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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Evaluation of Low-Gravity Smoke Particulate for Spacecraft Fire Detection

Tests were conducted on the International Space Station to evaluate the smoke particulate size from materials and conditions that are typical of those expected in spacecraft fires. Five different materials representative of those found in spacecraft (Teflon, Kapton, cotton, silicone rubber and Pyrell) were heated to temperatures below the ignition point with conditions controlled to provide repeatable sample surface temperatures and air flow. The air flow past the sample during the heating period ranged from quiescent to 8 cm/s. The effective transport time to the measurement instruments was varied from 11 to 800 seconds to simulate different smoke transport conditions in spacecraft. The resultant aerosol was evaluated by three instruments which measured different moments of the particle size distribution. These moment diagnostics were used to determine the particle number concentration (zeroth moment), the diameter concentration (first moment), and the mass concentration (third moment). These statistics were combined to determine the diameter of average mass and the count mean diameter and by assuming a log-normal distribution, the geometric mean diameter and the geometric standard deviations were also calculated. Smoke particle samples were collected on TEM grids using a thermal precipitator for post flight analysis. The TEM grids were analyzed to determine the particle morphology and shape parameters. The different materials produced particles with significantly different morphologies. Overall the majority of the average smoke particle sizes were found to be in the 200 to 400 nanometer range with the quiescent cases and the cases with increased transport time typically producing with substantially larger particles. The results varied between materials but the smoke particles produced in low gravity were typically twice the size of particles produced in normal gravity. These results can be used to establish design requirements for future spacecraft smoke detectors.

Fire↗
NASA NTRS2004

A Preliminary ZEUS Lightning Location Error Analysis Using a Modified Retrieval Theory

The ZEUS long-range VLF arrival time difference lightning detection network now covers both Europe and Africa, and there are plans for further expansion into the western hemisphere. In order to fully optimize and assess ZEUS lightning location retrieval errors and to determine the best placement of future receivers expected to be added to the network, a software package is being developed jointly between the NASA Marshall Space Flight Center (MSFC) and the University of Nevada Las Vegas (UNLV). The software package, called the ZEUS Error Analysis for Lightning (ZEAL), will be used to obtain global scale lightning location retrieval error maps using both a Monte Carlo approach and chi-squared curvature matrix theory. At the core of ZEAL will be an implementation of an Iterative Oblate (IO) lightning location retrieval method recently developed at MSFC. The IO method will be appropriately modified to account for variable wave propagation speed, and the new retrieval results will be compared with the current ZEUS retrieval algorithm to assess potential improvements. In this preliminary ZEAL work effort, we defined 5000 source locations evenly distributed across the Earth. We then used the existing (as well as potential future ZEUS sites) to simulate arrival time data between source and ZEUS site. A total of 100 sources were considered at each of the 5000 locations, and timing errors were selected from a normal distribution having a mean of 0 seconds and a standard deviation of 20 microseconds. This simulated "noisy" dataset was analyzed using the IO algorithm to estimate source locations. The exact locations were compared with the retrieved locations, and the results are summarized via several color-coded "error maps."

Elander, Valjean↗
NASA NTRS1998

Distribution and observed associations of orthostatic blood pressure changes in elderly general medicine outpatients

Factors associated with orthostatic blood pressure change in elderly outpatients were determined by surveying 398 medical clinical outpatients aged 65 years and older. Blood pressure was measured with random-zero sphygmomanometers after patients were 5 minutes in a supine and 5 minutes in a standing position. Orthostatic blood pressure changes were at normally distributed levels with systolic and diastolic pressures dropping an average of 4 mm Hg (standard deviation [SD]=15 mm Hg) and 2 mm Hg (SD=11 mm Hg), respectively. Orthostatic blood pressure changes were unassociated with age, race, sex, body mass, time since eating, symptoms, or other factors. According to multiple linear regression analysis, supine systolic pressure, chronic obstructive pulmonary disease (COPD), and diabetes mellitus were associated with a decrease in systolic pressure on standing. Hypertension, antiarthritic drugs, and abnormal heartbeat were associated with an increase in systolic pressure on standing. For orthostatic diastolic pressure changes, supine diastolic pressure and COPD were associated with a decrease in diastolic pressure on standing. Congestive heart failure was associated with an increase in standing diastolic pressure. Using logistic regression analysis, only supine systolic pressure was associated with a greater than 20-mm Hg drop in systolic pressure (n=53, prevalence=13%). Supine diastolic pressure and COPD were the only variables associated with a greater than 20-mm Hg drop in diastolic pressure (n=16, prevalence=4%). These factors may help physicians in identifying older persons at risk for having orthostatic hypotension.

