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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

FC Site 4.0 - NLR Scanning Lidar (Halo XR+ 235) / Standardized and Quality-Controlled Data

This dataset contains lidar data that have been standardized and quality-controlled through NatLabRockies/FIEXTA/LiDARGO (https://github.com/NatLabRockies/FIEXTA/tree/main/lidargo). Standardization rearranges the lidar data into convenient range vs beamID vs scanID coordinates that facilitate data analysis. The scan geometry (i.e., azimuth, elevation) is shifted on a regular grid based on the most likely angles within the scan file. Quality control of radial wind speed is performed through a generalized version of the dynamic lidar filter (Beck and Kuhn, 2017).

17 WIND ENERGY↗
DOE OSTI2026

FC Site 4.2 - NLR Scanning Lidar (Halo XR+ 199) / Standardized and Quality-Controlled Data

This dataset contains lidar data that have been standardized and quality-controlled through NatLabRockies/FIEXTA/LiDARGO (https://github.com/NatLabRockies/FIEXTA/tree/main/lidargo). Standardization rearranges the lidar data into convenient range vs beamID vs scanID coordinates that facilitate data analysis. The scan geometry (i.e., azimuth, elevation) is shifted on a regular grid based on the most likely angles within the scan file. Quality control of radial wind speed is performed through a generalized version of the dynamic lidar filter (Beck and Kuhn, 2017).

17 WIND ENERGY↗
DOE OSTI2026

FC Site 1.9 - NLR Scanning Lidar (Halo XR+ 200) / Standardized and Quality-Controlled Data

This dataset contains lidar data that have been standardized and quality-controlled through NatLabRockies/FIEXTA/LiDARGO (https://github.com/NatLabRockies/FIEXTA/tree/main/lidargo). Standardization rearranges the lidar data into convenient range vs beamID vs scanID coordinates that facilitate data analysis. The scan geometry (i.e., azimuth, elevation) is shifted on a regular grid based on the most likely angles within the scan file. Quality control of radial wind speed is performed through a generalized version of the dynamic lidar filter (Beck and Kuhn, 2017).

17 WIND ENERGY↗
DOE OSTI2024

In-Line Optical Transmission Imaging of Decals for Quality Control - Task 3

Quality monitoring is a critical aspect for manufacturing systems. Ideally the monitoring would be done in-line, be non-contact, non-destructive, and fast. This would enable reduced scrap and higher throughput. This poster presents an optical transmission method for evaluating and mapping coatings. With the method shown in the poster we can visualize optical variations on the macro and micro scales. This allows us to see the overall trend in loading in both the cross web and down web directions. Furthermore, we can visualize defects such dewetting spots, streaks, clumps, and pinholes where there is a lack of coating. The optical transmission signal has been found to be proportional to the IrOx loading signal using XRF measurements. Therefore, an optical transmission setup can be installed in-line and allow for a fast, non-contact method for mapping loading variations and defects.

coating uniformity↗
DOE OSTI2022

Automatic Waveform Quality Control for Surface Waves Using Machine Learning

Surface-wave seismograms are widely used by researchers to study Earth’s interior and earthquakes. To extract information reliably and robustly from a suite of surface waveforms, the signals require quality control screening to reduce artifacts from signal complexity and noise. This process has usually been completed by human experts labeling each waveform visually, which is time consuming and tedious for large data sets. We explore automated approaches to improve the efficiency of waveform quality control processing by investigating logistic regression, support vector machines, K-nearest neighbors, random forests (RF), and artificial neural networks (ANN) algorithms. To speed up signal quality assessment, we trained these five machine learning (ML) methods using nearly 400,000 human-labeled waveforms. The ANN and RF models outperformed other algorithms and achieved a test accuracy of 92%. We evaluated these two best-performing models using seismic events from geographic regions not used for training. The results show that the two trained models agree with labels from human analysts but required only 0.4% of the time. Although the original (human) quality assignments assessed general waveform signal-to-noise, the ANN or RF labels can help facilitate detailed waveform analysis. Our investigations demonstrate the capability of the automated processing using these two ML models to reduce outliers in surface-wave-related measurements without human quality control screening.

