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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

A Diagnostic Analysis of the Kennedy Space Center LDAR Network: Data Characteristics - 1

An analytical framework is developed in which to analyze climatological VHF (66 MHz) radiation measurements taken by the Kennedy Space Center Lightning Detection and Ranging (LDAR) network. A 19-month noise-filtered sample of LDAR observations is examined using this framework. It is found that the climatological VHF source density as observed by LDAR falls off approximately 10 dB every 71 km of ground range away from the network centroid (a 31 km e-folding scale). From this framework it is inferred that the underlying source distribution is likely inverse exponential in amplitude, with a log-slope of 126-147 mW(sup -1/2). The underlying vertical distribution of VHF sources is approximately normally distributed with a mean altitude of 9 km and a standard deviation of 2.7 km; this implies that the loss of below-horizon sources has a negligible effect on column-integrated source densities within 200 km ground range. At medium to far ranges, location errors are primarily radial and have a slightly asymmetric distribution whose first moment increases as range squared. Error moments estimated from observed lightning are significantly higher than those from aircraft-based signal generator or analytic solution estimates, suggesting that timing errors arising from poor signal identification and discrimination may dominate over timing errors arising from nominal sensor resolution. The VHF source properties of individual LDAR-observed flashes are computed and an analytic expression for flash detection efficiency vs. range is derived. This reveals nearly constant flash detection efficiency to 80-94 km range from the network centroid.

Boccippio, D. J.↗
NASA NTRS2015

Predicting the Mineral Composition of Dust Aerosols: Representing Key Processes - Part 1

Soil dust aerosols created by wind erosion are typically assigned globally uniform physical and chemical properties within Earth system models, despite known regional variations in the mineral content of the parent soil. Mineral composition of the aerosol particles is important to their interaction with climate, including shortwave absorption and radiative forcing, nucleation of cloud droplets and ice crystals, heterogeneous formation of sulfates and nitrates, and atmospheric processing of iron into bioavailable forms that increase the productivity of marine phytoplankton. Here, aerosol mineral composition is derived by extending a method that provides the composition of a wet-sieved soil. The extension accounts for measurements showing significant differences between the mineral fractions of the wetsieved soil and the emitted aerosol concentration. For example, some phyllosilicate aerosols are more prevalent at silt sizes, even though they are nearly absent at these diameters in a soil whose aggregates are dispersed by wet sieving. We calculate the emitted mass of each mineral with respect to size by accounting for the disintegration of soil aggregates during wet sieving. These aggregates are emitted during mobilization and fragmentation of the original undispersed soil that is subject to wind erosion. The emitted aggregates are carried far downwind from their parent soil. The soil mineral fractions used to calculate the aggregates also include larger particles that are suspended only in the vicinity of the source. We calculate the emitted size distribution of these particles using a normalized distribution derived from aerosol measurements. In addition, a method is proposed for mixing minerals with small impurities composed of iron oxides. These mixtures are important for transporting iron far from the dust source, because pure iron oxides are more dense and vulnerable to gravitational removal than most minerals comprising dust aerosols. A limited comparison to measurements from North Africa shows that the model extensions result in better agreement, consistent with a more extensive comparison to global observations as well as measurements of elemental composition downwind of the Sahara, as described in companion articles.

aerosols↗
DOE OSTI2019

Distributions of the Mean for Lognormally Distributed Data - 19427

In environmental sciences, a distribution of the mean is often needed for right-skewed data. For example, risk assessments are often based on distributions of the mean to obtain upper confidence limits (UCLs) for analyte concentrations, and, in probabilistic performance assessment (PPA) models, parameters are given distributions rather than deterministic values, and they are usually given distributions of their mean rather than the population distributions to account for the large spatial and temporal domains to which they are applied. How this distribution of the mean is developed depends on the characteristics of the parameter's full distribution and how the parameter relates to its use. In this presentation, I will discuss the implications of a right skew in distribution development. Parameters may vary over orders of magnitude and/or may be right-skewed. The material property of saturated hydraulic conductivity, Ks, is a prime example of such a parameter. Right-skewed parameters are often assumed to follow lognormal distributions. If X follows a lognormal distribution, then log(X) follows a normal distribution. For some right-skewed parameters, practitioners go back and forth between the two forms of the data depending on their needs. For example, it may be preferred to use the untransformed version of X in a model or equation, but it is easier to visualize the parameter values on a logarithmic scale. However, distribution development for the average value of the parameter will differ depending on whether X or log(X) is modeled. This difference is due to Jensen's Inequality, a theorem which states that the expected value of a concave function of a variable is less than or equal to the same function of the expected value of the variable; a logarithm is a concave function. In other words, the mean of log(X) is always less than or equal to the log of the mean of X and therefore the mean estimated from a distribution based on log(X) is less than or equal to the mean estimated from a distribution based on X. If a parameter is naturally considered on a log scale by subject matter experts, then distributions developed for the mean of log(X) may be more consistent with the use of the parameters in the literature than distributions developed for X. The statistical decisions of distribution development will be discussed within the context of right-skewed, lognormal data. These issues include method-of-moments versus maximum likelihood estimation of the distribution parameters and the use of bootstrapping to aid in the visualization of a distribution of the mean. The details surrounding Jensen's Inequality will be explained and visualized within the context of distribution development of a right-skewed parameter such as saturated hydraulic conductivity. (authors)

