A user-oriented time-shared online system.
Computerized method for on-line data analysis, elucidating SLIP language, request, processing, interpretation, time sharing, background activity, etc
LANGUAGE PROGRAMMING↗
SEARCH · Engineering Papers
Results for “methods: data analysis”
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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Open Science for Life in Space: Data Sharing and Tools for Knowledge Discovery
The next era in human space exploration is rapidly approaching. The use of health countermeasures and biomonitoring systems for space missions are required to counteract space health hazards and to support life to thrive in deep space (e.g., humans, animals, plants, crops; entire ecosystems within spacecrafts/habitats/spacesuits). The development of these mission components will be highly dependent on our understanding of basic biological and health responses to myriad space hazards (ionizing radiation, altered gravitational fields, altered day-night cycles, confined isolation, hostile-closed environments, distance-duration from Earth, planetary dust-regolith, and extreme temperatures/atmospheres). The fast-growing array of space biological and mission telemetry data, which in the past was simply archived after minimal analysis, holds great potential once applied to these mission challenges if it can be reorganized and formatted for Open Science. Organizing the data for such analysis is a challenge because of its multi-hierarchical, multi-modal, and heterogenous nature (molecular, cellular, tissue, organ, whole organism, behavior, ecosystem, microbiome; tabular, omics, imaging, video, biospecimen, environmental physical-chemical telemetry). This session focuses on current approaches in this domain such as: making space biological data FAIR (findable, accessible, interoperable, reusable), effective data ingestion/dissemination, observational versus experimental data, Open Science collaborations, data analysis techniques, AI/ML/knowledge graph/modeling methods, and data integration/discovery tools.
open science↗
Health and Environment Linked for Information Exchange in Atlanta (HELIX-Atlanta): A Pilot Tracking System
Objectives. To provide an overview of four environmental public health surveillance projects developed by CDC and its partners for the Health and Environment Linked for Information Exchange, Atlanta (HELIX-Atlanta) and to illustrate common issues and challenges encountered in developing an environmental public health tracking system. Methods. HELIX-Atlanta, initiated in October 2003 to develop data linkage and analysis methods that can be used by the National Environmental Public Health Tracking Network (Tracking Network), conducted four projects. We highlight the projects' work, assess attainment of the HELIX-Atlanta goals and discuss three surveillance attributes. Results. Among the major challenges was the complexity of analytic issues which required multidiscipline teams with technical expertise. This expertise and the data resided across multiple organizations. Conclusions:Establishing formal procedures for sharing data, defining data analysis standards and automating analyses, and committing staff with appropriate expertise is needed to support wide implementation of environmental public health tracking.
Rickman, Doug↗
Automatic classification of soils and vegetation with ERTS-1 data
Preliminary results of a test of a computerized analysis method using ERTS 1 data are presented. The method consisted of a four-spectral-band supervised, maximum likelihood, Gaussian classifier with training statistics derived through a combination of clustering and manual methods. The multivariate analysis method leads to the assignment of each resolution element of the data to one of a preselected set of discrete classes. The data frame was an area over the Texas-Oklahoma border including Lake Texoma. The study suggests that multispectral scanner data coupled with machine processing shows promise for earth surface cover surveys. Futhermore, the processing time is short and consequently the costs are low; a full frame can be analyzed completely within 48 hours.
