculum R sub 13 values. The output is issued principally for satellite orbital lifetime estimations.

Fuler, H. C.↗
DOE OSTI2025

SOC Microstructural Property Estimator

This pre-trained ML model is a tool that uses basic compositional parameters for porous solid oxide cell (SOC) electrodes - the phase fractions and mean particle/pore diameters – as inputs and uses them to estimate additional electrochemical performance parameters: active (i.e., connected) TPB density, all tortuosity factors, and phase pair specific interfacial areas. The electrode is assumed to be composed of two solid phases and a pore phase. The property calculations are performed using neural network regression models trained on a large bank of synthetic electrode microstructural data that NETL has generated using the program DREAM3D (that bank is also hosted on EDX: https://edx.netl.doe.gov/dataset/soc-synthetic-microstructure-bank). This means the generated parameters are based on training from actual measured properties from 3D microstructures, not estimated from geometric simplifications. This tool was developed and is intended to replace percolation theory calculations in models that use hypothetical electrode properties. An example use case would be running SOC performance simulations across a parametric sweep of electrode designs (e.g., varying phase fractions and particle sizes) and assessing how it impacts the electrochemical performance of the SOC. Within the parameter space of the training data (statistics of that parameter space is provided in the readme file), this model achieves sub-5% mean absolute percent errors, an order of magnitude less error than percolation theory across the same parameter space. However, be aware that this tool was developed with parametric simulations in mind, and users are encouraged to assess accuracy for their own specific use case rather than taking accuracy metrics at face value. More info, including a usage guide, is in the included readme file. This tool should be cited with the DOI number provided.

Electrode Microstructure↗
DOE OSTI2024

Airborne LiDAR to Improve Canopy Fuels Mapping for Wildfire Modeling

Increasing conflict between wildfire and the built environment has increased the need for more up-to-date and finer resolution canopy fuels data to improve wildfire modeling and associated risk forecasts. The US Forest Service and US Department of the Interior’s LANDFIRE product, which provides 30-m resolution canopy fuels data for the entire US, is one of the most widely used sources of fuels data. However, the last complete mapping effort for LANDFIRE is based on 2016 conditions, and subsequent updates reflect disturbances 1-2 years behind the release year. Airborne systems equipped with Light Detection and Ranging (LiDAR) sensors can be deployed to actively sense canopy structure and estimate canopy fuels data (cover, height, base height, bulk density) at finer resolutions. Canopy base height (CBH) and canopy bulk density (CBD) are difficult to measure both in the field and in LiDAR point clouds. Still, they are important for accurately modeling crown fires, which are often intense and difficult to contain. Additionally, point cloud datasets are large, and calculations require efficient utilization of computational resources. To address these challenges, we are working on an approach that uses openly available National Ecological Observatory Network (NEON) airborne LiDAR data, with calculations processed in the R programming language and parallelized through the lidR package. CBH and CBD are often derived from tree height, diameter at breast height, and species-specific allometries using the Fire and Fuels Extension of the Forest Vegetation Simulator (FFE-FVS). We aim to test if airborne LiDAR can estimate CBH and CBD without the use of empirical equations. Reliable estimates of canopy fuels data directly from airborne LiDAR could streamline quick, fine-resolution updates for use in wildfire behavior models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Protocol to detect dilution cycles in chemostat experiments and estimate growth rate slopes with linear modeling with R software chemostat_regression

Chemostat growth chambers measure optical density over time and require manual calculation of growth rates. Here, we present chemostat_regression, R software that enables users to automatically identify chemostat cycles and estimate growth rate using a linear regression approach. We describe steps for creating requisite software environment(s), formatting input data, executing the software via command line/RStudio/R-Shiny, interpreting results, assessing the validity of results, and modifying input parameters.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Development of an ERT‐Based Framework for Bentonite Buffers Monitoring From Laboratory Tests: 2. Quantitative Moisture Dynamics Estimation Model

