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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 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

On the estimation of statistical uncertainties on powder diffraction and small-angle scattering data from two-dimensional X-ray detectors

Optimal methods are explored for obtaining one-dimensional powder pattern intensities from two-dimensional planar detectors with good estimates of their standard deviations. Methods are described to estimate uncertainties when the same image is measured in multiple frames as well as from a single frame. The importance of considering the correlation of diffraction points during the integration and the resampling process of data analysis is shown. It is found that correlations between adjacent pixels in the image can lead to seriously overestimated uncertainties if such correlations are neglected in the integration process. Off-diagonal entries in the variance–covariance (VC) matrix are problematic as virtually all data processing and modeling programs cannot handle the full VC matrix. It is shown that the off-diagonal terms come mainly from the pixel-splitting algorithm used as the default integration algorithm in many popular two-dimensional integration programs, as well as from rebinning and resampling steps later in the processing. When the full VC matrix can be propagated during the data reduction, it is possible to get accurate refined parameters and their uncertainties at the cost of increasing computational complexity. However, as this is not normally possible, the best approximate methods for data processing in order to estimate uncertainties on refined parameters with the greatest accuracy from just the diagonal variance terms in the VC matrix is explored.

Yang, X.↗
DOE OSTI2024

Improving the estimate of higher-order moments from lidar observations near the top of the convective boundary layer

Abstract. Ground-based lidar data have proven extremely useful for profiling the convective boundary layer (CBL). Many groups have derived higher-order moments (e.g., variance, skewness, fluxes) from high-temporal-resolution lidar data using an autocovariance approach. However, these analyses are highly uncertain near the CBL top when the depth of the CBL (zi) is changing during the analysis period. This is because the autocovariance approach is usually applied to constant height levels and the character of the eddies is changing on either side of the changing CBL top. Here, a new approach is presented wherein the autocovariance analysis is performed on a normalized height grid, with a temporally smoothed zi. Output from a large eddy simulation model demonstrates that deriving higher-order moments from time series on a normalized height grid has better agreement with the slab-averaged quantities than the moments derived from the original height grid.

Rosenberger, Tessa E. (ORCID:0000000333205873)↗
NASA NTRS1973

Validity test for linear error analysis

To determine whether estimation process simulated by linear error analysis will converge, criterion has been developed based on extension of classical observability. Particular application of technique is with groups of batched navigation data where statistics of estimation errors are derived with classical minimum-variance methods.

Diamant, L. S.↗
NASA NTRS1986

Department of Geology/NASA-GSFC geobotanical investigation

Geobotanical mapping in the southern Appalachians and soil metal associated changes in vegatation spectral responses in the reflective and emissive portions of the electromagnetic spectrum (EMS) is studied. It is determined whether deciduous forest vegetation reflection and emission characteristics show detectable changes that can be related to residual soil characteristics. Analyses of such related characteristics enhances the ability to discriminate underlying lithologies as well as variances within lithologies associated with natural heavy metal occurences. An understanding is developed of the factors which contribute to the differing spectral signatures of various lithology/soil types. A combination of field data and remote spectral analysis is studied.

Source record↗
NASA NTRS2004

Managing Risk to Ensure a Successful Cassini/Huygens Saturn Orbit Insertion (SOI)

I. Design: a) S/C designed to be largely single fault tolerant; b) Operate in flight demonstrated envelope, with margin; and c) Strict compliance with requirements & flight rules. II. Test: a) Baseline, fault & stress testing using flight system testbeds (H/W & S/W); b) In-flight checkout & demos to remove first time events. III. Failure Analysis: a) Critical event driven fault tree analysis; b) Risk mitigation & development of contingencies. IV) Residual Risks: a) Accepted pre-launch waivers to Single Point Failures; b) Unavoidable risks (e.g. natural disaster). V) Mission Assurance: a) Strict process for characterization of variances (ISAs, PFRs & Waivers; b) Full time Mission Assurance Manager reports to Program Manager: 1) Independent assessment of compliance with institutional standards; 2) Oversight & risk assessment of ISAs, PFRs & Waivers etc.; and 3) Risk Management Process facilitator.