Landgrebe, D. A.↗
Holistic energy analysis method for thermal management architectures of data centers
Modern high-performance computing (HPC) data centers (DCs), particularly those supporting energy-intensive artificial intelligence (AI) workloads, face escalating thermal management challenges that degrade performance through thermal throttling and drive up cooling power consumption and operational costs. To address this challenge, many have developed a wide variety of thermal management solutions (single-phase, two-phase, direct, indirect, hybrid, and more) which attempt to cool HPC DCs effectively while attempting to minimize overall system power consumption. However, the analysis of these solutions and methods to effectively compare one with another is lacking. Overall power usage effectiveness (PUE) and total-power usage effectiveness (TUE) provide a metric to quantify power consumption but fail to identify components in the system which require further optimization. To address this, we propose a holistic analytical framework – the waterfall diagram (WFD) – which leverages a waterfall chart methodology, offering a comprehensive visualization of both the thermal management system loop and heat flow pathways from individual server components to the outdoor ambient. Use of the WFD enables graphical estimations of power efficiency and cooling performance across each component of a DC cooling system and complements Sankey-style energy flow visualizations by additionally resolving stage-wise temperature changes and incremental TUE contributions. The framework is used in conjunction with simulation-based approaches, to conduct a detailed pressure drop and flow distribution analysis aimed at identifying the optimal coolant distribution architecture for a single-phase direct-to-chip water-cooled DC, which serves as the baseline for subsequent WFD analysis. Among the evaluated architectures, the 3 U modular coolant distribution architecture is found to demonstrate the best performance, considering minimal pressure drop and uniform flow distribution. In addition, TUE is calculated for each cooling loop component based on its associated pressure drop and corresponding pumping power, which are integrated into the WFD. This correlation between TUE and local temperature offers immediate insight into the power efficiency and thermal performance contributions of individual components, facilitating further development and optimization. Examples of WFD applications are presented under varying thermal loads and ambient conditions, demonstrating reasonable cooling strategies. Notably, the 3 U modular architecture maintains a consistent chip case temperature of 85°C, achieving a TUE of 1.016 at ambient temperature of 47°C, and a TUE of 1.026 at ambient temperature of 52°C. The WFD methodology provides an efficient, holistic, and streamlined framework for DC thermal management architecture assessment and enables design optimization which is important for addressing the thermal-fluidic energy challenges of current and next-generation DCs.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Machine processing methods for earth observational data
A brief review of the development over the last decade of earth resource information systems is presented. Machine data preprocessing and analysis methods are surveyed and illustrated. These include preprocessing steps intended to modify geometric and radiometric aspects of earth observational image data to enhance the ability of either human interpreters or machine algorithms to extract information from the data. Illustrations of processed and analyzed images from spaceborne sensors including the Earth Resources Technology Satellite are discussed.
Landgrebe, D. A.↗
Einstein Slew Survey: Data analysis innovations
Several new methods were needed in order to make the Einstein Slew X-ray Sky Survey. The innovations which enabled the Slew Survey to be done are summarized. These methods included experimental approach to large projects, parallel processing on a LAN, percolation source detection, minimum action identifications, and rapid dissemination of the whole data base.
Elvis, Martin S.↗
Extraction of branching ratios from HERFD data
A quantitative analysis method has been developed that allows the cross calibration of separate Uranium M 4 and M 5 X-ray absorption spectra (XAS), in particular those collected with the new High Energy Resolution Fluorescence Detection (HERFD) method. With this method, it is now possible to generate experimental Branching Ratio (BR) values from the U M 4,5 XAS HERFD data.
36 MATERIALS SCIENCE↗
Measurement of Rayleigh Scattering in Liquid Argon at Vacuum Ultraviolet Wavelengths
Liquid argon based detectors are limited in scintillation light analysis capabilities due to inconsistent measurements of fundamental constants essential for the reconstruction of scintillation events. This experiment measures the Rayleigh scattering length of vacuum ultraviolet light propagating in liquid argon in support of liquid argon experiments. Preliminary results are presented for the Rayleigh scattering length in a range of vacuum ultraviolet wavelengths. Current data collection and analysis methods in this measurement require further advancements to understand and eliminate anomalous phenomena in the data. Future measurements in this experiment aim to precisely measure the liquid argon ultraviolet light scattering length. Results will contribute to the development of new photon system analysis methods for liquid argon experiments.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Improved Data Interpretation through Identification of Time Series Periodicity Changes
Analysis and interpretation of time series data is easiest when the data values occur at uniform intervals in time, but actual data may have differing data sampling frequencies, such as monthly and daily readings. Applying data analysis techniques, such as smoothing, to such a data set may not give a representative result between time segments. The ability to automatically distinguish time segments of differing data frequency would provide a means for applying data analysis independently to each segment, though a suitable blending at segment boundaries would be required. A method for detecting frequency changes was developed and applied to Gaussian and median smoothing of hydraulic head data from groundwater wells at the U.S. Department of Energy Hanford Site in southeastern Washington state. The process identifies time segments of high-frequency (daily) or low-frequency (greater than daily) data using adjusted-bandwidth Gaussian kernel density estimation and a threshold value, which are further refined to address small blocks of low-frequency data within larger blocks of high-frequency data. User-selectable levels of smoothing are then applied independently to the time segments prior to combining the segment results for a single smoothed data set. This time segment identification approach provides effective low- and high-frequency data separation, which provides a method to apply data analysis independently to each time segment.