Non-NASA Center↗
DOE OSTI2024

Quantifying Streambed Grain Size, Uncertainty, and Hydrobiogeochemical Parameters Using Machine Learning Model YOLO

Abstract Streambed grain sizes control river hydro‐biogeochemical (HBGC) processes and functions. However, measuring their quantities, distributions, and uncertainties is challenging due to the diversity and heterogeneity of natural streams. This work presents a photo‐driven, artificial intelligence (AI)‐enabled, and theory‐based workflow for extracting the quantities, distributions, and uncertainties of streambed grain sizes from photos. Specifically, we first trained You Only Look Once, an object detection AI, using 11,977 grain labels from 36 photos collected from nine different stream environments. We demonstrated its accuracy with a coefficient of determination of 0.98, a Nash–Sutcliffe efficiency of 0.98, and a mean absolute relative error of 6.65% in predicting the median grain size of 20 ground‐truth photos representing nine typical stream environments. The AI is then used to extract the grain size distributions and determine their characteristic grain sizes, including the 10th, 50th, 60th, and 84th percentiles, for 1,999 photos taken at 66 sites within a watershed in the Northwest US. The results indicate that the 10th, median, 60th, and 84th percentiles of the grain sizes follow log‐normal distributions, with most likely values of 2.49, 6.62, 7.68, and 10.78 cm, respectively. The average uncertainties associated with these values are 9.70%, 7.33%, 9.27%, and 11.11%, respectively. These data allow for the computation of the quantities, distributions, and uncertainties of streambed HBGC parameters, including Manning's coefficient, Darcy‐Weisbach friction factor, top layer interstitial velocity magnitude, and nitrate uptake velocity. Additionally, major sources of uncertainty in grain sizes and their impact on HBGC parameters are examined.

58 GEOSCIENCES↗
NASA NTRS1966

Log-normal model for microbial survival in heat sterilization

An analytical model is developed for the survival times of organisms in heat sterilization in which the probability of inactivation as a function of exposure time is log-normally distributed. Experimental data is examined relative to this model and it is concluded that the model is valid except during the initial period of heating when an additional interaction between the organisms and their surrounding medium appears to be present. At long heating times, the log-normal model appears more accurate for extrapolating to low survival probabilities than the usual logarithmic survivor curves and is generally more conservative.

SURVIVAL↗
NASA NTRS2012

Particle Morphology and Size Results from the Smoke Aerosol Measurement Experiment-2

Results are presented from the Reflight of the Smoke Aerosol Measurement Experiment (SAME-2) which was conducted during Expedition 24 (July-September 2010). The reflight experiment built upon the results of the original flight during Expedition 15 by adding diagnostic measurements and expanding the test matrix. Five different materials representative of those found in spacecraft (Teflon, Kapton, cotton, silicone rubber and Pyrell) were heated to temperatures below the ignition point with conditions controlled to provide repeatable sample surface temperatures and air flow. The air flow past the sample during the heating period ranged from quiescent to 8 cm/s. The smoke was initially collected in an aging chamber to simulate the transport time from the smoke source to the detector. This effective transport time was varied by holding the smoke in the aging chamber for times ranging from 11 to 1800 s. Smoke particle samples were collected on Transmission Electron Microscope (TEM) grids for post-flight analysis. The TEM grids were analyzed to observe the particle morphology and size parameters. The diagnostics included a prototype two-moment smoke detector and three different measures of moments of the particle size distribution. These moment diagnostics were used to determine the particle number concentration (zeroth moment), the diameter concentration (first moment), and the mass concentration (third moment). These statistics were combined to determine the diameter of average mass and the count mean diameter and, by assuming a log-normal distribution, the geometric mean diameter and the geometric standard deviations can also be calculated. Overall the majority of the average smoke particle sizes were found to be in the 200 nm to 400 nm range with the quiescent cases producing some cases with substantially larger particles.