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

A Further Study of the t{sub Burst} of GRBs: Rest-frame Properties, External Plateau Contributions, and Multiple Parameter Analysis

Zhang et al. propose to redefine the true γ-ray burst (GRB) central engine activity duration, t{sub burst}, by considering the contributions from the prompt γ-ray emission, X-ray flare, and internal plateau features. With a comprehensive study of a large sample of Swift GRBs, it is shown that the t{sub burst} distribution in the observer frame consists of a bimodal feature, suggesting the existence of a new population of ultra-long GRBs. In this work, we make a series of further studies on t{sub burst}: we update the Swift GRB sample up to 2016 June; we investigate the properties of t{sub burst} distribution in the rest frame; we redefine t{sub burst} by involving external plateau contributions; and we make a multiple parameter analysis to investigate whether the bursts within the ultra-long population are statistically different in the sense of other features besides the duration distribution. We find that for all situations, the distribution of t{sub burst} requires two normal distributions in logarithmic space to provide a good fit both in the observer frame and in the rest frame. Considering the observational gap effect would not completely erase the bimodal distribution feature. However, the bursts within the ultra-long population may have no statistical difference in the sense of other features besides the duration term. We thus suggest that if the ultra-long population of GRBs indeed exists, their central engine and radiation mechanisms should be similar to those of the normal population, but they have a longer central engine activity timescale.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1977

An estimate of field size distributions for selected sites in the major grain producing countries

The field size distributions for the major grain producing countries of the World were estimated. LANDSAT-1 and 2 images were evaluated for two areas each in the United States, People's Republic of China, and the USSR. One scene each was evaluated for France, Canada, and India. Grid sampling was done for representative sub-samples of each image, measuring the long and short axes of each field; area was then calculated. Each of the resulting data sets was computer analyzed for their frequency distributions. Nearly all frequency distributions were highly peaked and skewed (shifted) towards small values, approaching that of either a Poisson or log-normal distribution. The data were normalized by a log transformation, creating a Gaussian distribution which has moments readily interpretable and useful for estimating the total population of fields. Resultant predictors of the field size estimates are discussed.

Podwysocki, M. H.↗
DOE OSTI2016

WE-H-207A-03: The Universality of the Lognormal Behavior of [F-18]FLT PET SUV Measurements

Purpose: Log transforming [F-18]FDG PET standardized uptake values (SUVs) has been shown to lead to normal SUV distributions, which allows utilization of powerful parametric statistical models. This study identified the optimal transformation leading to normally distributed [F-18]FLT PET SUVs from solid tumors and offers an example of how normal distributions permits analysis of non-independent/correlated measurements. Methods: Forty patients with various metastatic diseases underwent up to six FLT PET/CT scans during treatment. Tumors were identified by nuclear medicine physician and manually segmented. Average uptake was extracted for each patient giving a global SUVmean (gSUVmean) for each scan. The Shapiro-Wilk test was used to test distribution normality. One parameter Box-Cox transformations were applied to each of the six gSUVmean distributions and the optimal transformation was found by selecting the parameter that maximized the Shapiro-Wilk test statistic. The relationship between gSUVmean and a serum biomarker (VEGF) collected at imaging timepoints was determined using a linear mixed effects model (LMEM), which accounted for correlated/non-independent measurements from the same individual. Results: Untransformed gSUVmean distributions were found to be significantly non-normal (p<0.05). The optimal transformation parameter had a value of 0.3 (95%CI: −0.4 to 1.6). Given the optimal parameter was close to zero (which corresponds to log transformation), the data were subsequently log transformed. All log transformed gSUVmean distributions were normally distributed (p>0.10 for all timepoints). Log transformed data were incorporated into the LMEM. VEGF serum levels significantly correlated with gSUVmean (p<0.001), revealing log-linear relationship between SUVs and underlying biology. Conclusion: Failure to account for correlated/non-independent measurements can lead to invalid conclusions and motivated transformation to normally distributed SUVs. The log transformation was found to be close to optimal and sufficient for obtaining normally distributed FLT PET SUVs. These transformations allow utilization of powerful LMEMs when analyzing quantitative imaging metrics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Development of an empirical model relating permeability and specific stiffness for rough fractures from numerical deformation experiments: Fracture Permeability and Stiffness

