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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Initial vegetation species and senescience/stress indicator mapping in the San Luis Valley, Colorado using imaging spectrometer data

We analyzed AVIRIS data obtained over agricultural areas in the San Luis Valley of Colorado. The data were acquired on September 3, 1993. A combined method of radiative transfer modeling and ground calibration site reflectance was used to correct the flight data to surface reflectance. This method, called Radiative Transfer Ground Calibration, or RTGC, corrects for variable water vapor in the atmosphere and produces spectra free of artifacts with spectral channel to channel noise approaching the signal to noise of the raw data. The calibration site soil samples were obtained on the day of the overflight and measured on our laboratory spectrometer. The site was near the center of the AVIRIS scene and the spectra of the soil is spectrally bland, especially in the region of the chlorophyll absorption in the visible portion of the spectrum. The center of the scene is located at approximately 106 deg 03' longitude, 37 deg 23' latitude, and the scene covers about 92 square kilometers. This scene is one of 28 in the area for a general project to study the Summitville abandoned mine site, located in the mountains west of the San Luis Valley, and its effects on the surrounding environment.

Clark, Roger N.↗
NASA NTRS2012

Topography of the Lunar Poles and Application to Geodesy with the Lunar Reconnaissance Orbiter

The Lunar Orbiter Laser Altimeter (LOLA) [1] onboard the Lunar Reconnaissance Orbiter (LRO) [2] has been operating continuously since July 2009 [3], accumulating approx.5.4 billion measurements from 2 billion on-orbit laser shots. LRO s near-polar orbit results in very high data density in the immediate vicinity of the lunar poles, which are each sampled every ~2h. With more than 10,000 orbits, high-resolution maps can be constructed [4] and studied [5]. However, this requires careful processing of the raw data, as subtle errors in the spacecraft position and pointing can lead to visible artifacts in the final map. In other locations on the Moon, ground tracks are subparallel and longitudinal separations are typically a few hundred meters. Near the poles, the track intersection angles can be large and the inter-track spacing is small (above 80 latitude, the effective resolution is better than 50m). Precision Orbit Determination (POD) of the LRO spacecraft [6] was performed to satisfy the LOLA and LRO mission requirements, which lead to a significant improvement in the orbit position knowledge over the short-release navigation products. However, with pixel resolutions of 10 to 25 meters, artifacts due to orbit reconstruction still exist. Here, we show how the complete LOLA dataset at both poles can be adjusted geometrically to produce a high-accuracy, high-resolution maps with minimal track artifacts. We also describe how those maps can then feedback to the POD work, by providing topographic base maps with which individual LOLA altimetric measurements can be contributing to orbit changes. These direct altimetry constraints improve accuracy and can be used more simply than the altimetric crossovers [6].

Mazarico, Erwan↗
DOE OSTI2024

fluxfinder: An R Package for Reproducible Calculation and Initial Processing of Greenhouse Gas Fluxes From Static Chamber Measurements

Fluxes of greenhouse gases are a critical component of the earth's natural climate, but anthropogenic emissions have created an imbalance and resulted in global climate change. Quantifying the emission of these gases is vital to our understanding of their sources and sinks, both natural and anthropogenic. The static chamber method, in which a system of interest is enclosed, and gas concentrations are measured over time, is widely used to estimate fluxes of greenhouse gases. With the development of instruments such as infrared gas analyzers (IRGAs) supporting high-frequency concentration data, there is a growing need for open-source workflows to calculate fluxes. Here we present fluxfinder, an R package designed to support reproducible calculations and processing of greenhouse gas fluxes measured with the static chamber method. The package includes raw data file parsing from widely used IRGAs, metadata matching, unit conversion, flux estimations, and initial quality assurance/quality control (QA/QC). Diagnostic graphical plots provide a transparent way to differentiate between measurement issues and nonlinear behavior. The package is also designed to be easily integrated with the gasfluxes package for further fitting of nonlinear concentration-time models, allowing alternative or additional flux QA/QC. The fluxfinder package offers a flexible workflow that is easily adaptable to promote open and reproducible greenhouse gas flux estimations.

