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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 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Cerebrospinal fluid pressure in conscious head-down tilted rats

The acute effects of a 1-h -45 deg head-down tilt on continouously recorded cerebrospinal fluid pressure (PCSF) of conscious rats are studied in order to investigate the shift of blood volume into the thoracic cavity in microgravity. PCSF, evaluated in 15-min time blocks over a 3-h experiment, increased slightly (less than 0.05) during the first 30 min of a control hour at 0 deg. There was a transient increase for about 5 min immediately after tilt (-45 deg) that may have been due to head movement after the position change. PCSF was statistically unchanged (above 0.05) during the second (-45 deg) hour and the third (0 deg) recovery hour. It is shown that the dynamics of intracranial pressure regulation can accommodate the acute cephalad fluid shift after tilting.

Severs, Walter B.↗
NASA NTRS2001

Disk Alloy Development

The advanced powder metallurgy disk alloy ME3 was designed using statistical screening and optimization of composition and processing variables in the NASA HSR/EPM disk program to have extended durability at 1150 to 1250 "Fin large disks. Scaled-up disks of this alloy were produced at the conclusion of this program to demonstrate these properties in realistic disk shapes. The objective of the UEET disk program was to assess the mechanical properties of these ME3 disks as functions of temperature, in order to estimate the maximum temperature capabilities of this advanced alloy. Scaled-up disks processed in the HSR/EPM Compressor / Turbine Disk program were sectioned, machined into specimens, and tested in tensile, creep, fatigue, and fatigue crack growth tests by NASA Glenn Research Center, in cooperation with General Electric Engine Company and Pratt & Whitney Aircraft Engines. Additional sub-scale disks and blanks were processed and tested to explore the effects of several processing variations on mechanical properties. Scaled-up disks of an advanced regional disk alloy, Alloy 10, were used to evaluate dual microstructure heat treatments. This allowed demonstration of an improved balance of properties in disks with higher strength and fatigue resistance in the bores and higher creep and dwell fatigue crack growth resistance in the rims. Results indicate the baseline ME3 alloy and process has 1300 to 1350 O F temperature capabilities, dependent on detailed disk and engine design property requirements. Chemistry and process enhancements show promise for further increasing temperature capabilities.

Gabb, Tim↗
NASA NTRS2003

Automated Monitoring with a BSP Fault-Detection Test

The figure schematically illustrates a method and procedure for automated monitoring of an asset, as well as a hardware- and-software system that implements the method and procedure. As used here, asset could signify an industrial process, power plant, medical instrument, aircraft, or any of a variety of other systems that generate electronic signals (e.g., sensor outputs). In automated monitoring, the signals are digitized and then processed in order to detect faults and otherwise monitor operational status and integrity of the monitored asset. The major distinguishing feature of the present method is that the fault-detection function is implemented by use of a Bayesian sequential probability (BSP) technique. This technique is superior to other techniques for automated monitoring because it affords sensitivity, not only to disturbances in the mean values, but also to very subtle changes in the statistical characteristics (variance, skewness, and bias) of the monitored signals.

Bickford, Randall L.↗
NASA NTRS2018

Remote Sensing, Uncertainty Quantification, and a Theory of Data Systems; Workshop Report

The purpose of the workshop was to invite statisticians, applied mathematicians, computer scientists, data system architects, experts in remote sensing technology, and Climate and Earth System scientists to review, discuss, and plan research on issues related to large-scale, efficient analysis of distributed data using spatial statistical methods. Our motivation in organizing this event was to catalyze interchange among experts on the fast-emerging problem of analysis of distributed data. As part of SAMSI's 2017-2018 Program on Mathematical and Statistical Methods for Climate and the Earth System, a Working Group on Remote Sensing was established to address statistical and mathematical research problems in the analysis of remote sensing data. The Working Group has five subgroups: 1) Spatial Retrieval Methodology (the so-called \Spatial-X" subgroup); 2) Spatial Analysis for Hyperspectral Data (the so-called \Spatial-Y" subgroup); 3) Emulators for Complex Forward Models; 4) Optimization for Remote Sensing Retrievals; and 5) Theory of Data Systems (ToDS). The ToDS subgroup spent the first half of this academic year formulating a framework in which to consider the joint problem of a) optimizing statistical methods for environments where data are distributed and too large to move to a central location, and b) the design of data system infrastructures within which to implement those statistical methods. To x ideas, the Workshop focused on spatial statistical methods. To date there are many new spatial statistical methods designed with massive data sets in mind, in the literature. However, very few have been implemented for remote sensing data, and none have been implemented in operational settings like those used by NASA and NOAA. A major impediment to their use in these cases is that the data are not only massive, but are stored in different physical locations. These data must be brought together in some way in order to estimate spatial covariance functions, but moving data to a central location for analysis is tedious at best and impossible at worst. Some remote data reduction is almost certainly necessary, but how much? What are the consequences for inference? The fundamental issue underlying these questions is how to navigate the trade-space between costs and uncertainty in the estimates or inferences that are ultimately produced.

