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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

Space Shuttle flying qualities criteria assessment. Phase 5: Data acquistion and analysis

The development of flying qualities experiments (OFQ) as a part of the Orbiter Experiments Program (OEX) was continued. The data base was extended to use the ground based cinetheodolite measurements of orbiter approach and landing. Onboard the cinetheodolite data were analyzed from flights STS 2 through 7 to identify the effective augmented vehicle dynamics, the control strategy employed by the pilot during preflare, shallow glide, and final flare segments of the landing, and the key approach and touchdown performance measures. A plan for an OFQ flying qualities data archive and processing is presented.

Myers, T. T.↗
DOE OSTI2025

Descriptor: High Temporal Resolution Meteorological Data at Oak Ridge Reservation (ORR-HiResMet)

Access to continuous, quality assessed meteorological data is critical for understanding the climatology and atmospheric dynamics of a region. Research facilities like Oak Ridge National Laboratory (ORNL) rely on such data to assess site-specific climatology, model potential emissions, establish safety baselines, and prepare for emergency scenarios. To meet these needs, on-site towers at ORNL collect meteorological data at 15-minute and hourly intervals. However, data measurements from meteorological towers are affected by sensor sensitivity, degradation, lightning strikes, power fluctuations, glitching, and sensor failures, all of which can affect data quality. To address these challenges, we conducted a comprehensive quality assessment and processing of five years of meteorological data collected from ORNL at 15-minute intervals, including measurements of temperature, pressure, humidity, wind, and solar radiation. The time series of each variable was pre-processed and gap-filled using established meteorological data collection and cleaning techniques, i.e., the time series were subjected to structural standardization, data integrity testing, automated and manual outlier detection, and gap-filling. The data product and highly generalizable processing workflow developed in Python Jupyter notebooks are publicly accessible online. As a key contribution of this study, the evaluated 5-year data will be used to train atmospheric dispersion models that simulate dispersion dynamics across the complex ridge-and-valley topography of the Oak Ridge Reservation in East Tennessee.

Steckler, Morgan R. [Oak Ridge National Laboratory↗
NASA NTRS1988

AVIRIS data quality for coniferous canopy chemistry

An assessment of AVIRIS data quality for studying coniferous canopy chemistry was made. Seven flightlines of AVIRIS data were acquired over a transect of coniferous forest sites in central Oregon. Both geometric and radiometric properties of the data were examined including: pixel size, swath width, spectral position and signal-to-noise ratio. A flat-field correction was applied to AVIRIS data from a coniferous forest site. Future work with this data set will exclude data from spectrometers C and D due to low signal-to-noise ratios. Data from spectrometers A and B will be used to examine the relationship between the canopy chemical composition of the forest sites and AVIRIS spectral response.

Swanberg, Nancy A.↗
DOE OSTI2022

Radiological Data Assessment Guidance for Emergency Response

This document provides guidance on how to apply data quality practices to measurements and information collected during the response and recovery to a radiological release. The process of applying data quality practices to measurement data is called data assessment. All data quality practices applied during a radiological incident response must balance the rigorous and time-consuming process normally applied to, for example, site decommissioning and decontamination, with the time- and resource-constraints present during emergency response. The guidance in this document presents the application of data quality practices for data assessment in a graded approach, where the recommended rigor increases as the response continues through its phases and as time and resource constraints relax.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2000

Atmospheric Boundary Layer Wind Data During the Period January 1, 1998 Through January 31, 1999 at the Dallas-Fort Worth Airport: Quality Assessment - Volume 1

The quality of the Aircraft Vortex Spacing System (AVOSS) is critically dependent on representative wind profiles in the atmospheric boundary layer. These winds observed from a number of sensor systems around the Dallas-Fort Worth airport were combined into single vertical wind profiles by an algorithm developed and implemented by MIT Lincoln Laboratory. This process, called the AVOSS Winds Analysis System (AWAS), is used by AVOSS for wake corridor predictions. During times when AWAS solutions were available, the quality of the resultant wind profiles and variance was judged from a series of plots combining all sensor observations and AWAS profiles during the period 1200 to 0400 UTC daily. First, input data was evaluated for continuity and consistency from criteria established. Next, the degree of agreement among all wind sensor systems was noted and cases of disagreement identified. Finally, the resultant AWAS solution was compared to the quality-assessed input data. When profiles differed by a specified amount from valid sensor consensus winds, times and altitudes were flagged. Volume one documents the process and quality of input sensor data. Volume two documents the data processing/sorting process and provides the resultant flagged files.