Wilson, Stephanie J.↗
DOE OSTI2021

Quantitative analysis method for multi-color microscopy

We developed an analysis framework for quantitatively interpreting results from multi-color fluorescence microscopy data. When the emission signal from fluorescent probes (i.e. from biological microscopy or in single-particle microscopy) is spectrally separated before detection, the resulting signals contain information about the strengths of each probe. We built a model to deconvolve the raw data into quantitative descriptions of either of the wavelength of a single probe or the relative strengths among multiple probes. This approach requires only spectrally separating the image data into two or more channels, as opposed to fully resolving the spectral profile, thus allowing other microscopy techniques to be used simultaneously. Our analysis framework incorporates the response features of the optical and imaging elements used to produce the spectral separation, yielding highly quantitative interpretations of the underlying behaviors that give rise to the data.

Ryan, Duncan↗
DOE OSTI2023

Efforts to enhance reproducibility in a human performance research project

Background: Ensuring the validity of results from funded programs is a critical concern for agencies that sponsor biological research. In recent years, the open science movement has sought to promote reproducibility by encouraging sharing not only of finished manuscripts but also of data and code supporting their findings. While these innovations have lent support to third-party efforts to replicate calculations underlying key results in the scientific literature, fields of inquiry where privacy considerations or other sensitivities preclude the broad distribution of raw data or analysis may require a more targeted approach to promote the quality of research output. Methods: We describe efforts oriented toward this goal that were implemented in one human performance research program, Measuring Biological Aptitude, organized by the Defense Advanced Research Project Agency's Biological Technologies Office. Our team implemented a four-pronged independent verification and validation (IV&V) strategy including 1) a centralized data storage and exchange platform, 2) quality assurance and quality control (QA/QC) of data collection, 3) test and evaluation of performer models, and 4) an archival software and data repository. Results: Our IV&V plan was carried out with assistance from both the funding agency and participating teams of researchers. QA/QC of data acquisition aided in process improvement and the flagging of experimental errors. Holdout validation set tests provided an independent gauge of model performance. Conclusions: In circumstances that do not support a fully open approach to scientific criticism, standing up independent teams to cross-check and validate the results generated by primary investigators can be an important tool to promote reproducibility of results.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2003

Mars Mission Optimization Based on Collocation of Resources

This paper presents a powerful approach for analyzing Martian data and for optimizing mission site selection based on resource collocation. This approach is implemented in a program called PROMT (Planetary Resource Optimization and Mapping Tool), which provides a wide range of analysis and display functions that can be applied to raw data or imagery. Thresholds, contours, custom algorithms, and graphical editing are some of the various methods that can be used to process data. Output maps can be created to identify surface regions on Mars that meet any specific criteria. The use of this tool for analyzing data, generating maps, and collocating features is demonstrated using data from the Mars Global Surveyor and the Odyssey spacecraft. The overall mission design objective is to maximize a combination of scientific return and self-sufficiency based on utilization of local materials. Landing site optimization involves maximizing accessibility to collocated science and resource features within a given mission radius. Mission types are categorized according to duration, energy resources, and in-situ resource utilization. Optimization results are shown for a number of mission scenarios.

G E Chamitoff↗
NASA NTRS2016

First Results from the ISS-RAD Charged Particle Detector

The Charged Particle Detector (CPD) subsystem of the ISS-RAD detector has been making measurements of high-energy charged and neutral particles since the unit was deployed on Feb. 1, 2016. The CPD is nearly identical to the MSL-RAD instrument, but onboard data processing has been significantly modified to meet ISS requirements. We will present dose rates and LET spectra obtained over the first six months of operations, as well as preliminary results obtained from the limited sample of pulse-height analyzed raw data that has been telemetered to Earth.