58 GEOSCIENCES↗
NASA NTRS2011

Sustainability of the Catalytic Activity of a Silica-Titania Composite (STC) for Long-Term Indoor Air Quality Control

TiO2-assisted photocatalytic oxidation (PCO) is an emerging technology for indoor air quality control and is also being evaluated as an alternative trace contaminant control technology for crew habitats in space exploration. Though there exists a vast range of literature on the development of photocatalysts and associated reactor systems, including catalyst performance and performance-influencing factors, the critical question of whether photocatalysts can sustain their initial catalytic activity over an extended period of operation has not been adequately addressed. For a catalyst to effectively serve as an air quality control product, it must be rugged enough to withstand exposure to a multitude of low concentration volatile organic compounds (VOCs) over long periods of time with minimal loss of activity. The objective of this study was to determine the functional lifetime of a promising photocatalyst - the silica-titania composite (STC) from Sol Gel Solutions, LLC in a real-world scenario. A bench-scale STC-packed annular reactor under continuous irradiation by a UV-A fluorescent black-light blue lamp ((lambda)max = 365 nm) was exposed to laboratory air continuously at an apparent contact time of 0.27 sand challenged with a known concentration of ethanol periodically to assess any changes in catalytic activity. Laboratory air was also episodically spiked with halocarbons (e.g., octafluoropropane), organosulfur compounds (e.g., sulfur hexafluoride), and organosilicons (e.g., siloxanes) to simulate accidental releases or leaks of such VOCs. Total organic carbon (TOC) loading and contaminant profiles of the laboratory air were also monitored. Changes in STC photocatalytic performance were evaluated using the ethanol mineralization rate, mineralization efficiency, and oxidation intermediate (acetaldehyde) formation. Results provide insights to any potential catalyst poisoning by trace halocarbons and organosulfur compounds.

Coutts, Janelle L.↗
NASA NTRS1972

Manufacture and quality control of interconnecting wire hardnesses, Volume 1

A standard is presented for manufacture, installation, and quality control of eight types of interconnecting wire harnesses. The processes, process controls, and inspection and test requirements reflected are based on acknowledgment of harness design requirements, acknowledgment of harness installation requirements, identification of the various parts, materials, etc., utilized in harness manufacture, and formulation of a typical manufacturing flow diagram for identification of each manufacturing and quality control process, operation, inspection, and test. The document covers interconnecting wire harnesses defined in the design standard, including type 1, enclosed in fluorocarbon elastomer convolute, tubing; type 2, enclosed in TFE convolute tubing lines with fiberglass braid; type 3, enclosed in TFE convolute tubing; and type 5, combination of types 3 and 4. Knowledge gained through experience on the Saturn 5 program coupled with recent advances in techniques, materials, and processes was incorporated.

Source record↗
NASA NTRS2008

Data Assimilation Experiments using Quality Controlled AIRS Version 5 Temperature Soundings

The AIRS Science Team Version 5 retrieval algorithm has been finalized and is now operational at the Goddard DAAC in the processing (and reprocessing) of all AIRS data. The AIRS Science Team Version 5 retrieval algorithm contains two significant improvements over Version 4: 1) Improved physics allows for use of AIRS observations in the entire 4.3 pm C02 absorption band in the retrieval of temperature profile T(p) during both day and night. Tropospheric sounding 15 pm C02 observations are now used primarily in the generation of cloud cleared radiances Ri. This approach allows for the generation of accurate values of Ri and T(p) under most cloud conditions. 2) Another very significant improvement in Version 5 is the ability to generate accurate case-by-case, level-by-level error estimates for the atmospheric temperature profile, as well as for channel-by- channel error estimates for Ri. These error estimates are used for quality control of the retrieved products. We have conducted forecast impact experiments assimilating AIRS temperature profiles with different levels of quality control using the NASA GEOS-5 data assimilation system. Assimilation of quality controlled T(p) resulted in significantly improved forecast skill compared to that obtained from analyses obtained when all data used operationally by NCEP, except for AIRS data, is assimilated. We also conducted an experiment assimilating AIRS radiances uncontaminated by clouds, as done Operationally by ECMWF and NCEP. Forecasts resulting from assimilated AIRS radiances were of poorer quality than those obtained assimilating AIRS temperatures.