Zak, J. Allen↗
NASA NTRS1978

Use of LANDSAT data to assess waterfowl habitat quality

The author has identified the following significant results. The capability of mapping ponds over a very large area was demonstrated, with multidate, multiframe LANDSAT imagery. A small double sample of aircraft data made it possible to adjust a LANDSAT large area census. Terrain classification was improved by using multitemporal LANDSAT data. Waterfowl production was estimated, using remotely determined pond data, in conjunction with FWS estimates of breeding population. Relative waterfowl habitat quality was characterized on a section by section basis.

Colwell, J. E.↗
DOE OSTI2018

Rapidly Assessing the Quality of Targeted Proteomics Experiments through Monitoring Stable-Isotope Labeled Standards

Selected reaction monitoring (SRM), also known as multiple reaction monitoring (MRM), is a data acquisition technique used in targeted analysis of molecules, including targeted proteomic studies. It exploits the unique capability of triple-quadrupole (QQQ) mass spectrometers to monitor the predefined precursor and fragment ion pairs of specific molecules of interest throughout a liquid chromatography (LC) elution profile. Compared to shotgun proteomics, targeted proteomics using SRM has high selectivity, high sensitivity, and a wide linear dynamic range,(1-3) which makes it especially useful in the accurate and reproducible quantification of low-abundance proteins in highly complex biological samples. SRM has been widely used in the fields of biomarker discovery,(4-7) analysis of protein post-translational modifications(8) and characterization of biological protein networks.(4,9) In the recent years, multiple technical advances have greatly improved the throughput of SRM analyses, allowing for the quantification of hundreds of peptides in a single analysis.(6,7,10) For example, a single 800-plex SRM assay (e.g., 400 unlabeled and heavy-labeled peptide pairs and 2400 transitions with retention time scheduling) using ultrahigh-performance liquid chromatography (UHPLC) has been developed to quantify proteins in plasma.(11) Advanced labeling techniques utilizing in vitro proteome-assisted MRM for protein absolute quantification (iMPAQT) demonstrated the capability of SRM in genome-wide protein quantification of over 18?000 human proteins.(12) Moreover, the scan speed of QQQ instrumentation has been greatly improved in recent releases of commercial instrumentation. The newly developed TSQ Altis (released in 2017) can scan more than 600 transitions per second, which is 6 times more than a traditional QQQ scan speed of 100 transitions per second. The breadth of measurement enabled by these technological improvements to QQQ mass spectrometry has increased the feasibility and popularity of large scale targeted proteomics studies,(13) a major application of which will be in clinical studies in which up to hundreds of protein candidates need to be quantified in hundreds of clinical specimens.(14) Quantitative accuracy is a primary motivating factor for utilizing a targeted proteomics protocol. The precise and reproducible absolute quantification produced by SRM assays is essential to many clinical and laboratory experiments.(15,16) Because the abundance of an endogenous peptide is calculated from the measurement of the spiked-in reference standard, it is essential to assess the data quality of these references.(17) In early applications of targeted proteomics, when instrument speed greatly limited the number of transitions that could be monitored, much of this quality assessment was done manually. However, recent improvements in instrument performance and experimental design have enabled a dramatic increase in the number of target peptides and associated SRM transitions, which makes manual quality assessment an untenable and laborious task. A variety of computational tools assist in SRM experiment design and data analysis. The first task in creating an SRM experiment is the choice of proteins and representative peptides to monitor. Achieving a reliable protein abundance requires appropriately choosing peptides that have a strong signal and are free from interferences in the biological matrix. Numerous computational tools exist to facilitate assay design by identifying peptides and refining SRM transitions.(18-21) To help share these assays and eliminate time spent designing the same transitions at multiple institutions, community portals have begun to host well-designed and vetted assays.(22-24) Analyzing the experimental data requires significant computational effort to align files across replicates and experimental conditions, pick peaks and produce quantitative values, normalize data and perform statistical tests, etc.(25-27)

Gibbons, Bryson C.↗
DOE OSTI2014

Solar Radiation Monitoring of Bluefield State College: Bluefield, West Virginia (Data)

The Historically Black Colleges and Universities (HBCU) Solar Radiation Monitoring Network operated from July 1985 through December 1996. Funded by DOE, the six-station network provided 5-minute averaged measurements of direct normal, global, and diffuse horizontal solar irradiance. The data were processed at NREL to improve the assessment of the solar radiation resources in the southeastern United States. Historical HBCU data available online include quality assessed 5-min data, monthly reports, and plots. In January 1997 the HBCU sites became part of the CONFRRM solar monitoring network and data from the two remaining active stations, Bluefield State College and Elizabeth City State University, are collected by the NREL Measurement & Instrumentation Data Center (MIDC).