Urban, David L.↗
NASA NTRS1974

An analysis of fracture trace patterns in areas of flat-lying sedimentary rocks for the detection of buried geologic structure

Two study areas in a cratonic platform underlain by flat-lying sedimentary rocks were analyzed to determine if a quantitative relationship exists between fracture trace patterns and their frequency distributions and subsurface structural closures which might contain petroleum. Fracture trace lengths and frequency (number of fracture traces per unit area) were analyzed by trend surface analysis and length frequency distributions also were compared to a standard Gaussian distribution. Composite rose diagrams of fracture traces were analyzed using a multivariate analysis method which grouped or clustered the rose diagrams and their respective areas on the basis of the behavior of the rays of the rose diagram. Analysis indicates that the lengths of fracture traces are log-normally distributed according to the mapping technique used. Fracture trace frequency appeared higher on the flanks of active structures and lower around passive reef structures. Fracture trace log-mean lengths were shorter over several types of structures, perhaps due to increased fracturing and subsequent erosion. Analysis of rose diagrams using a multivariate technique indicated lithology as the primary control for the lower grouping levels. Groupings at higher levels indicated that areas overlying active structures may be isolated from their neighbors by this technique while passive structures showed no differences which could be isolated.

Podwysocki, M. H.↗
NASA NTRS1980

A hill-sliding strategy for initialization of Gaussian clusters in the multidimensional space

A hill sliding technique was devised to extract Gaussian clusters from the multivariate probability density estimate of sample data for the first step of iterative unsupervised classification. Each cluster was assumed to posses a unimodal normal distribution. A clustering function proposed distinguished elements of a cluster under formation from the rest in the feature space. Initial clusters were extracted one by one according to the hill sliding tactics. A dimensionless cluster compactness parameter was proposed as a universal measure of cluster goodness and used satisfactorily in test runs with LANDSAT multispectral scanner data. The normalized divergence, defined by the cluster divergence divided by the entropy of the entire sample data, was utilized as a general separability measure between clusters. An overall clustering objective function was set forth in terms of cluster covariance matrices, from which the cluster compactness measure could be deduced. Minimal improvement of initial data partitioning was evaluated by this objective function in eliminating scattered sparse data points. The hill sliding clustering technique developed herein has the potential applicability to decomposition any multivariate mixture distribution into a number of unimodal distributions when an appropriate distribution function to the data set is employed.

Park, J. K.↗
DOE OSTI2017

Thermal pressure in the cold neutral medium of nearby galaxies

Dynamic and thermal processes regulate the structure of the multiphase interstellar medium (ISM), and ultimately establish how galaxies evolve through star formation. Thus, to constrain ISM models and better understand the interplay of these processes, it is of great interest to measure the thermal pressure (P{sub th}) of the diffuse, neutral gas. By combining [C ii] 158 μm, H i, and CO data from 31 galaxies selected from the Herschel KINGFISH sample, we have measured thermal pressures in 534 predominantly atomic regions with typical sizes of ∼1 kiloparsec. We find a distribution of thermal pressures in the P{sub th}/k∼10{sup 3}--10{sup 5} K cm{sup −3} range. For a sub-sample of regions with conditions similar to those of the diffuse, neutral gas in the Galactic plane, we find thermal pressures that follow a log-normal distribution with a median value of P{sub th}/k ≈ 3600 K cm{sup −3}. These results are consistent with thermal pressure measurements using other observational methods. We find that P{sub th} increases with radiation field strength and star formation activity, as expected from the close link between the heating of the gas and the star formation rate. Our thermal pressure measurements fall in the regime where a two-phase ISM with cold and warm neutral media could exist in pressure equilibrium. Finally, we find that the midplane thermal pressure of the diffuse gas is about ∼30% of the vertical weight of the overlying ISM, consistent with results from hydrodynamical simulations of self-regulated star formation in galactic disks.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Statistical analyses of reservoir and fracturing parameters for a multifractured shale oil reservoir in Mississippi

