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DOE OSTI2020

PBX9502 PAGOSA/SURF Calibration for 100 µm Grid Size

There are two methods to calibrate the SURF reactive burn explosives model.The first is to calibrate using Pop plot data. Because there are only two main parameters in SURF, called A and B, there is just enough flexibility in SURF to determine the Pop plot line, i.e., equivalent information to a slope and a single point on the line. However, due to the linearity of the Pop plot being based on logarithmic scales, a slight deviation off the Pop plot (though the fit to the Pop plot might be very good overall) can make considerable difference when comparing with the velocity profile data. The second calibration method thusly focuses strongly on matching entire velocity profile data. This is to say that individual velocity profiles extracted from embedded gages (in the case of PBX 9502, we refer to R. Gustavsen’s experimental data) may fit poorly, while the overall fit to the Pop plot may seem reasonable. In addition, there are other factors that could produce slightly different calibrations for SURF, while leading to an overall acceptable fit to data. One of those may be the physics code used and here we use Pagosa. Another is mesh size dependence. A third one stems from fitting a reactive burn model being done in conjunction with an equation of state (EOS) of the reactants and one for the products – different EOS can result in slightly different parameterizations. Finally, there are several secondary material parameters in SURF, and the overall fit will depend on the entire parameterization. The goal of this report is to clarify some of our previously made statements about SURF calibration, as well as to redo a systematic calibration using 100 µm grid resolution.

42 ENGINEERING↗

NASA NTRS1977

Correlation of total, diffuse, and direct solar radiation

Present requirements for realistic solar energy system evaluations necessitate a comprehensive body of solar-radition data. The data should include both diffuse and direct solar radiation as well as their total on an hourly (or shorter) basis. In general, however, only the total solar radiation values were recorded. This report presents a correlation that relates the diffuse component of an hourly total solar radiation value to the total radiation ratio of the maximum value attainable. The data used were taken at the Blue Hill Observatory in Milton, Massachusetts, for the period 1952. The relation - in the form of the data plots - can be used in situations in which only the hourly total radiation data are available but the diffuse component is desired.

Buyco, E. H.↗

DOE OSTI2022

Ring Pull Strain Analysis

Ring Pull Strain Analysis (RPSA) is a framework for analysis of Digital Image Correlation (DIC) data of gaugeless ring pull testing. It is meant for analysis of rings cut from tube cross sections and pulled in a displacement-controlled tensile test. This code takes load frame data, images take during testing, and csv files from the DIC analysis of those images and allows the user to analyze and plot data from the test. Some important features of the software include getting the strain values as a function of radial distance and angle, plotting of the strain around the ring, and stress-strain analysis of the load frame data.

Beck, Peter↗

DOE OSTI2024

Ring Pull Strain Analysis

Beck, Peter↗

NASA NTRS1987

Multipolarization SAR data for surface feature delineation and forest vegetation characterization

This paper presents the utility of multipolarization Synthetic Aperture Radar (SAR) data for surface feature delineation and forest vegetation characterization. Three channels of radioed data (VV/HH, VH/HH, and VH/VV) are generated from the HH, VV, and VH polarization data (V = vertical, H = horizontal). The radioed data are linearly stretched to yield a digital number within a range of 0 to 255. The techniques for reducing SAR speckle noise and for measuring the degree of separation are discussed. For surface feature delineation, the results indicate that cross polarization as well as cross polarization radioed data better delineate those surface features that are difficult to separate by like polarization data. The results suggest using a median value filtering technique to reduce within-plot data fluctuation to increase the separability measure. For forest vegetation characterization, the results indicate that multipolarization SAR data may be used to estimate forest properties such as total-tree biomass, basal area, and tree height.

Wu, Shih-Tseng↗

DOE OSTI2026

Data from: "Towards CONUS-Wide ML-Augmented Conceptually-Interpretable Modeling of Catchment-Scale Precipitation-Storage-Runoff Dynamics"