risk managment↗
NASA NTRS2013

Diurnal Variation in Gravity Wave Activity at Low and Middle Latitudes

We employ a modified composite day extension of the Hocking (2005) analysis method to study gravity wave (GW) activity in the mesosphere and lower thermosphere using 4 meteor radars spanning latitudes from 7deg S to 53.6deg S. Diurnal and semidiurnal modulations were observed in GW variances over all sites. Semidiurnal modulation with downward phase propagation was observed at lower latitudes mainly near the equinoxes. Diurnal modulations occur mainly near solstice and, except for the zonal component at Cariri (7deg S), do not exhibit downward phase propagation. At a higher latitude (SAAMER, 53.6deg S) these modulations are only observed in the meridional component where we can observe diurnal variation from March to May, and semidiurnal, during January, February, October (above 88 km) and November. Some of these modulations with downward phase progression correlate well with wind shear. When the wind shear is well correlated with the maximum of the variances the diurnal tide has its largest amplitudes, i.e., near equinox. Correlations exhibiting variations with tidal phases suggest significant GW-tidal interactions that have different characters depending on the tidal components and possible mean wind shears. Modulations that do not exhibit phase variations could be indicative of diurnal variations in GW sources.

waves↗
DOE OSTI2023

BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets

BigNeuron is an open community bench-testing platform with the goal of setting open standards for accurate and fast automatic neuron tracing. We gathered a diverse set of image volumes across several species that is representative of the data obtained in many neuroscience laboratories interested in neuron tracing. Here, we report generated gold standard manual annotations for a subset of the available imaging datasets and quantified tracing quality for 35 automatic tracing algorithms. The goal of generating such a hand-curated diverse dataset is to advance the development of tracing algorithms and enable generalizable benchmarking. Together with image quality features, we pooled the data in an interactive web application that enables users and developers to perform principal component analysis, t-distributed stochastic neighbor embedding, correlation and clustering, visualization of imaging and tracing data, and benchmarking of automatic tracing algorithms in user-defined data subsets. The image quality metrics explain most of the variance in the data, followed by neuromorphological features related to neuron size. Furthermore, we observed that diverse algorithms can provide complementary information to obtain accurate results and developed a method to iteratively combine methods and generate consensus reconstructions. The consensus trees obtained provide estimates of the neuron structure ground truth that typically outperform single algorithms in noisy datasets. However, specific algorithms may outperform the consensus tree strategy in specific imaging conditions. Finally, to aid users in predicting the most accurate automatic tracing results without manual annotations for comparison, we used support vector machine regression to predict reconstruction quality given an image volume and a set of automatic tracings.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Assessing the use of reflectance spectroscopy in determining CsCl stress in the model species Arabidopsis thaliana

Here, reflectance spectroscopy is a rapid and non-destructive analytical technique that may be used for assessing plant stress, and has potential applications for use in remediation. Changes in reflectance such as that due to metal stress may occur before damage is visible, and existing studies have shown that metal stress does cause changes in plant reflectance. To further investigate the potential use of reflectance spectroscopy as a method for assessing metal stress in plants, an exploratory study was conducted in which Arabidopsis thaliana plants were treated twice weekly in a laboratory setting with varying levels (0, 0.5, or 5 mM (millimolar)) of caesium chloride (CsCl) solution, and reflectance spectra were collected every week for three weeks using an Analytical Spectral Devices FieldSpec Pro spectroradiometer with both a contact probe (CP) and a field of view (FOV) probe at 36.8 and 66.7 cm, respectively, above the plant. Plants were harvested each week after spectra collection for determination of relative water content and chlorophyll content. A visual assessment of the plants was also conducted using point observations on a uniform grid of 81 points. A mixed-effects model analysis was conducted for each vegetation index (VI) considered to determine the effects of length of treatment, treatment level, view with which spectra were acquired, and the interactions of these terms. Two-way analyses of variance (ANOVAs) were performed on the aforementioned endpoints (e.g. chlorophyll content) to determine the significance of the effects of treatment level and length of treatment. Multiple linear regression (MLR) was used to develop a predictive model for each endpoint, considering VI acquired at each view (CP, high FOV, and low FOV). Of the 14 VI considered, 8 were included in the MLR models. Contact probe readings and FOV readings differed significantly, but FOV measurements were generally consistent at each height.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1981