The use of multifractured horizontal wells has improved the efficiency of hydrocarbon extraction from shale gas and oil plays. It is highly desirable to estimate the characteristics of the reservoir and well fracturing through production data analysis. Production rate transient data from 16 wells in the Mississippi sections were analyzed to estimate local reservoir permeability and hydraulic fracture parameters. Key factors affecting well productivity have been identified for optimizing future well completion. Based on the theory of distance of investigation during transient linear flow, the reservoir matrix permeability of TMS was estimated to be between 53 nd and 210 nd, averaging at 116 nd. The matrix permeability follows the lognormal distribution and is considered homogeneous according to the coefficient of variation. The fracture half-length was estimated using the matrix permeability data from the rate transient analysis. The fracture half-length was found to have a mean value of 234 ft with a standard deviation of 66 ft in a normal distribution. The fracture conductivity was back-calculated by matching pseudosteady production rate data to Guo et al's (SPE Reserve Eval Eng.12, 2009, 879) productivity model for boundary-dominated flow. The fracture conductivity was estimated to range from 0.4 md-ft to 3.2 md-ft, averaging at 1.4 md-ft. Based on Guo et al's (SPE Reserve Eval Eng.12, 2009, 879) well productivity model applied to TMS condition, well productivity can be improved significantly by increasing fracture length and conductivity. Future TMS wells should be completed with conductivity values of greater than 10 md-ft.

04 OIL SHALES AND TAR SANDS↗
NASA NTRS1987

Probabilistic SSME blades structural response under random pulse loading

The purpose is to develop models of random impacts on a Space Shuttle Main Engine (SSME) turbopump blade and to predict the probabilistic structural response of the blade to these impacts. The random loading is caused by the impact of debris. The probabilistic structural response is characterized by distribution functions for stress and displacements as functions of the loading parameters which determine the random pulse model. These parameters include pulse arrival, amplitude, and location. The analysis can be extended to predict level crossing rates. This requires knowledge of the joint distribution of the response and its derivative. The model of random impacts chosen allows the pulse arrivals, pulse amplitudes, and pulse locations to be random. Specifically, the pulse arrivals are assumed to be governed by a Poisson process, which is characterized by a mean arrival rate. The pulse intensity is modelled as a normally distributed random variable with a zero mean chosen independently at each arrival. The standard deviation of the distribution is a measure of pulse intensity. Several different models were used for the pulse locations. For example, three points near the blade tip were chosen at which pulses were allowed to arrive with equal probability. Again, the locations were chosen independently at each arrival. The structural response was analyzed both by direct Monte Carlo simulation and by a semi-analytical method.

Shiao, Michael↗
NASA NTRS1994

Distributions of the interplanetary magnetic field revisited

The adequacy of the power spectrum to characterize the variations of a parameter depends on whether or not the parameter has a Gaussian distribution. We here perform very simple tests of Gaussianity on the distribution. We here perform very simple tests of Gaussianity on the distributions of the magnitudes of the interplanetary magnetic field, and on the distributions of the components; that is, we find the first four cumulants of the distributions (mean, variance, skewness, and kurtosis) and their solar cycle variations. We find, consistent with other recent analyses, that the traditional distributions of the 1-hour averaged magnitude are not distributed normally or lognomally as has often been assumed and the 1-hour averaged z component is found to have a nonzero kurtosis. Thus the power spectrum is insufficient to completely characterize these variations and polyspectra are needed. We have isolated variations in the 1/f frequency region of the spectrum and show that the distributions of the magnitudes have nonzero skewness and kurtosis, the magnitudes are not distributed lognormally, and the distributions of the components have nonzero kurtosis. Thus higher-order spectra are again needed for a full characterization.