This data package was generated to support the manuscript “Towards CONUS-Wide Machine Learning-Augmented Conceptually Interpretable Modeling of Catchment-Scale Precipitation-Storage-Runoff Dynamics.” It provides input files, model outputs, plotting data, scripts, notebooks, and documentation used to develop, evaluate, and reproduce Mass-Conserving Perceptron (MCP)-based hydrologic modeling experiments across 513 selected Catchment Attributes and Meteorology for Large-sample Studies in the United States (CAMELS-US) basins. The files are organized by modeling component and analysis purpose, including rainfall–runoff experiments, snow module experiments, coupled hydrologic-snow experiments, Long Short-Term Memory (LSTM) benchmark results, model skill metrics, initialization and epoch records, cell-state normalization files, Akaike Information Criterion (AIC)-based model comparison files, and data used to generate manuscript figures. Tabular files can be opened using standard spreadsheet software or Python/R data-analysis tools. Python scripts, Jupyter notebooks, and selected MATLAB scripts are included for model execution, postprocessing, plotting, and statistical analysis. Quality assurance and quality control were conducted through the source-data selection and modeling workflow. Meteorological forcing, streamflow, and static catchment attributes were derived from the CAMELS-US dataset, and snow water equivalent data were derived from the University of Arizona (UA) Snow Water Equivalent dataset. Selected basins and time periods were screened during the associated research workflow to avoid missing observations or poor-quality cases. Static geospatial features were processed primarily using Quantum Geographic Information System (QGIS) and Geospatial Data Abstraction Library (GDAL) workflows. Additional details are provided in the associated manuscript and documentation.

ESS-DIVE CSV File Formatting Guidelines Reporting ↗

NASA NTRS1999

Acceleration Measurement and Characterization in Support of the USMP-4 Payloads

One common characteristic of the USMP-4 experiments is that various effects of gravity make it difficult, if not impossible, to achieve usable results when performing the experiments on Earth's surface. Therefore, the investigators took advantage of the microgravity environment afforded by being in low-Earth orbit to perform their research. Interpretation of the experiment results both during the mission and upon post-mission analyses of data and samples required an understanding of the microgravity environment in which the experiments were conducted. To achieve that understanding, data were collected using the Orbital Acceleration Research Experiment (OARE) and two Space Acceleration Measurement Systems (SAMS). Data from those systems, combined with an assessment of mission and experiment activities, were used to characterize the microgravity environment that existed on Columbia during the mission. The text herein gives details about some characteristics of the environment that were noted during the mission and during post-mission data analysis. The disturbances studied include the Ku-band antenna 17 Hz dither; the effect of changing the Orbiter attitude deadband limits; the effects of different bicycle ergometer configurations; and the effect of IDGE (Isothermal Dendritic Growth Experiment) experiment fans and SAMS computer hard drives. Additional information about the microgravity environment is provided. Supplementary data plots representing the environment throughout the majority of the mission are available at the Uniform Resource Locator (URL). Data files for both SAMS and OARE are accessible via anonymous file transfer protocol from the file server.

Rogers, M. J. B.↗

NASA NTRS2013

CFD Extraction Tool for TecPlot From DPLR Solutions

This invention is a TecPlot macro of a computer program in the TecPlot programming language that processes data from DPLR solutions in TecPlot format. DPLR (Data-Parallel Line Relaxation) is a NASA computational fluid dynamics (CFD) code, and TecPlot is a commercial CFD post-processing tool. The Tec- Plot data is in SI units (same as DPLR output). The invention converts the SI units into British units. The macro modifies the TecPlot data with unit conversions, and adds some extra calculations. After unit conversions, the macro cuts a slice, and adds vectors on the current plot for output format. The macro can also process surface solutions. Existing solutions use manual conversion and superposition. The conversion is complicated because it must be applied to a range of inter-related scalars and vectors to describe a 2D or 3D flow field. It processes the CFD solution to create superposition/comparison of scalars and vectors. The existing manual solution is cumbersome, open to errors, slow, and cannot be inserted into an automated process. This invention is quick and easy to use, and can be inserted into an automated data-processing algorithm.

Norman, David↗

NASA NTRS1984

Results of the AFRSI detailed-environment test of the 0.035-scale SSV pressure-loads model 84-0 in the Ames 11x11 ft. TWT and the Lewis 8x6 ft. and 10x10 ft. SWT (OA-310A, B, C), volume 1

Detailed orbiter aerodynamic and aeroacoustic pressure data were obtained in a three-part experimental investigation (OA-310A, B and C). The tests were conducted in three NASA facilities: OA-310A in the Ames 11x11-foot Transonic Wind Tunnel; OA-310B in the Lewis 8x6-foot Supersonic Wind Tunnel; and OA-310C in the Lewis 10x10-foot Supersonic Wind Tunnel. Test data were obtained to support analysis of the Space Transportation System (STS)-6 advanced flexible reusable surface insulation (AFRSI) anomaly using the 0.035-scale space shuttle vehicle pressure-loads Model 84-0. Data were obtained in the areas of the orbiter where AFRSI is to be applied to OV-099 and OV-103. Emphasis was placed on acquiring detailed aeroacoustic data and time-averaged pressure distributions on five affected areas: (1) canopy; (2) side of fuselage; (3) upper surface of wing; (4) OMS pods; and (5) vertical tail. Data were obtained at nominal ascent and entry atmospheric flight trajectory conditions between M=0.6 through M-3.5. Sample plotted data are given. aba M.G.