Ice/frost detection using millimeter wave radiometry

A series of ice detection tests was performed on the shuttle external tank (ET) and on ET target samples using a 35/95 GHz instrumentation radiometer. Ice was formed using liquid nitrogen and water spray inside a test enclosure containing ET spray on foam insulation samples. During cryogenic fueling operations prior to the shuttle orbiter engine firing tests, ice was formed with freon and water over a one meter square section of the ET LOX tank. Data analysis was performed on the ice signatures, collected by the radiometer, using Georgia Tech computing facilities. Data analysis technique developed include: ice signature images of scanned ET target; pixel temperature contour plots; time correlation of target data with ice present versus no ice formation; and ice signature radiometric temperature statistical data, i.e., mean, variance, and standard deviation.

Gagliano, J. A.↗
NASA NTRS1993

HL-20 operations and support requirements for the Personnel Launch System mission

The processing, mission planning, and support requirements were defined for the HL-20 lifting-body configuration that can serve as a Personnel Launch System. These requirements were based on the assumption of an operating environment that incorporates aircraft and airline support methods and techniques that are applicable to operations. The study covered the complete turnaround process for the HL-20, including landing through launch, and mission operations, but did not address the support requirements of the launch vehicle except for the integrated activities. Support is defined in terms of manpower, staffing levels, facilities, ground support equipment, maintenance/sparing requirements, and turnaround processing time. Support results were drawn from two contracted studies, plus an in-house analysis used to define the maintenance manpower. The results of the contracted studies were used as the basis for a stochastic simulation of the support environment to determine the sufficiency of support and the effect of variance on vehicle processing. Results indicate the levels of support defined for the HL-20 through this process to be sufficient to achieve the desired flight rate of eight flights per year.

Morris, W. D.↗
NASA NTRS2017

Exploratory Analysis of Carbon Dioxide Levels, Ultrasound and Optical Coherence Tomography Measures of the Eye During ISS Missions

Enhanced screening for the Visual Impairment/Intracranial Pressure (VIIP) syndrome has been implemented to better characterize the ocular and vision changes observed in some long-duration crewmembers. This includes implementation of in-flight ultrasound in 2010 and optical coherence tomography (OCT) in 2013. Potential risk factors for VIIP include cardiovascular health, diet, anatomical and genetic factors, and environmental conditions. Carbon dioxide (CO2), a potent vasodilator, is chronically elevated on the International Space Station (ISS) relative to ambient levels on Earth, and is a plausible risk factor for VIIP. In an effort to understand the possible associations between CO2 and VIIP, this study explores the relationship of ambient CO2 levels on ISS compared to inflight ultrasound and OCT measures of the eye obtained from ISS crewmembers. CO2 measurements were aggregated from Operational Data Reduction Complex and Node 3 major constituent analyzers (MCAs) on ISS or from sensors located in the European Columbus module, as available. CO2 levels in the periods between each ultrasound and OCT session are summarized using timeseries metrics, including time-weighted means and variances. Partial least squares regression analyses are used to quantify the complex relationship between specific ultrasound and OCT measures and the CO2 metrics simulataneously. These analyses will enhance our understanding of the possible associations between CO2 levels and structural changes to the eye which will in turn inform future analysis of inflight VIIP data.