Braverman, Amy↗
NASA NTRS2019

Cloud Giovanni: Reining in Costs and Improving Performance with Analytical Data Stores Using Scalable Serverless Architecture

Giovanni is the Geospatial Interactive Online Visualization ANd aNalysis Infrastructure developed at NASA GES DISC which provides a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science data. It receives large number of user requests each day for a variety of analysis and visualization services, which leads to the big data challenge of serving gradually increasing large data volumes with diverse statistical algorithms. We hereby propose a multi-dimensional accumulation method which provides fast and cost-efficient cloud analysis for diverse services including both area averaging and time averaging. This method involves the weighted volume integration over multiple variable dimensions (time and space), and is implemented in AWS using Athena providing serverless and highly scalable data analysis. Compared to the standard method, this approach dramatically reduced the computational time by order of magnitude with a minimal AWS cost incurred. For example, for a benchmark of 10-year area averaging over the 1x1 degree daily variable, the computational time was reduced from minutes to seconds, and the Athena cost is only $5 for 100,000 requests.

Zhang, Hailiang↗
NASA NTRS1994

Statistic analysis of annual total ozone extremes for the period 1964-1988

Annual extremes of total column amount of ozone (in the period 1964-1988) from a network of 29 Dobson stations have been examined using the extreme value analysis. The extremes have been calculated as the highest deviation of daily mean total ozone from its long-term monthly mean, normalized by the monthly standard deviations. The extremes have been selected from the direct-Sun total ozone observations only. The extremes resulting from abrupt changes in ozone (day to day changes greater than 20 percent) have not been considered. The ordered extremes (maxima in ascending way, minima in descending way) have been fitted to one of three forms of the Fisher-Tippet extreme value distribution by the nonlinear least square method (Levenberg-Marguard method). We have found that the ordered extremes from a majority of Dobson stations lie close to Fisher-Tippet type III. The extreme value analysis of the composite annual extremes (combined from averages of the annual extremes selected at individual stations) has shown that the composite maxima are fitted by the Fisher-Tippet type III and the composite minima by the Fisher-Tippet type I. The difference between the Fisher-Tippet types of the composite extremes seems to be related to the ozone downward trend. Extreme value prognoses for the period 1964-2014 (derived from the data taken at: all analyzed stations, the North American, and the European stations) have revealed that the prognostic extremes are close to the largest annual extremes in the period 1964-1988 and there are only small regional differences in the prognoses.

Krzyscin, Janusz W.↗
NASA NTRS1988

Variance and bias confidence criteria for ERA modal parameter identification

For the ERA system identification algorithm, perturbation methods are used to develop expressions for variance and bias of the identified modal parameters. Based on the statistics of the measurement noise, the variance results serve as confidence criteria by indicating how likely the true parameters are to lie within any chosen interval about their identified values. This replaces the use of expensive and time-consuming Monte Carlo computer runs to obtain similar information. The bias estimates help guide the ERA user in his choice of which data points to use and how much data to use in order to obtain the best results, performing the trade-off between the bias and scatter. Also, when the uncertainty in the bias is sufficiently small, the bias information can be used to correct the ERA results. In addition, expressions for the variance and bias of the singular values serve as tools to help the ERA user decide the proper modal order.

Longman, Richard W.↗
NASA NTRS1994

Approaches of comparison for clear-sky radiative fluxes from general circulation models with Earth Radiation Budget Experiment data

In order to compare the clear-sky greenhouse effect and cloud-radiative forcing from general circulation models with Earth Radiation Budget Experiments (ERBE) data, it is necessary to calculate the general circulation model (GCM) clear-sky radiative fluxes in a way consistent with ERBE. This study discusses problems associated with the available methods for clear-sky radiative flux computations in GCMs and proposes a new approach, which uses a statistical relationship between the grid cloud cover and the availability of ERBE clear-sky measurement, established from ERBE pixel data, to sample the model radiative fluxes. Calculations with version 2 of the National Center for Atmospheric Research (NCAR) Community Climate Model using observed sea surface temperature (SST) show good agreement of clear-sky sampling from the proposed method with ERBE sampling. It is also shown that large improvements are achieved in the spatial variability of the model clear-sky radiative fluxes over ocean, with reference to ERBE, by using the new clear-sky sampling method.