Abstract The long‐term containment of high‐level radioactive waste in geological disposal repositories relies on Engineered Barrier Systems (EBS), with bentonite clay emerging as a candidate material due to its unique properties. Understanding moisture dynamics within bentonite buffers is crucial for EBS performance, as it directly influences the material's swelling capacity, thermal and hydraulic conductivity, mechanical properties, and long‐term evolution under complex thermal‐hydrological‐mechanical (THM) processes. This study develops an advanced Electrical Resistivity Tomography (ERT)‐based framework to quantitatively monitor moisture dynamics under THM conditions. Our framework extends the Waxman‐Smits model to incorporate the coupled effects of temperature, water content, fluid chemistry, and mechanical changes on bentonite's electrical properties. Utilizing HotBENT‐Lab data from our companion paper, which includes electrical conductivity, CT density, and thermocouple measurements, this study offers a novel methodological framework bridging different scales of the model. Our results show that the extended model can estimate water content from ERT data, capturing spatial and temporal variations in moisture distribution within bentonite columns. However, the model tends to overestimate water content compared to CT density‐derived measurements. We address this discrepancy by incorporating a simplified swelling effect model, which improves agreement between ERT and CT density‐based water content estimates. We also discuss model limitations, including simplified treatment of swelling and micropore effects, and propose a conceptual framework for transitioning from laboratory to field applications, addressing challenges such as parameter scalability, field validation methods, and integration of diverse data sources. This ERT‐based framework can potentially advance real‐world moisture monitoring of bentonite‐based EBS in nuclear waste repositories. Plain Language Summary Safely containing high‐level radioactive waste depends on barriers made from materials like bentonite clay, which is effective because it swells and seals in the waste. To ensure these barriers work well over time, it's important to understand how moisture moves through the clay. Our study developed a new method using ERT to monitor moisture levels in bentonite under conditions that mimic those in actual storage sites, including changes in temperature, water content, and mechanical stress. This study improved an existing model to better account for how these factors affect the clay, allowing us to create more accurate moisture maps. Initially, the proposed model overestimated the amount of water in the clay, but its accuracy was improved by factoring in how the clay swells when wet. This study also identified some limitations of the model and suggested ways to adapt it for use in real‐world waste storage sites. This new approach could lead to better monitoring and safety checks for nuclear waste storage systems, helping to ensure long‐term containment. Key Points This work develops an ERT‐based framework extending the Waxman‐Smits model to monitor bentonite moisture dynamics during coupled THM processes The extended model accurately estimates water content from Electrical Resistivity Tomography data, incorporating swelling effects to improve precision This work proposes a conceptual framework for transitioning from laboratory to field applications, advancing EBS monitoring in nuclear waste repositories

Chen, Hang↗
NASA NTRS1978

High performance, high density hydrocarbon fuels

The fuels were selected from 77 original candidates on the basis of estimated merit index and cost effectiveness. The ten candidates consisted of 3 pure compounds, 4 chemical plant streams and 3 refinery streams. Critical physical and chemical properties of the candidate fuels were measured including heat of combustion, density, and viscosity as a function of temperature, freezing points, vapor pressure, boiling point, thermal stability. The best all around candidate was found to be a chemical plant olefin stream rich in dicyclopentadiene. This material has a high merit index and is available at low cost. Possible problem areas were identified as low temperature flow properties and thermal stability. An economic analysis was carried out to determine the production costs of top candidates. The chemical plant and refinery streams were all less than 44 cent/kg while the pure compounds were greater than 44 cent/kg. A literature survey was conducted on the state of the art of advanced hydrocarbon fuel technology as applied to high energy propellents. Several areas for additional research were identified.