The coupling between hydraulic and mechanical properties of porous and fractured geologic media are critical for many geophysical processes and practical applications. Thus, the prediction of this linkage between these properties is broadly important. Here we present a potentially predictive model that links fracture permeability and specific stiffness with empirical coefficients dependent on fracture roughness, correlation length of aperture field, and rock mechanical properties. The equation was developed empirically from results of modeling the deformation and flow through synthetic fractures with aperture fields that follow a normal distribution. The fractures were subjected to increasing normal stress and deformed following an elastic model. Specific stiffness was directly quantified from these numerical deformation experiments. Permeability was estimated through calculation of the local flow field while considering effects of local fracture roughness and tortuosity. The empirical model roughly captures the transition from effective medium to percolation flow regimes with increasing specific stiffness.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Theoretical estimate of the effect of thermal agitation on ribosome motion generated by stochastic microswimming

The effect of thermal agitation on ribosome motion is evaluated through the Péclet number, assuming that the ribosome is self-propelled along the mRNA during protein synthesis by a swimming stroke consisting of a cycle of stochastically-generated ribosome configurations involving its two subunits. The ribosome velocity probability distribution function is obtained, giving an approximately normal distribution. Its mean and variance together with an estimate of the in vivo free diffusion coefficient of the ribosome and using only configuration changes of small size, give a Péclet number similar to motor proteins and microorganisms. These results suggest the feasibility of the stochastic microswimming hypothesis to explain ribosome motion. - Highlights: • Hypothesis: the ribosome swims along the mRNA during protein synthesis. • How can withstand the thermal agitation of the particles in the surrounding fluid? • The Péclet number Pe is calculated estimating the in vivo diffusion coefficient. • With small size deformations the ribosome has speeds similar to motor proteins. • Similar Pe values for the ribosome and the motor proteins mean feasible hypothesis.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1989

Probability distribution of wind retrieval error for the NASA scatterometer

The NASA scatterometer (NSCAT) is a spaceborne scatterometer scheduled to be deployed in the mid-1990s. An analysis of the wind retrieval error distribution for wind estimates based on backscatter measurements made by the NSCAT instrument is presented. The results are based on an end-to-end simulation of the scatterometer instrument and data processing. In general, the distribution of the wind speed error, when normalized, is independent of the true wind speed and direction. The wind speed error can be characterized by a normal distribution. The wind direction error is independent of the true wind speed, but depends on the true wind direction. Details for wind vectors with true wind speeds from 3 m/s to 33 m/s and true wind directions from 0 to 360 deg are presented.

Leotta, Daniel F.↗
NASA NTRS2001

A Diagnostic Analysis of the Kennedy Space Center LDAR Network: Data Characteristics - 1

An analytic framework is developed in which to analyze climatological VHF (66 MHz) radiation measurements taken by the Kennedy Space Center Lightning Detection and Ranging (LDAR) network. A 19 month noise-filtered sample of LDAR observations is examined using this framework. It is found that the climatological impulsive VHF source density as observed by LDAR falls off approximately 10 dB every 71 km of ground range away from the network centroid (a 31 km e-folding scale). The underlying vertical distribution of impulsive VHF sources is approximately normally distributed with a mean altitude of 9 km and a standard deviation of 2.7 km; this implies that the loss of below-horizon sources has a negligible effect on column-integrated source densities within a 200 km ground range. At medium to far ranges, location errors are primarily radial and have a slightly asymmetric distribution whose standard deviation increases as r(exp 2). Error moments estimated from observed lightning are significantly higher than those from aircraft-based signal generator or analytic estimates. LDAR bulk flash detection efficiency is predicted to be above 90% to 94-113 km range from the network centroid and to fall below 10% at ranges greater than 200-240 km.