Semones, Edward↗
NASA NTRSDate not supplied

NDE Methods and Capabilities Handbook – Resources for the Composites NDE Community

Composite structures are often difficult to inspect due to the anisotropic nature of the material systems and the range of flaws and defects that can arise in the manufacturing process. NASA’s Advanced Composites Project, a public-private partnership between government, universities and industry, sought to address improved methods, tools, and protocols to reduce the development and certification timeline for composite materials and structures. The rapid inspection of composites was one of the three focused research areas of the project. One deliverable of the project was to develop an NDE Methods and Capabilities Handbook. This Handbook provides a publicly available guidance document that facilitates the selection of appropriate NDE techniques and provides recommended protocols for detecting and characterizing common flaw types in solid laminate carbon fiber reinforced polymer composite (CFRP) structures. The Handbook seeks to reduce the time required to develop qualified inspection processes for composite aircraft structures during the development, certification, and manufacturing phases by providing a reference that helps minimize trial and error and provides guidance on best practices, techniques, and settings, for specific flaw types and geometries. NDE techniques include, but are not limited to ultrasound, laser based ultrasound, infrared thermography, and x-ray CT. Flaw types include, but are not limited to porosity, delamination, voids, AFP defects and impact damage. The Handbook contains details such as inspection parameters, data analysis techniques, inspection efficiency (speed & cost), and limitations. This presentation will describe key Handbook activities with examples of the techniques and flaw types examined by the Advanced Composite Consortium members. Availability of the fabricated NDE standards as well as the raw data collected on the standards by the Consortium members to the NDE community is discussed.

Patricia A Howell↗
NASA NTRSDate not supplied

The ICESat-2 Mission: Land, Ocean, and Inland Water Data Products for Middle and Low Latitude Science and Applications

NASA’s Ice, Cloud, and Land Elevation Satellite (ICESat-2) is a polar orbiting mission, launched on September 15, 2018, with over two years of nearly continuous observations. The sole instrument onboard is the Advanced Topographic Laser Altimeter System (ATLAS), a micropulse, high repetition rate, six-beam, 532 nm Lidar with photon-counting technology. Although designed primarily for detecting height changes in ice caps and sea ice in the high latitudes, it continuously observes all terrain in its track including middle and low latitude regions as well, during approximately 15 orbits per day. The official ICESat-2 products include not only cryosphere data but also global high resolution parameters associated with tree canopies, land surface, oceans, and over 1.5 million inland water bodies consisting of lakes, rivers and coastal waters. This presentation provides an overview and the status of the ICESat-2 mission including: i) a summary of the salient technological features and orbit design, ii) the official ICESat-2 science data products for ice, vegetation canopy, ocean sea level, and inland water including several examples in the middle and low latitudes, iii) a list of NASA sponsored software tools for globally browsing the two year archive and for processing both the raw data and the official ICESat-2 geophysical data products, and iv) avenues for interested users to connect with the ICESat-2 Applications Program for answering questions and assistance in possibly using ICESat-2 data in your particular science or application. The overall goal is to facilitate the use of ICESat-2 data not only for science investigations but also for improved decision support applications with societal benefit. Additional ICESat-2 information, documentation and data products are publicly available at https://nsidc.org/data/icesat-2

ICESat-2↗
NASA NTRSDate not supplied

NDE Methods and Capabilities Handbook - Resources for the Composites NDE Community

Composite structures are often difficult to inspect due to the anisotropic nature of the material systems and the range of flaws and defects that can arise in the manufacturing process. NASA’s Advanced Composites Project, a public-private partnership between government, universities and industry, sought to address improved methods, tools, and protocols to reduce the development and certification timeline for composite materials and structures. The rapid inspection of composites was one of the three focused research areas of the project. One deliverable of the project was to develop an NDE Methods and Capabilities Handbook. This Handbook provides a publicly available guidance document that facilitates the selection of appropriate NDE techniques and provides recommended protocols for detecting and characterizing common flaw types in solid laminate carbon fiber reinforced polymer composite (CFRP) structures. The Handbook seeks to reduce the time required to develop qualified inspection processes for composite aircraft structures during the development, certification, and manufacturing phases by providing a reference that helps minimize trial and error and provides guidance on best practices, techniques, and settings, for specific flaw types and geometries. Techniques include, but are not limited to ultrasound, laser based ultrasound, infrared thermography, and x-ray CT. Flaw types include, but are not limited to porosity, delaminations, voids, Automated Fiber Placement (AFP) defects and impact damage. The Handbook contains details such as inspection parameters, data analysis techniques, inspection efficiency and limitations. This paper describes key Handbook activities with examples of the techniques and flaw types examined by the Advanced Composite Consortium members. Availability to the NDE community of the fabricated NDE standards as well as the raw data collected on the standards by the Consortium members is discussed.