97 MATHEMATICS AND COMPUTING↗
Methods for a blind analysis of isobar data collected by the STAR collaboration
In 2018, the STAR collaboration collected data from $_{44}^{96}{\mathrm{Ru}}+_{44}^{96}{\mathrm{Ru}}$ and $_{40}^{96}{\mathrm{Zr}}+_{40}^{96}{\mathrm{Zr}}$ at $\sqrt{s_\text {NN}}=200$ GeV to search for the presence of the chiral magnetic effect in collisions of nuclei. The isobar collision species alternated frequently between $_{44}^{96}{\mathrm{Ru}}+_{44}^{96}{\mathrm{Ru}}$ and $_{40}^{96}{\mathrm{Zr}}+_{40}^{96}{\mathrm{Zr}}$ . In order to conduct blind analyses of studies related to the chiral magnetic effect in these isobar data, STAR developed a three-step blind analysis procedure. Analysts are initially provided a “reference sample” of data, comprised of a mix of events from the two species, the order of which respects time-dependent changes in run conditions. After tuning analysis codes and performing time-dependent quality assurance on the reference sample, analysts are provided a species-blind sample suitable for calculating efficiencies and corrections for individual $\approx 30$-min data-taking runs. For this sample, species-specific information is disguised, but individual output files contain data from a single isobar species. Only run-by-run corrections and code alteration subsequent to these corrections are allowed at this stage. Following these modifications, the “frozen” code is passed over the fully un-blind data, completing the blind analysis. As a check of the feasibility of the blind analysis procedure, analysts completed a “mock data challenge,” analyzing data from Au + Au collisions at $\sqrt{s_\text {NN}}=27$ GeV, collected in 2018. The Au + Au data were prepared in the same manner intended for the isobar blind data. Finally, the details of the blind analysis procedure and results from the mock data challenge are presented.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
On the hot surface ignition of a wall-stagnating spray flame
The ignition of fuel sprays due to interaction with hot surfaces is an important phenomenon in the safety analysis of many engineering systems. We perform a parametric study of the hot surface ignition (HSI) of a fuel spray approaching a heated surface caused by the accidental leakage of a fuel line. Here, to this end, we employ a one-dimensional Eulerian-Eulerian formulation with a non-equilibrium evaporation model and a realistic chemical mechanism to describe $n$-dodecane fuel chemistry. We first describe and analyze the phenomenology of the unsteady processes leading to ignition using non-dimensionalized quantities. Through consideration of the temporal development of the most reactive mixture, we demonstrate that ignition occurs at a fuel-lean composition in a premixed region near the hot surface. Using non-dimensional parameters identified from the governing equations, we perform a parametric study of the time, location and local mixture composition at ignition and determine the ignition limits. We then identify the most important parametric sensitivities for physical analysis using a data-driven classification method. Our analysis demonstrates a contraction of the ignition limits with increased Stokes number and a regime of parametric insensitivity of igniting mixture composition. We also show that at high Damköhler numbers, the ignition location conforms to the parametric behavior of the thermal boundary layer, whereas at low Damköhler numbers approaching the ignition limit it reaches a near-unity value of the quenching Peclet number. We then compare the demonstrated parametric dependencies to the results of the quasi-steady asymptotic ignition literature, showing that our results are consistent with those obtained analytically within the limitations imposed by the simplified formulation of the latter.