Boccippio, D. J.↗
DOE OSTI2017

Release Fractions from Airborne Fluid and Slurry Spills

Release fractions are commonly used to make conservative estimates of emissions from processes and are applied to characterize industrial operations to safeguard workers and public. Release fractions cannot be derived theoretically; they must be measured. Appropriate measurements are limited. This paper describes tests that were conducted to provide large-scale release fraction data for estimating releases from three operations proposed for waste remediation at the Hanford Site in Richland, Washington. Experiments were conducted to measure release fractions of three processes: 1) pipe discharge of liquid and slurry in free fall into a liquid or slurry, 2) jet transfer of contents to the other side of the tank either impacting the tank wall or falling into the fluid pool, and 3) high pressure fan jet striking a steel plate or simulated waste from a small stand-off distance. The tests were conducted without forced ventilation in an enclosed prototypic ¼-scale model of a 3785 m^3 (1 million gallon) tank in use at the Hanford Site for storage of radioactive waste. Aerosol releases were characterized based on filter samples of aerosol collected near the process stream, tank wall, and tank top to determine release fraction at engineering scale. Particle size distribution measurements were analyzed to determine whether the particles were in the respirable range. The release fractions for the top of the unventilated tank ranged from 9x10-7 to 6x10-4 depending on the process simulated. The particle size distribution was determined to be log-normally distributed with geometric mean diameters ranging from 3 to 8 µm. Thus, all particles are conservatively considered to be “respirable.”

aerosol generation, release fraction, water spill,↗
NASA NTRS1980

Bivariate normal, conditional and rectangular probabilities: A computer program with applications

Some results for the bivariate normal distribution analysis are presented. Computer programs for conditional normal probabilities, marginal probabilities, as well as joint probabilities for rectangular regions are given: routines for computing fractile points and distribution functions are also presented. Some examples from a closed circuit television experiment are included.

Swaroop, R.↗
DOE OSTI2020

Creep Deformation and Dynamic Grain Growth in an Interstitial-Free Steel

Dynamic grain growth is demonstrated to be much faster than static grain growth in a body-centered-cubic, interstitial-free steel sheet material at 850°C. Dynamic grain growth occurs during concurrent plastic deformation at elevated temperature, whereas static grain growth occurs during static annealing. Grain growth during steady-state plastic flow in tension at 850°C to a true strain of 0.2 at a true-strain rate of 10 -4 s -1 doubled grain size, while static annealing for the same time produced no increase in grain size. This is described as dynamic normal grain growth (DNGG) because no abnormally large grains were observed. The recrystallized microstructure of the steel demonstrated a log-normal distribution of grain sizes. DNGG produced bimodal grain size distributions that deviate from the theoretical expectation of a simple shift to larger sizes during normal growth. The bimodal distributions contained a remnant of small grains that were not consumed during grain growth. DNGG produced a crystallographic texture that is unique from both the recrystallized material and that produced by lattice rotation alone. DNGG strengthened the {111}&lang;110&rang; and {111}&lang;112&rang; components of the strong γ-fiber component in the original recrystallization texture. Lattice rotation from tensile deformation, by contrast, strengthened the α-fiber components that intersect the original γ-fiber.

36 MATERIALS SCIENCE↗
DOE OSTI2020

The role of the spatial heterogeneity and correlation length of surface wettability on two-phase flow in a CO 2 -water-rock system

This study characterized and modeled heterogeneous surface wettability in sandstone and investigated the role of spatial heterogeneity and correlation length of surface wettability on relative permeability in a supercritical CO 2 (scCO 2 )-brine-rock system. Understanding the role of wettability heterogeneity on relative permeability is essential to geological CO 2 sequestration, oil and gas recovery, and contaminated groundwater remediation. Although numerous studies have attempted to understand the influences of surface wettability, capillary number (Ca), and viscosity ratio, the role of the spatial variation and correlation length of surface wettability on two-phase flow in three-dimensional (3D) porous media has not been unraveled due to the challenges in the measurement and representation of realistic rock surface wettability. In this work, we conducted in-situ measurements of surface contact angle (CA) in a Bentheimer sandstone after CO 2 flooding using micro-computed tomography (micro-CT), and found that the pore-scale CA distribution on rock surfaces followed a log-normal distribution associated with a spatial correlation length. Based on the statistical information from CT scanning, a Gaussian random field was used to model CA distributions that had desired standard deviations and spatial correlation lengths, which were then adjusted within a certain range of values for sensitivity analyses to study their combined effects on the two-phase flow in the porous medium using the lattice Boltzmann (LB) method. The LB two-phase flow simulation was accelerated using hybrid, multicore parallel computing to overcome the challenges in simulating multiphase flow in a large 3D domain having 800 × 800 × 600 nodes. The simulation results showed that the surface wettability heterogeneity (i.e., standard deviation of CA) had a lesser effect on the relative permeability of the wetting fluid (water) but a more significant impact on the relative permeability of the non-wetting fluid (scCO 2 ). The Corey model was used to fit the LB-simulated relative permeability curves of water and scCO 2 and showed that the variations in the relative permeability curves for both water and scCO 2 increased as the standard deviation and spatial correlation length of CA increased. This study illustrated that the assumption of homogeneous surface wettability may cause errors in multiphase flow simulations. Furthermore, the impacts of both the standard deviation and spatial correlation length of CAs should be accounted for. This is the first study that explored the spatial correlation lengths associated with CA distributions on sandstone surfaces and comprehensively investigated the roles of both spatial variation and correlation length of CA on two-phase flow properties in 3D porous media. The optimized LB multiphase flow model was proved a powerful tool to study the interplays and combined effects of these statistical parameters, which had critical applications in numerous natural and engineering processes that involved multiphase flow in porous media.