nondestructive evaluation↗
DOE OSTI2023

SIF and Vegetation Indices in the US Midwestern Agroecosystems, 2016-2021, Carbon Monitoring System (CMS)

This dataset contains half-hourly ground solar-induced chlorophyll fluorescence (SIF) and vegetation indices including NDVI, EVI, Red edge chlorophyll index, green chlorophyll index, and photochemical reflectance index at seven crop sites in Nebraska and Illinois for the period 2016-2021. Four sites were located at Eddy Covariance (EC) tower sites (sites US-Ne2, US-Ne3, US-UiB, and US-UiC), and three sites were located on private farms (sites Reifsteck, Rund, and Reinhart). The sites were either miscanthus, corn-soybean rotation or corn-corn-soybean rotation. The spectral data for SIF retrieval and hyperspectral reflectance for vegetation index calculation were collected by the FluoSpec2 system, installed near planting, and uninstalled after harvest to collect whole growing-season data. Raw nadir SIF at 760 nm from different algorithms (sFLD, 3FLD, iFLD, SFM) are included. SFM_nonlinear and SFM_linear represent the Spectral fitting method (SFM) with the assumption that fluorescence and reflectance change with wavelength non-linearly and linearly, respectively. Additional data include two SIF correction factors including calibration coefficient adjustment factor (f_cal_corr_QEPRO) and upscaling nadir SIF to eddy covariance footprint factor (ratio_EC footprint, SIF pixel), and measured FPAR from quantum sensors and Rededge NDVI calculated FPAR. The data are provided in comma-separated values (CSV) format.

Ameriflux↗
NASA NTRSDate not supplied

NDE Methods and Capabilities Handbook - Resources for the Composites NDE Community

Composite structures are often difficult to inspect due to the anisotropic nature of the material systems and the range of flaws and defects that can arise in the manufacturing process. NASA’s Advanced Composites Project, a public-private partnership between government, universities and industry, sought to address improved methods, tools, and protocols to reduce the development and certification timeline for composite materials and structures. The rapid inspection of composites was one of the three focused research areas of the project. One deliverable of the project was to develop an NDE Methods and Capabilities Handbook. This Handbook provides a publicly available guidance document that facilitates the selection of appropriate NDE techniques and provides recommended protocols for detecting and characterizing common flaw types in solid laminate carbon fiber reinforced polymer composite (CFRP) structures. The Handbook seeks to reduce the time required to develop qualified inspection processes for composite aircraft structures during the development, certification, and manufacturing phases by providing a reference that helps minimize trial and error and provides guidance on best practices, techniques, and settings, for specific flaw types and geometries. Techniques include, but are not limited to ultrasound, laser based ultrasound, infrared thermography, and x-ray CT. Flaw types include, but are not limited to porosity, delaminations, voids, Automated Fiber Placement (AFP) defects and impact damage. The Handbook contains details such as inspection parameters, data analysis techniques, inspection efficiency and limitations. This presentation will describe key Handbook activities with examples of the techniques and flaw types examined by the Advanced Composite Consortium members. Availability to the NDE community of the fabricated NDE standards as well as the raw data collected on the standards by the Consortium members is discussed.

Nondestructive Evaluation↗
NASA NTRS1997

Out-of-Core Streamline Visualization on Large Unstructured Meshes

It's advantageous for computational scientists to have the capability to perform interactive visualization on their desktop workstations. For data on large unstructured meshes, this capability is not generally available. In particular, particle tracing on unstructured grids can result in a high percentage of non-contiguous memory accesses and therefore may perform very poorly with virtual memory paging schemes. The alternative of visualizing a lower resolution of the data degrades the original high-resolution calculations. This paper presents an out-of-core approach for interactive streamline construction on large unstructured tetrahedral meshes containing millions of elements. The out-of-core algorithm uses an octree to partition and restructure the raw data into subsets stored into disk files for fast data retrieval. A memory management policy tailored to the streamline calculations is used such that during the streamline construction only a very small amount of data are brought into the main memory on demand. By carefully scheduling computation and data fetching, the overhead of reading data from the disk is significantly reduced and good memory performance results. This out-of-core algorithm makes possible interactive streamline visualization of large unstructured-grid data sets on a single mid-range workstation with relatively low main-memory capacity: 5-20 megabytes. Our test results also show that this approach is much more efficient than relying on virtual memory and operating system's paging algorithms.