Zhang, M. H.↗
NASA NTRS2015

Improving the Timeliness of Winter Wheat Production Forecast in the United States of America, Ukraine and China Using MODIS Data and NCAR Growing Degree Day Information

Wheat is themost important cereal crop traded on international markets and winter wheat constitutes approximately 80% of global wheat production. Thus, accurate and timely production forecasts are critical for making informed agricultural policies and investments, as well as increasing market efficiency and stability. Becker-Reshef et al. (2010) developed an empirical generalized model for forecasting winter wheat production. Their approach combined BRDF-corrected daily surface reflectance from Moderate resolution Imaging Spectroradiometer (MODIS) Climate Modeling Grid (CMG) with detailed official crop statistics and crop typemasks. It is based on the relationship between the Normalized Difference Vegetation Index (NDVI) at the peak of the growing season, percent wheat within the CMG pixel (area within the CMG pixel occupied by wheat), and the final yields. This method predicts the yield approximately one month to six weeks prior to harvest. In this study, we include Growing Degree Day (GDD) information extracted from NCEP/NCAR reanalysis data in order to improve the winter wheat production forecast by increasing the timeliness of the forecasts while conserving the accuracy of the original model. We apply this modified model to three major wheat-producing countries: the Unites States (US), Ukraine and China from 2001 to 2012. We show that a reliable forecast can be made between one month to a month and a half prior to the peak NDVI (meaning two months to two and a half months prior to harvest), while conserving an accuracy of 10% in the production forecast.

Production↗
NASA NTRS2019

Statistical optical link budget analysis

In this paper, we describe work on extending statistical analysis methods to optical communications links, with a primary focus on intensity modulated, direct detected photon-counting channel utilizing pulse-position-modulation (PPM). We performed analysis on the relationship between bit error rate (BER) requirement, statistical characteristics of the received signal power and noise power, and the coded performance curves. We presented link analysis results with preliminary uncertainty quantifications of signal power and noise power. We used the Consultative Committee for Space Data Systems (CCSDS) Serially Concatenated convolutionally coded Pulse Position Modulation (SCPPM) prototype software [1] to obtain coded performance curves under different operating conditions with varying signal power, background noise power, code rates,and PPM modulation orders. Comparison with traditional, deterministic analysis shows that extra margin needs to be reserved to compensate for the performance losses caused by uncertainties of the link parameters.

Cheung, Kar-Ming↗
NASA NTRS1987

Systematic properties of CO emission from galaxies. I - Luminosity function

A sensitive survey of normal galaxies covering a wide range of luminosities and morphological types is combined with galaxy observations in the literature to provide a sample for statistical study. The global CO emission of these galaxies is extrapolated by modeling the galaxies with an exponential radial profile. The maximum-likelihood distribution functions of CO luminosity and CO/H I flux ratio are similar in behavior. Both have long tails of bright galaxies. However, the typical galaxy has a CO luminosity of about 10 to the 6th Jy km/s Mpc-squared or less and a CO/H I ratio of the order of 10 or less. Averages of the distributions of CO luminosity and CO/H I flux ratio are higher for galaxies of Hubble type Sb-Sbc than for groups of earlier or later types. Quantitative estimates of the possible error sources in the conversion of CO luminosity to molecular mass indicates that the peaking of CO emission at intermediate types is a fairly confident result.

Verter, Frances↗
NASA NTRS2000

Correlative Aspects of the Solar Electron Neutrino Flux and Solar Activity

Between 1970 and 1994, the Homestake Solar Neutrino Detector obtained 108 observations of the solar electron neutrino flux (less than 0.814 MeV). The "best fit" values derived from these observations suggest an average daily production rate of about 0.485 Ar-37 atom per day, a rate equivalent to about 2.6 SNU (solar neutrino units) or about a factor of 3 below the expected rate from the standard solar model. In order to explain, at least, a portion of this discrepancy, some researchers have speculated that the flux of solar neutrinos is variable, possibly being correlated with various markers of the solar cycle (e.g., sunspot number, the Ap index, etc.). In this paper, using the larger "standard data set," the issue of correlative behavior between solar electron neutrino flux and solar activity is re-examined. The results presented here clearly indicate that no statistically significant association exists between any of the usual markers of solar activity and the solar electron neutrino flux.