14 SOLAR ENERGY↗
NASA NTRS2012

Forest Canopy Cover and Height from MISR in Topographically Complex Southwestern US Landscape Assessed with High Quality Reference Data

This study addresses the retrieval of spatially contiguous canopy cover and height estimates in southwestern USforests via inversion of a geometric-optical (GO) model against surface bidirectional reflectance factor (BRF) estimates from the Multi-angle Imaging SpectroRadiometer (MISR). Model inversion can provide such maps if good estimates of the background bidirectional reflectance distribution function (BRDF) are available. The study area is in the Sierra National Forest in the Sierra Nevada of California. Tree number density, mean crown radius, and fractional cover reference estimates were obtained via analysis of QuickBird 0.6 m spatial resolution panchromatic imagery usingthe CANopy Analysis with Panchromatic Imagery (CANAPI) algorithm, while RH50, RH75 and RH100 (50, 75, and 100 energy return) height data were obtained from the NASA Laser Vegetation Imaging Sensor (LVIS), a full waveform light detection and ranging (lidar) instrument. These canopy parameters were used to drive a modified version of the simple GO model (SGM), accurately reproducing patterns ofMISR 672 nm band surface reflectance (mean RMSE 0.011, mean R2 0.82, N 1048). Cover and height maps were obtained through model inversion against MISR 672 nm reflectance estimates on a 250 m grid.The free parameters were tree number density and mean crown radius. RMSE values with respect to reference data for the cover and height retrievals were 0.05 and 6.65 m, respectively, with of 0.54 and 0.49. MISR can thus provide maps of forest cover and height in areas of topographic variation although refinements are required to improve retrieval precision.

Chopping, Mark↗
NASA NTRSDate not supplied

A Framework for Assessing Earth Observation Metadata Quality: Implications for Data Discovery and Open Science

The Common Metadata Repository (CMR) contains metadata records describing NASA’s collection of over 8,000 Earth observation data products. The Analysis and Review of CMR (ARC) Team at Marshall Space Flight Center assesses the quality of these metadata records. Metadata, rather than the data itself, is indexed for search in both discipline-specific datacenters and global or aggregated catalogs (such as Earth data Search), making it essential for determining whether a data product is appropriate for a given research question or application need. Since metadata connects users to data, it should be as accurate and complete as possible in addition to meeting minimum database requirements. The ARC team has developed a metadata quality framework by which to assess quality. The framework consists of a set of quality criteria that converge around the dimensions of correctness, completeness, and consistency, with the goal of improving the discoverability, accessibility, and usability of NASA’s Earth Observation data. The application of the framework has resulted in a measurable improvement in NASA’s metadata quality. Key aspects of the framework’s success are the ability to systematically evaluate metadata and provide actionable quality improvement recommendations. Lessons learned from the project will be shared along with implementation details which may be relevant to other science disciplines. By aiming to make data more discoverable and accessible to a broad user community, the ARC metadata quality framework helps contribute to NASA’s commitment to open science.

Jeanne Le Roux↗
NASA NTRS2009

Data Assimilation and Regional Forecasts using Atmospheric InfraRed Sounder (AIRS) Profiles

In data sparse regions, remotely-sensed observations can be used to improve analyses, which in turn should lead to better forecasts. One such source comes from the Atmospheric Infrared Sounder (AIRS), which, together with the Advanced Microwave Sounding Unit (AMSU), provides temperature and moisture profiles with an accuracy comparable to that of radionsondes. The purpose of this poster is to describe a procedure to optimally assimilate AIRS thermodynamic profiles, obtained from the version 5.0 Earth Observing System (EOS) science team retrieval algorithm, into a regional configuration of the Weather Research and Forecasting (WRF) model using WRF-Var. The poster focuses on development of background error covariances for the regional domain and background field type, a methodology for ingesting AIRS profiles as separate over-land and over-water retrievals with different error characteristics, and utilization of level-by-level quality indicators to select only the highest quality data. The assessment of the impact of the AIRS profiles on WRF-Var analyses will focus on intelligent use of the quality indicators, optimized tuning of the WRF-Var, and comparison of analysis soundings to radiosondes. The analyses are used to conduct a month-long series of regional forecasts over the continental U.S. The long-term impact of AIRS profiles on forecast will be assessed against NAM analyses and stage IV precipitation data.