Marshall, B. A.↗

NASA NTRS1991

Development of a calibrated software reliability model for flight and supporting ground software for avionic systems

The object of this project was to develop and calibrate quantitative models for predicting the quality of software. Reliable flight and supporting ground software is a highly important factor in the successful operation of the space shuttle program. The models used in the present study consisted of SMERFS (Statistical Modeling and Estimation of Reliability Functions for Software). There are ten models in SMERFS. For a first run, the results obtained in modeling the cumulative number of failures versus execution time showed fairly good results for our data. Plots of cumulative software failures versus calendar weeks were made and the model results were compared with the historical data on the same graph. If the model agrees with actual historical behavior for a set of data then there is confidence in future predictions for this data. Considering the quality of the data, the models have given some significant results, even at this early stage. With better care in data collection, data analysis, recording of the fixing of failures and CPU execution times, the models should prove extremely helpful in making predictions regarding the future pattern of failures, including an estimate of the number of errors remaining in the software and the additional testing time required for the software quality to reach acceptable levels. It appears that there is no one 'best' model for all cases. It is for this reason that the aim of this project was to test several models. One of the recommendations resulting from this study is that great care must be taken in the collection of data. When using a model, the data should satisfy the model assumptions.

Lawrence, Stella↗

NASA NTRS1992

A system for verifying models and classification maps by extraction of information from a variety of data sources

Recent updates to a geographical information system (GIS) called VICAR (Video Image Communication and Retrieval)/IBIS are described. The system is designed to handle data from many different formats (vector, raster, tabular) and many different sources (models, radar images, ground truth surveys, optical images). All the data are referenced to a single georeference plane, and average or typical values for parameters defined within a polygonal region are stored in a tabular file, called an info file. The info file format allows tracking of data in time, maintenance of links between component data sets and the georeference image, conversion of pixel values to `actual' values (e.g., radar cross-section, luminance, temperature), graph plotting, data manipulation, generation of training vectors for classification algorithms, and comparison between actual measurements and model predictions (with ground truth data as input).

Norikane, L.↗

NASA NTRS2006

Identifying Trends in Deep Space Network Monitor Data

A computer program has been developed that analyzes Deep Space Network monitor data, looking for changes of trends in critical parameters. This program represents a significant improvement over the previous practice of manually plotting data and visually inspecting the resulting graphs to identify trends. This program uses proven numerical techniques to identify trends. When a statistically significant trend is detected, then it is characterized by means of a symbol that can be used by pre-existing model-based reasoning software. The program can perform any of the following functions: Given an expectation that data in a given list should exhibit an upward, downward, constant, or unknown trend, it can determine whether the data do or do not follow such a trend. Given a list of data, it can identify which of the aforementioned trends the data follow. Given two lists of data, it can determine whether or not both follow the same trend. This program can be executed on a variety of computers. It can be distributed in either source code or binary code form. It must be run in conjunction with any one of a number of Lisp compilers that are available commercially or as shareware.

James, Mark↗

NASA NTRS2020

Development of a Display Tool to Quality Control Weather Balloon Data for Space Launch Vehicles Using Python

Continuous atmospheric data analysis is an important factor for space launch vehicle design and operations. The balloon quality control tool was developed by NASA’s Marshall Space Flight Center (MSFC) Natural Environments Branch (NEB) for monitoring quality control processes and verifying the automated flags created on the balloon data sets analyzed. The data sets currently analyzed are comprised of high-resolution and low-resolution balloon data from NASA Kennedy Space Center (KSC), co-located on the United States Air Force’s Eastern range (ER) at the Cape Canaveral Air Force Station. The NEB was tasked to perform a quality assessment of these data sets and needed a tool to confirm the quality control (QC) flags produced from an automated process and add additional QC flags if necessary. This Graphical User Interface (GUI) was developed to visualize all of the data from these balloon sets, display any flags from the automated QC process, and add additional flags to variables if necessary. The GUI was developed in Python 3.6 utilizing different packages available such as pandas for data analysis and manipulation, NumPy for high-performance multidimensional array and tools to compute with and manipulate arrays, Matplotlib for plotting data and Tkinter to build the GUI.