Frankenfeld, J. W.↗
NASA NTRS1992

Distant magnetotails of the outer magnetic planets

The distant planetary magnetotails of Jupiter, Saturn, Uranus, and Neptune are assumed to be partially open, hot, long plasma cavities generally in pressure equilibrium with the solar wind. Most of the magnetosheath magnetic field lines drape around the magnetotails. Conservation of momentum density, magnetic field, plasma density, and energy density fluxes are invoked at the tail boundaries to determine the shape of the magnetotails and the variations of plasma and magnetic field characteristics with distance down the magnetotail. Voyager observations are used to initialize calculations in the near-planet portions of each magnetotail. Estimates of magnetotail cross sections, magnetic field strengths, and plasma densities are described as a function of downstream distance. The model accurately predicts properties of the Jovian magnetotail at least as far as Saturn's orbit.

Macek, W. M.↗
DOE OSTI2020

Integrating Overhead Camera Imagery with Reinforcement Learning to Improve Fuel Economy Through Adaptive Traffic Control

Overhead cameras have been deployed for some time as a sensor for traffic control, with many advantages over conventional inductive loop sensors in terms of robustness, ease of installation, and simplicity with respect to maintenance. We explore the utility of such imagery (in particular, fisheye lens cameras) for intelligent traffic control in real-time using reinforcement learning, with a goal of improving fuel economy for the overall intersection and grid of intersections. We summarize our initial work in data collection and approach to ascertain the ability to visually sense vehicular fuel consumption using real-world data. We then describe our deep reinforcement learning topology to test adaptive control informed by the camera capabilities. Next, we tested the proof-of-concept through a variety of simulation scenarios using the Simulation of Urban Mobility (SUMO) traffic simulator, which included different estimates on vehicle classifications, different traffic distributions, and different traffic densities. Six different control policies were tested ranging from simple timing, to heuristic visual-based methods, to actual policies learned via the reinforcement learning approach. Our results demonstrate the feasibility of the approach for controlling traffic lights for better fuel efficiency based on visual vehicle estimates from commercial, fisheye lens cameras.

Karnowski, Thomas↗
NASA NTRS1960

The Solar Wind

Parker's model of a spherically expanding corona, the "solar wind," is compared with D. E. Blackwell's observations of the 1954 minimum equatorial corona. A significant discrepancy is found between the predicted and the observed electron densities at distances from the sun greater than 20 solar radii. Blackwell's data are found to be consistent with a model in which the corona expands mostly within a disk less than 25 solar radii thick, lying within the sun's equatorial plane. The thickness of the disk as a function of distance from the sun is qualitatively explained in terms of magnetic pressure. The solar wind is found to have a considerable effect on the lunar atmosphere. First, the calculated density of the lunar atmosphere is greatly reduced by collisions with protons in the solar wind. If the flux of particles in this wind has the conventional values ranging between 10(exp 10) to 10(exp 11) per sq cm-sec, the calculations yield a lunar pressure of 10(exp -13) atmosphere of argon, in agreement with the value predicted by Elsmore and Whitfield on the basis of observations on the occultation of radio stars. Second, following a suggestion by Gold, it was found that the collisions of solar-wind protons with the lunar surface produce an atmosphere of cold neutral hydrogen with a density of 10(exp 5) per cu cm at the lunar surface. The density falls off at greater distances in accordance with the inverse-square law. Estimates indicate that the interaction of solar particles with the neutral hydrogen will produce an extended lunar ionosphere with a density of the order of 400 protons/cu cm in the vicinity of the moon.

Herring, J. R.↗
NASA NTRS1981

A fireball in Jupiter's atmosphere

One fireball was photographed during two encounters with Jupiter. Its total luminosity was 120,000 0 mag s (at standard range 100 km). If the luminous efficiency proposed by Cook et al. (1981) for slip flow of a meteoroid in its own vapors is employed, an estimated mass of 11 kg is obtained. A rough absolute magnitude is -12.5. If it is noted that the search was conducted for a total of 223 s during two exposures, a number density near Jupiter of 10 to the -28th/cu cm is estimated for masses of meteoroids of 3 kg and greater. This value is about a factor of six smaller than a rough upper limit reached from an extrapolation from terrestrial observations of meteors and comets.