58 GEOSCIENCES↗
DOE OSTI2015

Quantitative study of particle size distribution in an in-situ grown Al–TiB{sub 2} composite by synchrotron X-ray diffraction and electron microscopy

Synchrotron X-ray diffraction and transmission electron microscopy (TEM) were applied to quantitatively characterize the average particle size and size distribution of free-standing TiB{sub 2} particles and TiB{sub 2} particles in an in-situ grown Al–TiB{sub 2} composite. The detailed evaluations were carried out by X-ray line profile analysis using the restricted moment method and multiple whole profile fitting procedure (MWP). Both numerical methods indicate that the formed TiB{sub 2} particles are well crystallized and free of crystal defects. The average particle size determined from different Bragg reflections by the restricted moment method ranges between 25 and 55 nm, where the smallest particle size is determined using the 110 reflection suggesting the highest lateral-growth velocity of (110) facets. The MWP method has shown that the in-situ grown TiB{sub 2} particles have a very low dislocation density (~ 10{sup 11} m{sup −} {sup 2}) and their size distribution can be described by a log-normal distribution. Good agreement was found between the results obtained from the restricted moment and MWP methods, which was further confirmed by TEM. - Highlights: • Accurate quantitative characterization of in-situ grown T{sub i}B{sub 2} particles has been achieved. • Particle size anisotropy was revealed indicating 110 facets being largest during T{sub i}B{sub 2} growth. • A wide size distribution was observed for T{sub i}B{sub 2} particles with a dominant size smaller than 100 nm.

36 MATERIALS SCIENCE↗
NASA NTRS1995

Computing Tolerance Factors And Noncentral t Distribution

TF, Tolerance Factors and Noncentral t Distribution computer program, computes tolerance factor from normal-distribution sample for arbitrarily specified coverage probability, confidence level, and any positive (integer or noninteger) number of degrees of freedom. Used extensively in engineering and quality analyses. Used in place of reference tables. Written in Microsoft QuickBasic v2.0.

Huang, Zhaofeng↗
DOE OSTI2024

Determining reference standard strength for neutron-irradiated reduced activation ferritic/martensitic steel F82H by Bayesian method

The deterministic approach widely adopted in the design of structural components relies on systematically defined design limits using empirically determined safety factors. However, this approach is not always appropriate because structures are subjected to a variety of loads in the practical environment, which may result in excessively conservative design limits. In recent years, a more rigorous probabilistic approach that incorporates material strength distributions has become an important solution. In the probabilistic approach, the probability density functions of material strength properties underpin the design criteria. Here, the objective of this study is to identify the density distribution functions that best describe tensile properties of irradiated F82H to define a reference strength for DEMO design. Due to the limited number of existing data, this study specifically employs a Bayesian prediction method based on Monte Carlo simulations to determine a material reference value with statistical reliability and to investigate its effectiveness. For example, the dependence of tensile properties of 300 °C irradiated materials on irradiation damage and the range predicted by 95% Bayesian estimation was evaluated. As a statistical model for the dose dependence of statistical parameters, the normal distribution exhibited a better fit for 0.2% proof strength and tensile strength, whereas the distribution of total elongation data gave comparable reference values for both the normal and Weibull distribution models. Both models gave comparable criteria for the distribution of total elongation data. The Weibull model also gave better results for uniform elongation. The function best describing the model was a logarithmic law for both 0.2% proof strength and tensile strength, while a power law for both total and uniform elongation, which allowed for more comprehensive data prediction of irradiation data with statistical accuracy for DEMO reactor design.

36 MATERIALS SCIENCE↗