Schaefer, C.↗
DOE OSTI2022

Machine Learning of All Mycobacterium tuberculosis H37Rv RNA-seq Data Reveals a Structured Interplay between Metabolism, Stress Response, and Infection

Mycobacterium tuberculosis is one of the most consequential human bacterial pathogens, posing a serious challenge to 21st century medicine. A key feature of its pathogenicity is its ability to adapt its transcriptional response to environmental stresses through its transcriptional regulatory network (TRN). While many studies have sought to characterize specific portions of the M. tuberculosis TRN, and some studies have performed system-level analysis, few have been able to provide a network-based model of the TRN that also provides the relative shifts in transcriptional regulator activity triggered by changing environments. Here, we compiled a compendium of nearly 650 publicly available, high quality M. tuberculosis RNA-sequencing data sets and applied an unsupervised machine learning method to obtain a quantitative, top-down TRN. It consists of 80 independently modulated gene sets known as “iModulons,” 41 of which correspond to known regulons. These iModulons explain 61% of the variance in the organism’s transcriptional response. We show that iModulons (i) reveal the function of poorly characterized regulons, (ii) describe the transcriptional shifts that occur during environmental changes such as shifting carbon sources, oxidative stress, and infection events, and (iii) identify intrinsic clusters of regulons that link several important metabolic systems, including lipid, cholesterol, and sulfur metabolism. This transcriptome-wide analysis of the M. tuberculosis TRN informs future research on effective ways to study and manipulate its transcriptional regulation and presents a knowledge-enhanced database of all published high-quality RNA-seq data for this organism to date.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Driving mode analysis—How uncertain functional inputs propagate to an output

Abstract Driving mode analysis elucidates how correlated features of uncertain functional inputs jointly propagate to produce uncertainty in the output of a computation. Uncertain input functions are decomposed into three terms: the mean functions, a zero‐mean driving mode, and zero‐mean residual. The random driving mode varies along a single direction, having fixed functional shape and random scale. It is uncorrelated with the residual, and under linear error propagation, it produces an output variance equal to that of the full input uncertainty. Finally, the driving mode best represents how input uncertainties propagate to the output because it minimizes expected squared Mahalanobis distance amongst competitors. These characteristics recommend interpretation of the driving mode as the single‐degree‐of‐freedom component of input uncertainty that drives output uncertainty. We derive the functional driving mode, show its superiority to other seemingly sensible definitions, and demonstrate the utility of driving mode analysis in an application. The application is the simulation of neutron transport in criticality experiments. The uncertain input functions are nuclear data that describe how Pu reacts to bombardment by neutrons. Visualization of the driving mode helps scientists understand what aspects of correlated functional uncertainty have effects that either reinforce or cancel one another in propagating to the output of the simulation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Planck 2015 results: XX. Constraints on inflation