SUsskind, Joel↗
NASA NTRS2009

Improving Forecast Skill by Assimilation of Quality Controlled AIRS Version 5 Temperature Soundings

The AIRS Science Team Version 5 retrieval algorithm has been finalized and is now operational at the Goddard DAAC in the processing (and reprocessing) of all AIRS data. The AIRS Science Team Version 5 retrieval algorithm contains two significant improvements over Version 4: 1) Improved physics allows for use of AIRS observations in the entire 4.3 micron CO2 absorption band in the retrieval of temperature profile T(p) during both day and night. Tropospheric sounding 15 micron CO2 observations are now used primarily in the generation of cloud cleared radiances R(sub i). This approach allows for the generation of accurate values of R(sub i) and T(p) under most cloud conditions. 2) Another very significant improvement in Version 5 is the ability to generate accurate case-by-case, level-by-level error estimates for the atmospheric temperature profile, as well as for channel-by-channel error estimates for R(sub i). These error estimates are used for Quality Control of the retrieved products. We have conducted forecast impact experiments assimilating AIRS temperature profiles with different levels of Quality Control using the NASA GEOS-5 data assimilation system. Assimilation of Quality Controlled T(p) resulted in significantly improved forecast skill compared to that obtained from analyses obtained when all data used operationally by NCEP, except for AIRS data, is assimilated. We also conducted an experiment assimilating AIRS radiances uncontaminated by clouds, as done operationally by ECMWF and NCEP. Forecast resulting from assimilated AIRS radiances were of poorer quality than those obtained assimilating AIRS temperatures.

Susskind, Joel↗
DOE OSTI2022

ATLAS ITk strip sensor quality control procedures and testing site qualification

Abstract The high-luminosity upgrade of the Large Hadron Collider, scheduled to become operational in 2029, requires the replacement of the ATLAS Inner Detector with a new all-silicon Inner Tracker. Radiation hard n + -in-p micro-strip silicon sensors were developed by the ATLAS Inner Tracker strip collaboration and are produced by Hamamatsu Photonics K.K. Production of the total amount of 22000 strip sensors has started in 2020 and will continue until 2025. The ATLAS strip sensor collaboration has the responsibility to monitor the quality of the fabricated devices by performing detailed measurements of individual sensor characteristics and by comparing the obtained results with the tests done by the manufacturer. Dedicated Quality Control procedures were developed to check whether the delivered large-format sensors adhere to the ATLAS specifications. The institutes performing the Quality Control testing of the pre-production and production ATLAS ITk strip sensors had to initially be qualified for multiple high-throughput tests by successfully completing the Site Qualification process. The Quality Control procedures and the qualification process are described in this paper.

Instruments & Instrumentation↗
NASA NTRS2009

Data Assimilation Experiments Using Quality Controlled AIRS Version 5 Temperature Soundings

The AIRS Science Team Version 5 retrieval algorithm has been finalized and is now operational at the Goddard DAAC in the processing (and reprocessing) of all AIRS data. The AIRS Science Team Version 5 retrieval algorithm contains a number of significant improvements over Version 4. Two very significant improvements are described briefly below. 1) The AIRS Science Team Radiative Transfer Algorithm (RTA) has now been upgraded to accurately account for effects of non-local thermodynamic equilibrium on the AIRS observations. This allows for use of AIRS observations in the entire 4.3 micron CO2 absorption band in the retrieval algorithm during both day and night. Following theoretical considerations, tropospheric temperature profile information is obtained almost exclusively from clear column radiances in the 4.3 micron CO2 band in the AIRS Version 5 temperature profile retrieval step. These clear column radiances are a derived product that are indicative of radiances AIRS channels would have seen if the field of view were completely clear. Clear column radiances for all channels are determined using tropospheric sounding 15 micron CO2 observations. This approach allows for the generation of accurate values of clear column radiances and T(p) under most cloud conditions. 2) Another very significant improvement in Version 5 is the ability to generate accurate case-by-case, level-by-level error estimates for the atmospheric temperature profile, as well as for channel-by-channel clear column radiances. These error estimates are used for quality control of the retrieved products. Based on error estimate thresholds, each temperature profiles is assigned a characteristic pressure, pg, down to which the profile is characterized as good for use for data assimilation purposes. We have conducted forecast impact experiments assimilating AIRS quality controlled temperature profiles using the NASA GEOS-5 data assimilation system, consisting of the NCEP GSI analysis coupled with the NASA FVGCM, at a spatial resolution of 0.5 deg by 0.5 deg. Assimilation of Quality Controlled AIRS temperature profiles down to pg resulted in significantly improved forecast skill compared to that obtained from experiments when all data used operationally by NCEP, except for AIRS data, is assimilated. These forecasts were also significantly better than to those obtained when AIRS radiances (rather than temperature profiles) are assimilated, which is the way AIRS data is used operationally by NCEP and ECMWF.