Wilson, Robert M.↗
NASA NTRS2002

Characterization of the Temperature Capabilities of Advanced Disk Alloy ME3

The successful development of an advanced powder metallurgy disk alloy, ME3, was initiated in the NASA High Speed Research/Enabling Propulsion Materials (HSR/EPM) Compressor/Turbine Disk program in cooperation with General Electric Engine Company and Pratt & Whitney Aircraft Engines. This alloy was designed using statistical screening and optimization of composition and processing variables to have extended durability at 1200 F in large disks. Disks of this alloy were produced at the conclusion of the program using a realistic scaled-up disk shape and processing to enable demonstration of these properties. The objective of the Ultra-Efficient Engine Technologies disk program was to assess the mechanical properties of these ME3 disks as functions of temperature in order to estimate the maximum temperature capabilities of this advanced alloy. These disks were sectioned, machined into specimens, and extensively tested. Additional sub-scale disks and blanks were processed and selectively tested to explore the effects of several processing variations on mechanical properties. Results indicate the baseline ME3 alloy and process can produce 1300 to 1350 F temperature capabilities, dependent on detailed disk and engine design property requirements.

Gabb, Timothy P.↗
NASA NTRS1996

Changes in aerobic power of women, ages 20-64 yr

This study quantified and compared the cross-sectional and longitudinal influence of age, self-report physical activity (SR-PA), and body composition (%fat) on the decline of maximal aerobic power (VO2peak) of women. The cross-sectional sample consisted of 409 healthy women, ages 20-64 yr. The 43 women of the longitudinal sample were from the same population and examined twice, the mean time between tests was 3.7 (+/-2.2) yr. Peak oxygen uptake was determined by indirect calorimetry during a maximal treadmill test. The zero-order correlation of -0.742 between VO2peak and %fat was significantly (P < 0.05) higher then the SR-PA (r = 0.626) and age correlations (r = -0.633). Linear regression defined the cross-sectional age-related decline in VO2peak at 0.537 ml.kg-1.min-1.yr-1. Multiple regression analysis (R = 0.851) showed that adding %fat and SR-PA and their interaction to the regression model reduced the age regression weight of -0.537, to -0.265 ml.kg-1.min-1.yr-1. Statistically controlling for time differences between tests, general linear models analysis showed that longitudinal changes in aerobic power were due to independent changes in %fat and SR-PA, confirming the cross-sectional results. These findings are consistent with men's data from the same lab showing that about 50% of the cross-sectional age-related decline in VO2peak was due to %fat and SR-PA.

Aging/physiology↗
NASA NTRS2007

Electrification in Hurricanes over the Tropical Americas: Implication for Stratospheric Water Vapor

This study explores the relation between lightning activity and water vapor in the Tropical Tropopause Layer (TTL) over hurricane systems in the Tropical Americas. The hypothesis herein is that hurricanes that exhibit enhanced lightning activity are associated with stronger updrafts that can transport more moisture directly into the TTL (and subsequently into the tropical stratosphere) or even directly into the tropical stratosphere over this region. The TTL over the Tropical Americas, which includes the Caribbean and Gulf of Mexico, is of particular interest, because summertime cold point tropopause is the lowest in height and thus the warmest in temperature over the tropics. The latter condition implies higher saturation values and thus potential for more water vapor to enter the stratosphere. Climate forecast is very sensitive to stratospheric water vapor abundance, because of the key role that water vapor plays in regulating the chemical and radiative properties of the stratosphere. Given the potential for increases in hurricane intensity and frequency under predicted warmer conditions, it becomes essential to understand the effect of hurricanes on stratospheric water vapor. In this study, we use a combination of ground and space-borne observations as well as trajectory calculations. The observations include: cloud-to-ground (CG) lightning data from the U.S. National Lightning Detection Network (NLDN), geostationary infrared observations from the National Climatic Data Center Hurricane Satellite (HURSAT) data set, cloud properties from Aqua-MODIS, and water vapor from Aura-MLS. We analyze hurricanes from the 2005 season when Aura-MLS data are available, namely: Dennis, Emily, Katrina, Rita, and Wilma. Our analysis consists of examining CG lightning, cloud-top properties, and TTL water vapor (i.e., 100 and 147 mb) over the hurricane while it remains over water in the Tropical Americas region. We investigate daily as well as diurnal statistical properties. The hurricanes analyzed in this study showed that lightning activity is negatively correlated with minimum infrared brightness temperature and positively correlated with 100-mb water vapor. An examination of the maxima in water vapor observed over the hurricane not only shows larger magnitudes, but also larger differences between water vapor averages and water vapor maxima over the hurricane as lightning activity increases. Trajectory calculations are performed using the Flextra model in order to investigate the fate of the moister air masses found in the TTL.