Ueng, Shyh-Kuang↗
NASA NTRS1972

OGO-F-02 data analysis

The OGO-VI satellite, which was launched on June 5, 1969 carried a complement of twenty-six experiments. One of those instruments, the F-02 package, was a cylindrical Langmuir probe experiment whose primary purpose was to measure ionospheric electron temperatures and densities. This report briefly describes the F-02 experiment itself, outlines the computer programs developed to analyze the raw data, and gives a summary of the scientific information obtained, with the aid of this experiment.

Nagy, A. F.↗
NASA NTRS1978

System design package for the solar heating and cooling central data processing system

The central data processing system provides the resources required to assess the performance of solar heating and cooling systems installed at remote sites. These sites consist of residential, commercial, government, and educational types of buildings, and the solar heating and cooling systems can be hot-water, space heating, cooling, and combinations of these. The instrumentation data associated with these systems will vary according to the application and must be collected, processed, and presented in a form which supports continuity of performance evaluation across all applications. Overall software system requirements were established for use in the central integration facility which transforms raw data collected at remote sites into performance evaluation information for assessing the performance of solar heating and cooling systems.

Source record↗
DOE OSTI2022

Accelerating the discovery of battery electrode materials through data mining and deep learning models

The availability of crystalline materials databases allows for building accurate machine learning (ML) models that can accelerate the exploration of materials chemical space for energy storage applications. In this work, we screen all inorganic materials included in the Materials Project and AFLOW databases as potential metal-ion battery electrodes. We develop an efficient protocol to mine and screen raw data in current databases and provide a new database of electrode materials by considering pairs of charged and discharged electrodes. This effort leads to a new database with over 190,000 instances, in contrast to the original battery database which contains about 5000. The expanded battery data set is then used to build regression-based deep neural network models for predicting average voltages and percentage volume changes upon charging and discharging, which present improvements of at least 28% for target properties with respect to previous models, and are now able to predict anode electrodes (low voltage region) as well as electrodes that will not work in electrochemical cells (negative voltages), overcoming the challenges identified in previous ML models for battery electrodes. Additionally, a further screening of the expanded database itself allowed us to identify 35 novel electrode candidates with excellent battery performance metrics.

25 ENERGY STORAGE↗
DOE OSTI2024

Streaming Large-Scale Microscopy Data to a Supercomputing Facility

Data management is a critical component of modern experimental workflows. As data generation rates increase, transferring data from acquisition servers to processing servers via conventional file-based methods is becoming increasingly impractical. The 4D Camera at the National Center for Electron Microscopy generates data at a nominal rate of 480 Gbit s -1 (87,000 frames s -1 ⁠), producing a 700 GB dataset in 15 s. To address the challenges associated with storing and processing such quantities of data, we developed a streaming workflow that utilizes a high-speed network to connect the 4D Camera’s data acquisition system to supercomputing nodes at the National Energy Research Scientific Computing Center, bypassing intermediate file storage entirely. In this work, we demonstrate the effectiveness of our streaming pipeline in a production setting through an hour-long experiment that generated over 10 TB of raw data, yielding high-quality datasets suitable for advanced analyses. Additionally, we compare the efficacy of this streaming workflow against the conventional file-transfer workflow by conducting a postmortem analysis on historical data from experiments performed by real users. Our findings show that the streaming workflow significantly improves data turnaround time, enables real-time decision-making, and minimizes the potential for human error by eliminating manual user interactions.

4D-STEM↗
DOE OSTI2021

Scaling Inference Using Triton to Accelerate Particle Physics at the LHC and DUNE

DUNE and the LHC experiments consist of unique and cutting-edge particle detectors that create massive, complex, and rich datasets with billions of events. They require sophisticated algorithms to reconstruct and interpret the data. Modern machine learning algorithms provide a powerful toolset to detect and classify particles, from familiar image processing convolutional neural networks to newer graph neural network architectures. A full reconstruction of these particle collisions requires novel approaches to handle the computing challenge of processing so much raw data. In a series of studies, physicists from Fermilab, CERN, and university groups explored how to accelerate their data processing using the Triton Inference Server.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