Jessica K Headley↗

NASA NTRS2020

Development of a Display Tool to Quality Control Weather Balloon Data for Space Launch Vehicles

Jessica K Headley↗

DOE OSTI2021

SURFplus model calibration for PBX 9012

PBX 9012 is a plastic bonded explosive composed of 90.2 wt % HMX (cyclo-tetramethylene-tetranitramine) and 9.8 % Viton A (vinylidene-hexafluoropropylene copolymer). It has nearly the same composition as LX-07 (90% HMX and 10% Viton A) but with a slightly lower density. Hence it has a higher porosity and is slightly more shock sensitive. Here we describe the SURFplus model calibration for PBX 9012 using data from five shock-to-detonation transition (SDT) gas gun experiments by Burns and Chiquete, detonation front shape data from rate stick experiments and cylinder test experiment reported in Anderson et al., Jackson et al. The SDT experiments provide Pop plot data points (run distance-to-detonation) which characterize shock initiation, Lagrangian velocity time histories from embedded magnetic velocity gauges which give information on the reaction behind the lead shock, and Hugoniot data points for the reactants EOS. The rate stick experiments provide data on the curvature effect which characterize propagating detonation waves. The cylinder test experiments provide data on the detonation release isentrope used to calibrate the products EOS. The HE model uses a Davis reactants EOS with parameters that Burns and Chiquete [2020] fit to Hugoniot data, and Davis products EOS with parameters that Anderson et al. [2020] fit to cylinder test data.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

NASA NTRS2006

What Happens to bone health during and after spaceflight?

Weightless conditions of space flight accelerate bone loss. There are no reports to date that address whether the bone that is lost during spaceflight could ever be recovered. Spaceinduced bone loss in astronauts is evaluated at the Johnson Space Center (JSC) by measurement of bone mineral density (BMD) by Dual-energy x-ray absorptiometry (DXA) scans. Astronauts are routinely scanned preflight and at various time points postflight (greater than or equal to Return+2 days). Two sets of BMD data were used to model spaceflight-induced loss and skeletal recovery in crewmembers following long-duration spaceflight missions (4-6 months). Group I was from astronauts (n=7) who were systematically scanned at multiple time points during the postflight period as part of a research protocol to investigate skeletal recovery. Group II came from a total of 49 sets of preflight and postflight data obtained by different protocols. These data were from 39 different crewmembers some of whom served on multiple flights. Changes in BMD (between pre- and postflight BMD) were plotted as a function of time (days-after-landing); plotted data were fitted to an exponential equation which enabled estimations of i) BMD change at day 0 after landing and ii) the number of days by which 50% of the lost bone is recovered (half-life). These fits were performed for BMD of the lumbar spine, trochanter, pelvis, femoral neck and calcaneus. There was consistency between the models for BMD recovery. Based upon the exponential model of BMD restoration, recovery following long-duration missions appears to be substantially complete in crewmembers within 36 months following return to Earth.

Sibonga, Jean D.↗

NASA NTRS2006

Skeletal Recovery Following Long-Duration Spaceflight Missions as Determined by Preflight and Postflight DXA Scans of 45 Crew Members

Introduction: The loss of bone mineral in astronauts during spaceflight has been investigated throughout the more than 40 years of bone research in space. Consequently, it is a medical requirement at NASA that changes in bone mass be monitored in crew members by measurements of bone mineral density (BMD) with dual-energy x-ray absorptiometry (DXA). This report is the first to evaluate medical data to address the recovery of bone mineral that is lost during spaceflight. Methods: DXA scans are performed before and after flight in astronauts who serve on long-duration missions (4-6 months) to ensure that medical standards for flight certification are met, to evaluate the effects of spaceflight and to monitor the restoration to preflight BMD status after return to Earth. Through cooperative agreements with the Russian Space Agency, the Bone and Mineral Lab at NASA Johnson Space Center (Houston, TX), also had access to BMD data from cosmonauts who had flown on long-duration missions yielding data from a total of 45 individual crew members. Changes in BMD (between 56 different sets of pre- and postflight measurements) were plotted as a function of time (days after landing); plotted data were fitted to an exponential mathematical model that determined i) BMD change at day 0 after landing and ii) the number of days after which 50% of the lost bone was recovered ("Recovery Half-Life"). These fits were performed for BMD of the lumbar spine, trochanter, pelvis, femoral neck and calcaneus. Results: In sum, averaged losses of bone mineral after spaceflight ranged between 2-9% for sites in the axial and appendicular skeleton. The fitted postflight BMD values predicted a 50% recovery of bone loss for all sites within 9 months.

Sibonga, J. D.↗

NASA NTRS1979

A Geophysical Atlas for Interpretation of Satellite-derived Data

A compilation of maps of global geophysical and geological data plotted on a common scale and projection is presented. The maps include satellite gravity, magnetic, seismic, volcanic, tectonic activity, and mantle velocity anomaly data. The Bibliographic references for all maps are included.

Lowman, P. D., Jr.↗