Pittman, Jasna V.↗
NASA NTRS2010

Acoustic Noise Prediction of the Amine Swingbed ISS ExPRESS Rack Payload

Acoustics plays a vital role in maintaining the health, safety, and comfort of crew members aboard the International Space Station (ISS). In order to maintain this livable and workable environment, acoustic requirements have been established to ensure that ISS hardware and payload developers account for the acoustic emissions of their equipment and develop acoustic mitigations as necessary. These requirements are verified by an acoustic emissions test of the integrated hardware. The Amine Swingbed ExPRESS (Expedite the PRocessing of ExperimentS to Space) rack payload creates a unique challenge to the developers in that the payload hardware is transported to the ISS in phases, making an acoustic emissions test on the integrated flight hardware impossible. In addition, the payload incorporates a high back pressure fan and a diaphragm vacuum pump, which are recognized as significant and complex noise sources. In order to accurately predict the acoustic emissions of the integrated payload, the individual acoustic noise sources and paths are first characterized. These characterizations are conducted though a series of acoustic emissions tests on the individual payload components. Secondly, the individual acoustic noise sources and paths are incorporated into a virtual model of the integrated hardware. The virtual model is constructed with the use of hybrid method utilizing the Finite Element Acoustic (FEA) and Statistical Energy Analysis (SEA) techniques, which predict the overall acoustic emissions. Finally, the acoustic model is validated though an acoustic characterization test performed on an acoustically similar mock-up of the flight unit. The results of the validated acoustic model are then used to assess the acoustic emissions of the flight unit and define further acoustic mitigation efforts.

Welsh, David↗
NASA NTRS2012

An Automated Algorithm to Screen Massive Training Samples for a Global Impervious Surface Classification

An algorithm is developed to automatically screen the outliers from massive training samples for Global Land Survey - Imperviousness Mapping Project (GLS-IMP). GLS-IMP is to produce a global 30 m spatial resolution impervious cover data set for years 2000 and 2010 based on the Landsat Global Land Survey (GLS) data set. This unprecedented high resolution impervious cover data set is not only significant to the urbanization studies but also desired by the global carbon, hydrology, and energy balance researches. A supervised classification method, regression tree, is applied in this project. A set of accurate training samples is the key to the supervised classifications. Here we developed the global scale training samples from 1 m or so resolution fine resolution satellite data (Quickbird and Worldview2), and then aggregate the fine resolution impervious cover map to 30 m resolution. In order to improve the classification accuracy, the training samples should be screened before used to train the regression tree. It is impossible to manually screen 30 m resolution training samples collected globally. For example, in Europe only, there are 174 training sites. The size of the sites ranges from 4.5 km by 4.5 km to 8.1 km by 3.6 km. The amount training samples are over six millions. Therefore, we develop this automated statistic based algorithm to screen the training samples in two levels: site and scene level. At the site level, all the training samples are divided to 10 groups according to the percentage of the impervious surface within a sample pixel. The samples following in each 10% forms one group. For each group, both univariate and multivariate outliers are detected and removed. Then the screen process escalates to the scene level. A similar screen process but with a looser threshold is applied on the scene level considering the possible variance due to the site difference. We do not perform the screen process across the scenes because the scenes might vary due to the phenology, solar-view geometry, and atmospheric condition etc. factors but not actual landcover difference. Finally, we will compare the classification results from screened and unscreened training samples to assess the improvement achieved by cleaning up the training samples. Keywords:

Tan, Bin↗
NASA NTRS2015

Implicit Large-Eddy Simulations of Zero-Pressure Gradient, Turbulent Boundary Layer

A set of direct simulations of zero-pressure gradient, turbulent boundary layer flows are conducted using various span widths (62-630 wall units), to document their influence on the generated turbulence. The FDL3DI code that solves compressible Navier-Stokes equations using high-order compact-difference scheme and filter, with the standard recycling/rescaling method of turbulence generation, is used. Results are analyzed at two different Re values (500 and 1,400), and compared with spectral DNS data. They show that a minimum span width is required for the mere initiation of numerical turbulence. Narrower domains ((is) less than 100 w.u.) result in relaminarization. Wider spans ((is) greater than 600 w.u.) are required for the turbulent statistics to match reference DNS. The upper-wall boundary condition for this setup spawns marginal deviations in the mean velocity and Reynolds stress profiles, particularly in the buffer region.

Turblent boundary layer↗