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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 19 records

Program of solar wind data analysis utilizing data from Pioneer 6, Mariner 5 and explorer 35

A combined data analysis and theoretical program aimed at interpreting and utilizing solar wind data obtained from Pioneer 6, Mariner 5, and Explorer 35 has been completed. A theoretical model of the radial dependence of large scale solar wind inhomogeneities was developed and used to map solar wind variations measured by Explorer 35 to various heliocentric distances and to the orbits of Mercury, Venus, and Mars. The model was also used to determine power spectra velocity, density and temperature variations of 20 R sub s from spectra obtained from the Mariner 5 data at an average heliocentric distance of 180 R sub s. Five stream-stream interaction events in the Pioneer 6 data were analyzed which confirmed the picture of a spiral compression ridge interfacing the two streams and the associated east-west deflections of the solar wind flow. Magnetopause crossings observed in Explorer 35 plasma data were used to develop statics on boundary motions at lunar distance. A study of the geomagnetic disturbance field asymmetry was performed and a model of disturbance field from a partial ring current was developed.

Siscoe, G. L.↗

Off-line data analysis and data reduction from digitally controlled random test systems.

This paper discusses the merits of employing the new computer-controlled random environment control systems for fast and efficient large-scale data analysis when they are not being used for test control. Hardware and software requirements are stated. Several of the more familiar frequency functions are defined from the Fourier coefficients, the main product of the Fourier processors used in these control systems. Another function, the probability density function, is defined and suggestions for its application are made. An analysis example is presented. Some programming tips are listed, and the accuracy and reliability of frequency analysis measurements are considered.

Chapman, C. P.↗

OPAD data analysis

Data obtained in the framework of an Optical Plume Anomaly Detection (OPAD) program intended to create a rocket engine health monitor based on spectrometric detections of anomalous atomic and molecular species in the exhaust plume are analyzed. The major results include techniques for handling data noise, methods for registration of spectra to wavelength, and a simple automatic process for estimating the metallic component of a spectrum.

Buntine, Wray L.↗

Geographic Information System Data Analysis

Data was collected in order to further NASA Langley Research Center's Geographic Information System(GIS). Information on LaRC's communication, electrical, and facility configurations was collected. Existing data was corrected through verification, resulting in more accurate databases. In addition, Global Positioning System(GPS) points were used in order to accurately impose buildings on digitized images. Overall, this project will help the Imaging and CADD Technology Team (ICTT) prove GIS to be a valuable resource for LaRC.

Billings, Chad↗

Quantile Data Analysis of Image Data

Quantile data analysis and functional statistical inference methods are introduced and applied to provide representations of spectral data which may lead to simple statistical discriminators effective for the estimation of ground truth from satellite spectral measurements. To estimate the ground truth of a pixel, the probability of each possible ground truth is estimated, given observed (estimated) quantile theoretic statistical characteristics of the multispectral image data corresponding to the pixel and its neighboring pixels. A strategy for determining which statistical characteristics discriminate best is described. Results are reported of quantile data analysis of an extensive collection of training files of image data.

Parzen, E.↗

Real‐time XFEL data analysis at SLAC and NERSC: A trial run of nascent exascale experimental data analysis

X‐ray scattering experiments using free electron lasers (XFELs) are a powerful tool to determine the molecular structure and function of unknown samples (such as COVID‐19 viral proteins). XFEL experiments are a challenge to computing in two ways: (i) due to the high cost of running XFELs, a fast turnaround time from data acquisition to data analysis is essential to make informed decisions on experimental protocols; (ii) data‐collection rates are growing exponentially, requiring new scalable algorithms. Here we report our experiences analyzing data from two experiments at the Linac Coherent Light Source (LCLS) during September 2020. Raw data were analyzed on NERSC's Cori XC40 system, using the Superfacility paradigm: our workflow automatically moves raw data between LCLS and NERSC, where it is analyzed using the software package CCTBX. We achieved real time data analysis with a turnaround time from data acquisition to full molecular reconstruction in as little as 10 min—sufficient time for the experiment's operators to make informed decisions. By hosting the data analysis on Cori, and by automating LCLS‐NERSC interoperability, we achieved a data analysis rate which matches the data acquisition rate. Completing data analysis within 10 min is a first for XFEL experiments and an important milestone if we are to keep up with data‐collection trends.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Real-Time XFEL Data Analysis at SLAC and NERSC: a Trial Run of Nascent Exascale Experimental Data Analysis

X-ray scattering experiments using Free Electron Lasers (XFELs) are a powerful tool to determine the molecular structure and function of unknown samples (such as COVID-19 viral proteins). XFEL experiments are a challenge to computing in two ways: i) due to the high cost of running XFELs, a fast turnaround time from data acquisition to data analysis is essential to make informed decisions on experimental protocols; ii) data collection rates are growing exponentially, requiring new scalable algorithms. Here we report our experiences analyzing data from two experiments at the Linac Coherent Light Source (LCLS) during September 2020. Raw data were analyzed on NERSC's Cori XC40 system, using the Superfacility paradigm: our workflow automatically moves raw data between LCLS and NERSC, where it is analyzed using the software package CCTBX. We achieved real time data analysis with a turnaround time from data acquisition to full molecular reconstruction in as little as 10 min -- sufficient time for the experiment's operators to make informed decisions. By hosting the data analysis on Cori, and by automating LCLS-NERSC interoperability, we achieved a data analysis rate which matches the data acquisition rate. Furthermore, completing data analysis with 10 mins is a first for XFEL experiments and an important milestone if we are to keep up with data collection trends.