Cook, A. F.↗
NASA NTRS1984

Power dissipation at slow-mode shocks in the distant geomagnetic tail

An estimate is made of the decreases in Poynting flux across slow shocks in the geomagnetic tail detected by the ISEE-3 spacecraft. An electron analyzer and a magnetometer recorded 26 of the events in January-February 1983. Two-dimensional electron velocity distributions parallel to the magnetic field across the shock transition characterized the data. The shocks were of relatively high strength, close to the switch-off limit, and displayed a large upstream Alfven Mach number. The Poynting flux decreased an average of 0.0018-0.0166 ergs/sq cm per sec. The power dissipated from lobe-magnetic energy density to plasma sheet convection across the shocks is estimated to be 5 x 10 to the 18th ergs/sec.

Feldman, W. C.↗
NASA NTRS2004

Experimentally Determined Plasma Parameters in a 30 cm Ion Engine

Single planar Langmuir probes and fiber optic probes are used to concurrently measure the plasma properties and neutral density variation in a 30cm diameter ion engine discharge chamber, from the immediate vicinity of the keeper to the near grid plasma region. The fiber optic probe consists of a collimated optical fiber recessed into a double bore ceramic tube fitted with a stainless steel light-limiting window. The optical fiber probe is used to measure the emission intensity of excited neutral xenon for a small volume of plasma, at various radial and axial locations. The single Langmuir probes, are used to generate current-voltage characteristics at a total of 140 spatial locations inside the discharge chamber. Assuming a maxwellian distribution for the electron population, the Langmuir probe traces provide spatially resolved measurements of plasma potential, electron temperature, and plasma density. Data reduction for the NSTAR TH8 and TH15 throttle points indicates an electron temperature range of 1 to 7.9 eV and an electron density range of 4e10 to le13 cm(sup -3), throughout the discharge chamber, consistent with the results in the literature. Plasma potential estimates, computed from the first derivative of the probe characteristic, indicate potential from 0.5V to 11V above the discharge voltage along the thruster centerline. These values are believed to be excessively high due to the sampling of the primary electron population along the thruster centerline. Relative neutral density profiles are also obtained with a fiber optic probe sampling photon flux from the 823.1 nm excited to ground state transition. Plasma parameter measurements and neutral density profiles will be presented as a function of probe location and engine discharge conditions. A discussion of the measured electron energy distribution function will also be presented, with regards to variation from pure maxwellian. It has been found that there is a distinct primary population found along the thruster centerline, which causes estimates of electron temperature, electron density, and plasma potential, to err on the high side, due this energetic population. Computation of the energy distribution fimction of the plasma clearly indicates the presence of primaries, whose presence become less obvious with radial distance from the main discharge plume.

near grid plasma↗
NASA NTRS2001

ROSAT HRI and ASCA Observations of the Spiral Galaxy NGC 6946 and its Northeast Complex of Luminous Supernova Remnants

Analysis of 80 ks ASCA (Advanced Satellite for Cosmology and Astrophysics) and 60 ks ROSAT HRI (High Resolution Image) observations of the face-on spiral galaxy NGC 6946 are presented. The ASCA image is the first observation of this galaxy above approximately 2 keV. Diffuse emission may be present in the inner approximately 4' extending to energies above approximately 2-3 keV. In the HRI data, 14 pointlike sources are detected, the brightest two being a source very close to the nucleus and a source to the northeast that corresponds to a luminous complex of interacting supernova remnants (SNRs). We detect a point source that lies approximately 30" west of the SNR complex but with a luminosity -1115 of the SNR complex. None of the point sources show evidence of strong variability; weak variability would escape our detection. The ASCA spectrum of the SNR complex shows evidence for an emission line at approximately 0.9 keV that could be either Ne IX at approximately 0.915 keV or a blend of ion stages of Fe L-shell emission if the continuum is fitted with a power law. However, a two-component, Raymond-Smith thermal spectrum with no lines gives an equally valid continuum fit and may be more physically plausible given the observed spectrum below 3 keV. Adopting this latter model, we derive a density for the SNR complex of 10-35 cm(exp -3), consistent with estimates inferred from optical emission-line ratios. The complex's extraordinary X-ray luminosity may be related more to the high density of the surrounding medium than to a small but intense interaction region where two of the complex's SNRs are apparently colliding.