In this paper, we present the implications for cosmic inflation of the Planck measurements of the cosmic microwave background (CMB) anisotropies in both temperature and polarization based on the full Planck survey, which includes more than twice the integration time of the nominal survey used for the 2013 release papers. The Planck full mission temperature data and a first release of polarization data on large angular scales measure the spectral index of curvature perturbations to be n s = 0.968 ± 0.006 and tightly constrain its scale dependence to dn s / dlnk = -0.003 ± 0.007 when combined with the Planck lensing likelihood. When the Planck high-ℓ polarization data are included, the results are consistent and uncertainties are further reduced. The upper bound on the tensor-to-scalar ratio is r 0.002 < 0.11 (95% CL). This upper limit is consistent with the B-mode polarization constraint r< 0.12 (95% CL) obtained from a joint analysis of the BICEP2/Keck Array and Planck data. These results imply that V(φ) ∝ φ 2 and natural inflation are now disfavoured compared to models predicting a smaller tensor-to-scalar ratio, such as R 2 inflation. We search for several physically motivated deviations from a simple power-law spectrum of curvature perturbations, including those motivated by a reconstruction of the inflaton potential not relying on the slow-roll approximation. We find that such models are not preferred, either according to a Bayesian model comparison or according to a frequentist simulation-based analysis. Three independent methods reconstructing the primordial power spectrum consistently recover a featureless and smooth P R (k)over the range of scales 0.008 Mpc -1 ≲ k ≲ 0.1 Mpc -1 . At large scales, each method finds deviations from a power law, connected to a deficit at multipoles ℓ ≈ 20-40 in the temperature power spectrum, but at an uncompelling statistical significance owing to the large cosmic variance present at these multipoles. By combining power spectrum and non-Gaussianity bounds, we constrain models with generalized Lagrangians, including Galileon models and axion monodromy models. The Planck data are consistent with adiabatic primordial perturbations, and the estimated values for the parameters of the base Λ cold dark matter (ΛCDM) model are not significantly altered when more general initial conditions are admitted. In correlated mixed adiabatic and isocurvature models, the 95% CL upper bound for the non-adiabatic contribution to the observed CMB temperature variance is | α non - adi | < 1.9%, 4.0%, and 2.9% for CDM, neutrino density, and neutrino velocity isocurvature modes, respectively. We have tested inflationary models producing an anisotropic modulation of the primordial curvature power spectrum finding that the dipolar modulation in the CMB temperature field induced by a CDM isocurvature perturbation is not preferred at a statistically significant level. We also establish tight constraints on a possible quadrupolar modulation of the curvature perturbation. Lastly, these results are consistent with the Planck 2013 analysis based on the nominal mission data and further constrain slow-roll single-field inflationary models, as expected from the increased precision of Planck data using the full set of observations.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1995

A new model for Mars atmospheric dust based upon analysis of ultraviolet through infrared observations from Mariner 9, Viking, and Phobos

We propose key modifications to the Toon et al. (1977) model of the particle size distribution and composition of Mars atmospheric dust, based on a variety of spacecraft and wavelength observations of the dust. A much broader (r(sub eff) variance approximately 0.8 micrometers), smaller particle size (r(sub mode) approximately 0.02 micrometers) distribution coupled with a 'palagonite-like' composition is argued to fit the complete ultraviolet-to-30-micrometer absorption properties of the dust better than the montmorillonite-basalt, r(sub eff) variance = 0.4 micrometers, r(sub mode) = 0.40 dust model of Toon et al. Mariner 9 (infrared interferometer spectrometer) IRIS spectra of high atmospheric dust opacities during the 1971-1972 Mars global dust storm are analyzed in terms of the Toon et al. dust model, and a Hawaiian palagonite sample (Rousch et al., 1991) with two different size distribution models incorporating smaller dust particle sizes. Viking Infrared Thermal Mapper (IRTM) emmission-phase-function (EPF) observations at 9 micrometers are analyzed to retrieve 9-micrometer dust opacities coincident with solar band dust opacities obtained from the same EPF sequences (Clancy and Lee, 1991). These EPF dust opacities provide an independent measurement of the visible/9-micrometer extinction opacity ratio (greater than or = 2) for Mars atmospheric dust, which is consistent with a previous measurement by Martin (1986). Model values for the visible/9-micrometer opacity ratio and the ultraviolet and visible single-scattering albedos are calculated for the palagonite model with the smaller particle size distributions compared to the same properties for the Toon et al. model of dust. The montmorillonite model of the dust is found to fit the detailed shape of the dust 9-micrometer absorption well. However, it predicts structured, deep aborptions at 20 micrometers which are not observed and requires a separate ultraviolet-visible absorbing component to match the observed behavior of the dust in this wavelength region. The modeled palagonite does not match the 8-to 9-micrometer absorption presented by the dust in the IRIS spectra, probably due to its low SiO2 content (31%). However, it does provide consistent levels of ultraviolet/visible absorption, 9-to 12-micrometer absorption, and a lack of structured absorption at 20 micrometers. The ratios of dust extinction opacities at visible, 9 micrometers, and 30 micrometers are strongly affected by the dust particle size distribution. The Toon et al. dust size distribution (r(sub mode) = 0.40,r(sub eff) variance = 0.4 micrometers, r(sub cwmu) = 2.7 micrometers) predicts the correct ratio of the 9- to 30-micrometer opacity, but underpredicts the visible/9-micrometer opacity ratio considerably (1 versus greater than or = 2). A similar particle distribution width with smaller particle sizes (r(sub mode) = 0.17, r(sub eff) variance = 0.4 micrometers, r(sub cwmu) = 1.2 micrometers) will fit the observed visible/9-micrometer opacity ratio, but overpredicts the observed 9-micrometer/30-micrometer opacity ratio. A smaller and much broader particle size distribution (r(sub mode) = 0.002, r(sub eff) variance = 0.8 micrometers, r(sub cwmu) = 1.8 micrometers) can fit both dust opacity ratios. Overall, the nanocrystalline structure of palagonite coupled with a smaller, broader distribution of dust particle sizes provides a more consistent fit than the Toon et al. model of the dust to the IRIS spectra, the observed visible/9-micrometer dust opacity ratio, the Phobos occulation measurements of the dust particle sizes (Chassefiere et al., 1992), and the weakness of surface near IR absorptions expected for clay minerals (Clark, 1992; Bell and Crisp, 1993).