Susskind, Joel↗
DOE OSTI2021

Pycheron: A Python-Based Seismic Waveform Data Quality Control Software Package

Supplementing an existing high-quality seismic monitoring network with openly available station data could improve coverage and decrease magnitudes of completeness; however, this can present challenges when varying levels of data quality exist. Without discerning the quality of openly available data, using it poses significant data management, analysis, and interpretation issues. Incorporating additional stations without properly identifying and mitigating data quality problems can degrade overall monitoring capability. If openly available stations are to be used routinely, a robust, automated data quality assessment for a wide range of quality control (QC) issues is essential. To meet this need, we developed Pycheron, a Python-based library for QC of seismic waveform data. Pycheron was initially based on the Incorporated Research Institutions for Seismology’s Modular Utility for STAtistical kNowledge Gathering but has been expanded to include more functionality. Pycheron can be implemented at the beginning of a data processing pipeline or can process stand-alone data sets. Its objectives are to (1) identify specific QC issues; (2) automatically assess data quality and instrumentation health; (3) serve as a basic service that all data processing builds on by alerting downstream processing algorithms to any quality degradation; and (4) improve our ability to process orders of magnitudes more data through performance optimizations. This article provides an overview of Pycheron, its features, basic workflow, and an example application using a synthetic QC data set.

58 GEOSCIENCES↗
DOE OSTI2026

Mu2e straw tube tracker gas flow quality control

Here, we present a tracker gas flow quality control method developed for the Mu2e straw tube tracker. Using time-dependent current measurements, we quantify the onset time of ionization gain induced by an 55 F source during gas exchange, which is correlated to the gas conductance in the straw. This allows for the identification of channels with inadequate flow. This approach is broadly applicable to other gaseous detectors that require high-channel-count screening.

Flow↗
DOE OSTI2021

Quality control of mislocalized and orphan proteins

A healthy and functional proteome is essential to cell physiology. However, this is constantly being challenged as most steps of protein metabolism are error-prone and changes in the physico-chemical environment can affect protein structure and function, thereby disrupting proteome homeostasis. Among a variety of potential mistakes, proteins can be targeted to incorrect compartments or subunits of protein complexes may fail to assemble properly with their partners, resulting in the formation of mislocalized and orphan proteins, respectively. Quality control systems are in place to handle these aberrant proteins, and to minimize their detrimental impact on cellular functions. Here, we discuss recent findings on quality control mechanisms handling mislocalized and orphan proteins. We highlight common principles involved in their recognition and summarize how accumulation of these aberrant molecules is associated with aging and disease.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

UR 2 : Ultra-rapid reactivity test for real-time, low-cost quality control of calcined clays

To reduce cement's carbon footprint, there is growing interest in commercial adoption of sustainable SCMs such as calcined clays. However, the existing ASTM standard (R 3 test, C1897) to test the reactivity of such clays takes up to 7 days and cannot be used for real-time quality control in an industrial setting. We address this issue by introducing a 5-min Ultra-Rapid Reactivity (UR 2 ) test. By dissolving 47 clay specimens in 4 M NaOH solutions at 90°C, we report that a dissolution index of 1.54Al + Si correlates strongly to the 7-day R 3 heat (R 2 = 0.92, RMSE = 94.1 J/g). This dissolution index also correlates to the 28-day compressive strength for 14 clay mixtures (R 2 = 0.94, RMSE = 1.7 MPa). This UR 2 test relies on colorimetry and can be conducted via off-the-shelf, low-cost cameras. Overall, our new UR 2 test opens a pathway for real-time, low-cost quality control of calcined clays.

36 MATERIALS SCIENCE↗