Schlegel, E.↗
NASA NTRS1975

Estimates of saltation threshold and erosion rates on Mars

The Mariner 9 photographs of the Martian surface include many which show crater-associated streaks caused by atmospheric winds. Due to the low density atmosphere of Mars, the wind speeds necessary to move surface particles and thus cause the streaks are apparently very high. The atmospheric-boundary-layer wind tunnel has been used to determine threshold speeds for particles of varying density and diameter and the results for small particles have been extrapolated to estimate somewhat lower threshold speeds on Mars than previous estimates. A series of streak modeling tests is used to derive an erosion-rate correlation function, which is in turn used to estimate erosion rates to the lee of some of the craters on Mars which exhibited time-dependent streak behavior during the mission.

Iversen, J. D.↗
DOE OSTI2021

Investigations on the electronic properties and effect of chitosan capping on the structural and optical properties of zinc aluminate quantum dots

Quantum confined uncapped and chitosan capped nanoparticles of ZnAl 2 O 4 synthesized by microwave-assisted sol–gel method were investigated by structural analysis and optical techniques. X-ray diffraction studies confirmed the formation of cubic spinels with crystallite size 4.5 nm and 3.4 nm, respectively for uncapped and chitosan capped ZnAl 2 O 4 nanoparticles. Chitosan capping produced a blue shift in bandgap energy (3.84 to 3.94 eV) agreeing with size effects according to the Brus equation. A blue shift in emission peak and enhancement in photoluminescence intensity was also observed upon chitosan capping. The electronic band structure and the density of states of the bulk spinel were also calculated using density functional theory. The effective masses of electrons and holes estimated based on the band structure were used to extract the excitonic Bohr radius.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Algorithm 1049: The Delaunay Density Diagnostic

Accurate approximation of a real-valued function depends on two aspects of the available data: the density of inputs within the domain of interest and the variation of the outputs over that domain. There are few methods for assessing whether the density of inputs is sufficient to identify the relevant variations in outputs—i.e., the “geometric scale” of the function—despite the fact that sampling density is closely tied to the success or failure of an approximation method. In this article, we introduce a general purpose, computational approach to detecting the geometric scale of real-valued functions over a fixed domain using a deterministic interpolation technique from computational geometry. The algorithm is intended to work on scalar data in moderate dimensions (2–10). Our algorithm is based on the observation that a sequence of piecewise linear interpolants will converge to a continuous function at a quadratic rate (in L 2 norm) if and only if the data are sampled densely enough to distinguish the feature from noise (assuming sufficiently regular sampling). We present numerical experiments demonstrating how our method can identify feature scale, estimate uncertainty in feature scale, and assess the sampling density for fixed (i.e., static) datasets of input–output pairs. Finally, we include analytical results in support of our numerical findings and have released lightweight code that can be adapted for use in a variety of data science settings.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1991

Estimating Confidence In Data Via Trend Analysis

Recursive equation defines probability-density function storing trends in noisy or potentially erroneous data. Part of algorithm for analysis of trends in data. Developed to determine reliability of data from sensor used to guide robot, and mathematical approach that it represents proves valuable in other applications. Enables computation of statistic (called "confidence statistic") indicating level of confidence in new datum. Generates confidence statistic high or low, depending on whether new datum consistent or inconsistent with previous trends.

Gutow, David A.↗