Clancy, R. T.↗
NASA NTRS1995

A new model for Mars atmospheric dust based upon analysis of ultraviolet through infrared observations from Mariner 9, Viking, and Phobos

We propose key modifications to the Toon et al. (1977) model of the particle size distribution and composition of Mars atmospheric dust, based on a variety of spacecraft and wavelength observations of the dust. A much broader (r(sub eff)variance-0.8 micron), smaller particle size (r(sub mode)-0.02 microns) distribution coupled with a "palagonite-like" composition is argued to fit the complete ultraviolet-to-30-micron absorption properties of the dust better than the montmorillonite-basalt r(sub eff)variance= 0.4 micron, r(sub mode)= 0.40 micron dust model of Toon et al. Mariner 9 (infrared interferometer spectrometer) IRIS spectra of high atmospheric dust opacities during the 1971 - 1972 Mars global dust storm are analyzed in terms of the Toon et al. dust model, and a Hawaiian palagonite sample with two different size distribution models incorporating smaller dust particle sizes. Viking Infrared Thermal Mapper (IRTM) emission-phase-function (EPF) observations at 9 microns are analyzed to retrieve 9-micron dust opacities coincident with solar band dust opacities obtained from the same EPF sequences. These EPF dust opacities provide an independent measurement of the visible/9-microns extinction opacity ratio (> or equal to 2) for Mars atmospheric dust, which is consistent with a previous measurement by Martin (1986). Model values for the visible/9-microns opacity ratio and the ultraviolet and visible single-scattering albedos are calculated for the palagonite model with the smaller particle size distributions and compared to the same properties for the Toon et al. model of dust. The montmorillonite model of the dust is found to fit the detailed shape of the dust 9-micron absorption well. However, it predicts structured, deep absorptions at 20 microns which are not observed and requires a separate ultraviolet-visible absorbing component to match the observed behavior of the dust in this wavelength region. The modeled palagonite does not match the 8- to 9-micron absorption presented by the dust in the IRIS spectra, probably due to its low SiO2 content (31%). However, it does provide consistent levels of ultraviolet/visible absorption, 9- to 12-micron absorption, and a lack of structured absorption at 20 microns. The ratios of dust extinction opacities at visible, 9 microns, and 30 microns are strongly affected by the dust particle size distribution. The Toon et al. dust size distribution (r(sub mode)= 0.40, r(sub eff)variance= 0.4 microns, r(sub cw mu)= 2.7 microns) predicts the correct ratio of the 9- to 30-micron opacity, but underpredicts the visible/9-micron opacity ratio considerably (1 versus > or equal to 2). A similar particle distribution width with smaller particle sizes (r(sub mode)= 0.17, r(sub eff)variance= 0.4 microns, r(sub cw mu)=1.2 microns) will fit the observed visible/9-micron opacity ratio, but overpredicts the observed 9-micron/30-micron opacity ratio. A smaller and much broader particle size distribution (r(sub mode)= 0.02, r(sub eff)variance= 0.8 microns, r(sub cw mu)= 1.8 microns) can fit both dust opacity ratios. Overall, the nanocrystalline structure of palagonite coupled with a smaller, broader distribution of dust particle sizes provides a more consistent fit than the Toon et al. model of the dust to the IRIS spectra, the observed visible/9-micron dust opacity ratio, the Phobos occultation measurements of dust particle sizes, and the weakness of surface near IR absorptions expected for clay minerals.