42 ENGINEERING↗
Standard methods for analysis and interpretation of Lidar data for environmental monitoring
Lidar is similar in principle to microwave radar but uses a pulsed laser as the source and an optical telescope as the receiver. Lidar observations of elastic scattering from aerosols and more recently Raman scattering from molecules have been performed in the atmosphere with favorable results. A description of the Lidar technique is provided. Lidar measurements of remote visibility are discussed together with the measurement of remote visibility and the determination of molecular concentrations.
Melfi, S. H.↗
Interpolation and extrapolation of creep rupture data by the minimum commitment method. III - Analysis of multiheats
An outline is presented of approaches for treating multiheats on the basis of the focal point convergence method. The method has been employed in the case of two highly characterized multiheats, including a 304 stainless steel studied in Japan and a low alloy carbon steel studied in England. The method makes use of the same functional form for all materials. Only the constants are varied for each multiheat. Completely computerized procedures are employed for the determination of the constants. Once the basic analysis has been performed, the representation of various members in the same system is achieved by adding linear expressions of log stress, changing only two constants in the equations to represent a selected heat.
Manson, S. S.↗
Methods for trend analysis: Examples with problem/failure data
Statistics are emphasized as an important role in quality control and reliability. Consequently, Trend Analysis Techniques recommended a variety of statistical methodologies that could be applied to time series data. The major goal of the working handbook, using data from the MSFC Problem Assessment System, is to illustrate some of the techniques in the NASA standard, some different techniques, and to notice patterns of data. Techniques for trend estimation used are: regression (exponential, power, reciprocal, straight line) and Kendall's rank correlation coefficient. The important details of a statistical strategy for estimating a trend component are covered in the examples. However, careful analysis and interpretation is necessary because of small samples and frequent zero problem reports in a given time period. Further investigations to deal with these issues are being conducted.
Church, Curtis K.↗
Numerical methods for the analysis of sampled-data systems and for the computation of system zeros
MARSYAS is a computer aided control system design package for the simulation and analysis of open loop and closed loop dynamic systems. Outlined here is the numerical and theoretical basis of the MARSYAS functions developed during the summer of 1991. In particular, the numerical computation of the matrix exponential e(exp A) = I + A + A(exp 2)/2! + A(exp 3)/3! + ... and the numerical computation of the finite system zeros of a dynamic system (continuous time or discrete time) are presented.
Hodel, A. Scottedward↗
Numerical methods for the analysis of sampled-data systems and for the computation of system zeros
MARSYAS is a computer-aided control system design package for the simulation and analysis of dynamic systems. In the summer of 1991 MARSYAS was updated to allow for the analysis of sampled-data systems in terms of frequency response, stability, etc. This update was continued during the summer of 1992 in order to extend further MARSYAS commands to the study of sampled-data systems. Further work was done to examine the computation of OPENAT transfer functions, root-locii and w-plane frequency response plots.
Hodel, A. Scottedward↗
Program of Research in Flight Dynamics, The George Washington University at NASA Langley Research Center
The program objectives are fully defined in the original proposal entitled Program of Research in Flight Dynamics in GW at NASA Langley Research Center, which was originated March 20, 1975, and in the renewals of the research program from January 1, 2003 to September 30, 2005. The program in its present form includes three major topics: 1. the improvement of existing methods and development of new methods for wind tunnel and flight data analysis, 2. the application of these methods to wind tunnel and flight test data obtained from advanced airplanes, 3. the correlation of flight results with wind tunnel measurements, and theoretical predictions.
Murphy, Patrick C.↗