Blaschke, Johannes P.↗

Multi-layer holographic bifurcative neural network system for real-time adaptive EOS data analysis

Optical data processing techniques have the inherent advantage of high data throughout, low weight and low power requirements. These features are particularly desirable for onboard spacecraft in-situ real-time data analysis and data compression applications. The proposed multi-layer optical holographic neural net pattern recognition technique will utilize the nonlinear photorefractive devices for real-time adaptive learning to classify input data content and recognize unexpected features. Information can be stored either in analog or digital form in a nonlinear photorefractive device. The recording can be accomplished in time scales ranging from milliseconds to microseconds. When a system consisting of these devices is organized in a multi-layer structure, a feed forward neural net with bifurcating data classification capability is formed. The interdisciplinary research will involve the collaboration with top digital computer architecture experts at the University of Southern California.

Liu, Hua-Kuang↗

Multi-layer holographic bifurcative neural network system for real-time adaptive EOS data analysis

Optical data processing techniques have the inherent advantage of high data throughout, low weight and low power requirements. These features are particularly desirable for onboard spacecraft in-situ real-time data analysis and data compression applications. the proposed multi-layer optical holographic neural net pattern recognition technique will utilize the nonlinear photorefractive devices for real-time adaptive learning to classify input data content and recognize unexpected features. Information can be stored either in analog or digital form in a nonlinear photofractive device. The recording can be accomplished in time scales ranging from milliseconds to microseconds. When a system consisting of these devices is organized in a multi-layer structure, a feedforward neural net with bifurcating data classification capability is formed. The interdisciplinary research will involve the collaboration with top digital computer architecture experts at the University of Southern California.

Liu, Hua-Kuang↗

Cycles till failure of silver-zinc cells with competing failure modes - Preliminary data analysis

The data analysis of cycles to failure of silver-zinc electrochemical cells with competing failure modes is presented. The test ran 129 cells through charge-discharge cycles until failure; preliminary data analysis consisted of response surface estimate of life. Batteries fail through low voltage condition and an internal shorting condition; a competing failure modes analysis was made using maximum likelihood estimation for the extreme value life distribution. Extensive residual plotting and probability plotting were used to verify data quality and selection of model.

Sidik, S. M.↗

Post-test navigation data analysis techniques for the shuttle ALT

Postflight test analysis data processing techniques for shuttle approach and landing tests (ALT) navigation data are defined. Postfight test processor requirements are described along with operational and design requirements, data input requirements, and software test requirements. The postflight test data processing is described based on the natural test sequence: quick-look analysis, postflight navigation processing, and error isolation processing. Emphasis is placed on the tradeoffs that must remain open and subject to analysis until final definition is achieved in the shuttle data processing system and the overall ALT plan. A development plan for the implementation of the ALT postflight test navigation data processing system is presented. Conclusions are presented.

Source record↗

Apollo data analysis experiment S-211. Low brightness image data analysis

The scientific analyses of photographic data in astronomy obtained by the Apollo Orbital Science Photographic Team during Apollo flights 14 through 17 are described. Some of the tasks are the collection and correlation of Quick-Look listings, working prints for further study, the generation of post-mission reports, and project reports. Postflight calibrations of the flight photographic systems are carried out, and lens vignetting effects are corrected. The data handling is described and includes photodigitization of photographic scenes, calibrated step-wedges, and vignetting patterns, which are followed by computer program processing of the film density readings.

Mercer, R. D.↗

Goddard high resolution spectrograph science verification and data analysis

The data analysis performed was to support the Orbital Verification (OV) and Science Verification (SV) of the GHRS was in the areas of the Digicon detector's performance and stability, wavelength calibration, and geomagnetic induced image motion. The results of the analyses are briefly described. Detailed results are given in the form of attachments. Specialized software was developed for the analyses. Calibration files were formatted according to the specifications in a Space Telescope Science report. IRAS images were restored of the Large Magellanic Cloud using a blocked iterative algorithm. The algorithm works with the raw data scans without regridding or interpolating the data on an equally spaced image grid.

Source record↗

Online data analysis and reduction: An important co-design motif for extreme-scale computers

A growing disparity between supercomputer computation speeds and I/O rates means that it is rapidly becoming infeasible to analyze supercomputer application output only after that output has been written to a file system. Instead, data-generating applications must run concurrently with data reduction and/or analysis operations, with which they exchange information via high-speed methods such as interprocess communications. The resulting parallel computing motif, online data analysis and reduction (ODAR), has important implications for both application and HPC systems design. Here we introduce the ODAR motif and its co-design concerns, describe a co-design process for identifying and addressing those concerns, present tools that assist in the co-design process, and present case studies to illustrate the use of the process and tools in practical settings.

Data Analysis↗

Harnessing Uncertainty through Functional Data Analysis in Gas Breakthrough Data

Detecting subsurface explosions from radionuclide gas migration through rock fractures is an effective way to identify nuclear activity. Los Alamos National Laboratory (LANL) has developed simulation methods, based on data from the 1962 Hardhat underground nuclear test, to predict gas breakthrough times at the surface. However, these methods rely on an imperfect understanding of the relationship between rock damage and fracture permeability. Our clinic project studies methods for predicting breakthrough curves that characterize total mass produced as a function of time, as well as quantifying the uncertainty associated with these predictions. The model that is currently employed to relate damage to permeability uses an empirically motivated power-law expression, with a range of parameter values that are compatible with the experimental Hardhat data. We develop emulators, built from functional data analysis techniques and trained on simulation data, that rapidly predict the gas breakthrough curve given a damage field and given the parameter values of the power-law equation. Using Bayesian regression, we address the problem of uncertainty quantification in our emulators. Finally, in order to test the robustness of the model, we further validate it on a damage field representing different physical conditions.

58 GEOSCIENCES↗