Clancy, R. T.↗
DOE OSTI2013

In-Situ Statistical Analysis of Autotune Simulation Data using Graphical Processing Units

Developing accurate building energy simulation models to assist energy efficiency at speed and scale is one of the research goals of the Whole-Building and Community Integration group, which is a part of Building Technologies Research and Integration Center (BTRIC) at Oak Ridge National Laboratory (ORNL). The aim of the Autotune project is to speed up the automated calibration of building energy models to match measured utility or sensor data. The workflow of this project takes input parameters and runs EnergyPlus simulations on Oak Ridge Leadership Computing Facility’s (OLCF) computing resources such as Titan, the world’s second fastest supercomputer. Multiple simulations run in parallel on nodes having 16 processors each and a Graphics Processing Unit (GPU). Each node produces a 5.7 GB output file comprising 256 files from 64 simulations. Four types of output data covering monthly, daily, hourly, and 15- minute time steps for each annual simulation is produced. A total of 270TB+ of data has been produced. In this project, the simulation data is statistically analyzed in-situ using GPUs while annual simulations are being computed on the traditional processors. Titan, with its recent addition of 18,688 Compute Unified Device Architecture (CUDA) capable NVIDIA GPUs, has greatly extended its capability for massively parallel data processing. CUDA is used along with C/MPI to calculate statistical metrics such as sum, mean, variance, and standard deviation leveraging GPU acceleration. The workflow developed in this project produces statistical summaries of the data which reduces by multiple orders of magnitude the time and amount of data that needs to be stored. These statistical capabilities are anticipated to be useful for sensitivity analysis of EnergyPlus simulations

accelerators↗
NASA NTRS2003

Low Earth Orbit Plasma Variability Model

The empirical International Reference Ionosphere is a widely used model for estimating low Earth orbit plasma characteristics for use in spacecraft design and mission analysis. The climatological model provides mean values of plasma density, temperature, composition, and other ionospheric parameters that can be used to estimate the average magnitude of spacecraft charging, current collection for electrodynamic tethers, and other effects on spacecraft design. Mean IRI parameters are not adequate to answer questions such as what is the maximum or minimum value of the spacecraft potential, does the maximum spacecraft potential exceed a program requirement, will an electrodynamic tether provide adequate drag to deorbit a satellite at end of life, and will the tether provide sufficient thrust to reboost a spacecraft at any time in the solar cycle. These questions require estimates of the variability of the ionospheric environment about the mean values. This presentation describes the status of work at MSFC to develop an empirical ionospheric variability model that can be used in conjunction with the climatological IRI model to provide both mean ionospheric parameters and variations of the environment about the mean. Our technique will use an extensive database of satellite and radar observations of the electron density and temperature to derive variances of the data about the model values. The variances will then be incorporated into Fortran wrapper software that calls the IRI-2001 model and provides statistical estimates of the deviation of the environment about the mean IRI values. We will provide an update on the state of the database development and provide examples of analysis and modeling efforts completed specifically for an International Space Station application.

Minow, Joseph I.↗