Feynman, Joan↗
DOE OSTI2018

Probability Distributions for Effective Permeability of Potentially Leaking Wells at CO 2 Sequestration Sites

Wells with defects originating from either poor completions or subsequent damage arising from chemical, thermal and/or mechanical stresses provide potential pathways for leakage of carbon dioxide (CO 2 ) and brine from a CO 2 sequestration site. This report provides a methodology for analyzing data on the frequency of occurrence of defective wells and the effective permeability of the damaged wells. The results include bimodal, log-normal distributions of the effective permeability of wells in addition to other distributions designed to provide a measure of the likelihood of encountering a leaking well in a CO 2 storage project.

58 GEOSCIENCES↗
NASA NTRS2022

Non-Gaussian Distributions of TOA SW Flux as Observed by MISR and CERES

The Top of Atmosphere (TOA) shortwave (SW) flux, converted from Terra Multi angle Imaging‐SpectroRadiometer (MISR) narrow band albedos, is compared with that measured from Clouds and the Earth’s Radiant Energy System (CERES). We describe the probability density function (PDF) of the monthly TOA SW flux and how the statistical third moment, skewness, can impact the quantification of the flux. The PDF of the SW flux is not normally distributed but positively skewed. In both sets of observations, the near-global (80S-80N) median value of the SW flux is ≈3 W/m 2 less than the mean value, due to the positive skewness of the distribution. The near-global mean TOA SW flux converted from MISR is about 7 W/m 2 (≈7%) less than CERES measured flux during the last two decades. Surprisingly, hemispheric asymmetry exists with TOA SW observations from Terra platform. SH reflects 3.92 W/m 2 and 1.15 W/m 2 more mean SW flux than NH, from MISR and CERES Single Scanner Footprint products, respectively. We can infer that the offsetting by morning clouds in the SH is greater than the effect of hemispheric imbalance of SW flux caused by different land masses in two hemispheres. While the characteristics of the two SW fluxes broadly agree with each other, differences in the regional PDF from two different SW fluxes are substantially different over high cloud regions and high altitude regions. Our analysis shows that some parts of the different skewness from two measurements may be attributed to the different calibration of the radiance anisotropy over high cloud scenes.

satellite measurements↗
NASA NTRS1984

High-frequency wave normals in the solar wind

High-frequency (0.01-0.04 Hz) magnetic fluctuations in 506 ten-minute intervals of contemporaneous Explorer 35 and Apollo 12 measurements made in the solar wind near the morning side of the earth's bow shock show the presence of a large population of disturbances resembling Alfven waves. Each wavefront normal is systematically aligned (median deviation = 35 deg) with the associated ten-minute average of the magnetic field. Because of variability in the direction of this ten-minute average, from one interval to another, the coupled wavefront-normal distribution is nearly isotropic in solar ecliptic coordinates, in contrast with the results of other studies of waves at much lower frequency indicating outward propagation from the sun. Presumably the high frequency waves discussed here are stirred into isotropy (in solar ecliptic coordinates) by following the low frequency fluctuations. As these waves maintain their alignment of wavefront-normal with the field ten-minute average despite the great variation of the field ten-minute average, a strong physical alignment constraint is inferred.