Zabodsky, Brad↗
NASA NTRS2009

Data Assimilation and Regional Forecasts Using Atmospheric InfraRed Sounder (AIRS) Profiles

In data sparse regions, remotely-sensed observations can be used to improve analyses, which in turn should lead to better forecasts. One such source comes from the Atmospheric Infrared Sounder (AIRS), which together with the Advanced Microwave Sounding Unit (AMSU), provides temperature and moisture profiles with an accuracy comparable to that of radiosondes. The purpose of this paper is to describe a procedure to optimally assimilate AIRS thermodynamic profiles--obtained from the version 5.0 Earth Observing System (EOS) science team retrieval algorithm-into a regional configuration of the Weather Research and Forecasting (WRF) model using WRF-Var. The paper focuses on development of background error covariances for the regional domain and background field type, a methodology for ingesting AIRS profiles as separate over-land and over-water retrievals with different error characteristics, and utilization of level-by-level quality indicators to select only the highest quality data. The assessment of the impact of the AIRS profiles on WRF-Var analyses will focus on intelligent use of the quality indicators, optimized tuning of the WRF-Var, and comparison of analysis soundings to radiosondes. The analyses will be used to conduct a month-long series of regional forecasts over the continental U.S. The long-tern1 impact of AIRS profiles on forecast will be assessed against verifying radiosonde and stage IV precipitation data.

Chou, Shih-Hung↗
DOE OSTI2014

A Real-Time Safety and Quality Reporting System: Assessment of Clinical Data and Staff Participation

Purpose: To report on the use of an incident learning system in a radiation oncology clinic, along with a review of staff participation. Methods and Materials: On September 24, 2010, our department initiated an online real-time voluntary reporting system for safety issues, called the Radiation Oncology Quality Reporting System (ROQRS). We reviewed these reports from the program's inception through January 18, 2013 (2 years, 3 months, 25 days) to assess error reports (defined as both near-misses and incidents of inaccurate treatment). Results: During the study interval, there were 60,168 fractions of external beam radiation therapy and 955 brachytherapy procedures. There were 298 entries in the ROQRS system, among which 108 errors were reported. There were 31 patients with near-misses reported and 27 patients with incidents of inaccurate treatment reported. These incidents of inaccurate treatment occurred in 68 total treatment fractions (0.11% of treatments delivered during the study interval). None of these incidents of inaccurate treatment resulted in deviation from the prescription by 5% or more. A solution to the errors was documented in ROQRS in 65% of the cases. Errors occurred as repeated errors in 22% of the cases. A disproportionate number of the incidents of inaccurate treatment were due to improper patient setup at the linear accelerator (P<.001). Physician participation in ROQRS was nonexistent initially, but improved after an education program. Conclusions: Incident learning systems are a useful and practical means of improving safety and quality in patient care.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRSDate not supplied

Data Fusion for Urban Air Quality Assessment & Forecasting

This presentation provides an overview for our funded project with NASA's Health and Air Quality Applied Sciences Program. The project will expand an existing air quality data fusion tool implemented in Google Earth Engine (GEE) by our project team members at Sonoma Technology, Inc. (STI), a private air quality data company. We will expand the capabilities of this tool using new methods developed by the NASA GMAO which will give it the capability of providing sub-city scale resolution and hourly frequency estimates and forecasts of three key air quality indicators: surface-level particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3). We will combine a variety of Earth Observations including satellite data, global air quality forecasts, and local data from regulatory-grade monitors and/or low cost sensors. We will implement the new data fusion capabilities into the existing GEE tool in consultation with our end-users to best address their needs for sub-city scale air quality estimates and forecasts.

K Emma Knowland↗
NASA NTRS1986

Multi-station lunar laser ranging - An analysis of data quality and earth rotation results

The lunar laser ranging (LLR) results obtained from the MERIT period (Sept. 1983 through Oct. 1984) as well as from the post-MERIT period (Nov. 1, 1984 through Aug. 12, 1985) are presented. The ranging targets on the moon include the Apollo 11, 14, and 15 reflectors and a reflector on Lunokhod 2; the LLR network includes McDonald, Texas; CERGA, France; Haleakala, Hawaii; Orroral, Australia; and Crimea, USSR, stations. Data acquired with these systems are reported, and the data quality is assessed, with particular emphasis on recent ranges. During the MERIT period, sixty-five earth rotation values (UTO) were derived from LLR data, with the best accuracy being 0.25 msec; during the post-MERIT period, 115 determinations of UTO were calculated with the best inherent accuracy of about 0.1 msec. The results are compared with those from other techniques.

Dickey, J. O.↗
NASA NTRS1974

Systematic monitoring and evaluation of M7 scanner performance and data quality

An investigation was conducted to provide the information required to maintain data quality of the Michigan M7 Multispectral scanner by systematic checks on specific system performance characteristics. Data processing techniques which use calibration data gathered routinely every mission have been developed to assess current data quality. Significant changes from past data quality are thus identified and attempts made to discover their causes. Procedures for systematic monitoring of scanner data quality are discussed. In the solar reflective region, calculations of Noise Equivalent Change in Radiance on a permission basis are compared to theoretical tape-recorder limits to provide an estimate of overall scanner performance. M7 signal/noise characteristics are examined.

Stewart, S.↗