Herbert, F.↗
DOE OSTI2020

Reconciling Chord Length Distributions and Area Distributions for Fields of Fractal Cumulus Clouds

While the total cover of broken cloud fields can in principle be obtained from one-dimensional measurements, the cloud size distribution normally differs between two-dimensional (area) and one-dimensional retrieval (chord length) methods. In this study, we use output from high-resolution Large Eddy Simulations to generate a transfer function between the two. We retrieve chord lengths and areas for many clouds, and plot the one as a function of the other, and vice versa. We find that the cloud area distribution conditional on the chord length behaves like a gamma distribution with well-behaved parameters, with a mean μ=1.1L and a shape parameter β=L−0.645. Using this information, we are able to generate a transfer function that can adjust the chord length distribution so that it comes much closer to the cloud area distribution. Our transfer function improves the error in predicting the mean cloud size, and is performs without strong biases for smaller sample sizes. However, we find that the method is still has difficulties in accurately predicting the frequency of occurrence of the largest cloud sizes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Evaluating Safeguards Statistical Assumptions via Stochastic Simulation

Herein, the authors built and tested a stochastic simulation to estimate achieved detection probabilities (DPs) on a stratum basis, over a tailorable range of diverted amounts from 0 to 2 SQ, using typical IAEA inspection data: i.e., SQ in stratum, number of items, number of gross/partial/bias defect measurements conducted, and realistic relative standard deviation (RSD) values for typical IAEA verification measurements. For bulk strata, the model calculates achieved DP at 0.01 SQ diversion increments; for item strata, the model calculates DP using the smallest realistic diversion increment (e.g., a plate, pin, or coupon). After successfully benchmarking against IAEA deterministic models, the simulation was used to test the sensitivity of DP to certain standard assumptions and selected input parameters. First, the equal defect assumption was tested; the results suggest significant complexity in the effectiveness of partial defect measurements. Next, the authors explored the sensitivity of DP to the assumed RSD of attribute tests. Then, the authors compared non-normal models for instrument performance (e.g., logistic, step, or arbitrary functions) to the typical results from a normal distribution (characterized by RSD). This last comparison was supplemented with experimentally derived performance data for an HM-5. The HM-5 was used to make enrichment measurements on both LEU and HEU MTR fuel elements as plates were removed, and the results fit with logistic and step curves and applied in the simulation. These stochastic DP results were compared to DP estimates from a deterministic model assuming a normal curve and typical RSD, yielding insights that could improve effectiveness in the field. These early results illustrate the potential of stochastic models to better understand achieved DP and to improve safeguards effectiveness.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2021

Stochastic Approaches for Calculating and Aggregating Detection Probabilities for Nuclear Material Diversion

The authors built and tested a stochastic simulation to estimate achieved detection probabilities (DPs) on a stratum basis, over a tailorable range of diverted amounts from 0 to 2 significant quantities (SQ), using typical International Atomic Energy Agency (IAEA) inspection data: i.e., SQ in stratum, number of items, number of gross/partial/bias defect measurements conducted, and realistic relative standard deviation (RSD) values for typical IAEA verification measurements. For bulk strata, the model calculates achieved DP at 0.01 SQ diversion increments; for item strata, the model calculates DP using the smallest realistic diversion increment (e.g., a plate, pin, or coupon). After successfully benchmarking against IAEA deterministic models, the simulation was used to test the sensitivity of DP to certain standard assumptions and selected input parameters. First, the equal defect assumption was tested; the results suggest significant complexity in the effectiveness of partial defect measurements. Next, the authors explored the sensitivity of DP to the assumed RSD of attribute tests. Then, the authors compared non-normal models for instrument performance (e.g., logistic, step, or arbitrary functions) to the typical results from a normal distribution (characterized by RSD). This last comparison was supplemented with experimentally derived performance data for an HM-5 gamma spectrometer. The HM-5 was used to make enrichment measurements on both LEU and HEU MTR fuel elements as plates were removed, and the results fit with logistic and step curves and applied in the simulation. These stochastic DP results were compared to DP estimates from a deterministic model assuming a normal curve and typical RSD, yielding insights that could improve effectiveness in the field. These early results illustrate the potential of stochastic models to better understand achieved DP and to improve safeguards effectiveness.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