Government position on quality control with small business contractors.
Government position on quality control with small business contractors
QUALITY CONTROL↗
SEARCH · Engineering Papers
Results for “Quality Control”
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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Advancements in the Aerosol Robotic Network (AERONET) Version 3 database – automated near-real-time quality control algorithm with improved cloud screening for Sun photometer aerosol optical depth (AOD) measurements
The Aerosol Robotic Network (AERONET) has provided highly accurate, ground-truth measurements of the aerosol optical depth (AOD) using Cimel Electronique Sun–sky radiometers for more than 25 years. In Version 2 (V2) of the AERONET database, the near-real-time AOD was semiautomatically quality controlled utilizing mainly cloud-screening methodology, while additional AOD data contaminated by clouds or affected by instrument anomalies were removed manually before attaining quality-assured status (Level 2.0). The large growth in the number of AERONET sites over the past 25 years resulted in significant burden to the manual quality control of millions of measurements in a consistent manner. The AERONET Version 3 (V3) algorithm provides fully automatic cloud screening and instrument anomaly quality controls. All of these new algorithm updates apply to near-real-time data as well as post-field-deployment processed data, and AERONET reprocessed the database in 2018. A full algorithm redevelopment provided the opportunity to improve data inputs and corrections such as unique filter-specific temperature characterizations for all visible and near-infrared wavelengths, updated gaseous and water vapor absorption coefficients, and ancillary data sets. The Level 2.0 AOD quality-assured data set is now available within a month after post-field calibration, reducing the lag time from up to several months. Near-real-time estimated uncertainty is determined using data qualified as V3 Level 2.0 AOD and considering the difference between the AOD computed with the pre-field calibration and AOD computed with pre-field and post-field calibration. This assessment provides a near-real-time uncertainty estimate for which average differences of AOD suggest a +0.02 bias and one sigma uncertainty of 0.02, spectrally, but the bias and uncertainty can be significantly larger for specific instrument deployments. Long-term monthly averages analyzed for the entire V3 and V2 databases produced average differences (V3–V2) of +0.002 with a ±0.02 SD (standard deviation), yet monthly averages calculated using time-matched observations in both databases were analyzed to compute an average difference of −0.002 with a ±0.004 SD. The high statistical agreement in multiyear monthly averaged AOD validates the advanced automatic data quality control algorithms and suggests that migrating research to the V3 database will corroborate most V2 research conclusions and likely lead to more accurate results in some cases.
David M. Giles↗
Mesh quality control for multiply-refined tetrahedral grids
A new algorithm for controlling the quality of multiply-refined tetrahedral meshes is presented in this paper. The basic dynamic mesh adaption procedure allows localized grid refinement and coarsening to efficiently capture aerodynamic flow features in computational fluid dynamics problems; however, repeated application of the procedure may significantly deteriorate the quality of the mesh. Results presented show the effectiveness of this mesh quality algorithm and its potential in the area of helicopter aerodynamics and acoustics.
Biswas, Rupak↗
Development of a Display Tool to Quality Control Weather Balloon Data for Space Launch Vehicles
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↗
Influence of quality control variables on failure of graphite/epoxy under extreme moisture conditions
Tension tests on graphite/epoxy composites were performed to determine the influence of various quality control variables on failure strength as a function of moisture and moderate temperatures. The extremely high and low moisture contents investigated were found to have less effect upon properties than did temperature or the quality control variables of specimen flaws and prepreg batch to batch variations. In particular, specimen flaws were found to drastically reduce the predicted strength of the composite, whereas specimens from different batches of prepreg displayed differences in strength as a function of temperature and extreme moisture exposure. The findings illustrate the need for careful specimen preparation, studies of flaw sensitivity, and careful quality control in any study of composite materials.
Clements, L. L.↗
Influence of quality control variables on failure of graphite/epoxy under extreme moisture conditions
Tension tests on graphite/epoxy composites were performed to determine the influence of various quality control variables on failure strength as a function of moisture and moderate temperatures. The extremely high and low moisture contents investigated were found to have less effect upon properties than did temperature or the quality control variables of specimen flaws and prepreg batch to batch variations. In particular, specimen flaws were found to drastically reduce the predicted strength of the composite, whereas specimens from different batches of prepreg displayed differences in strength as a function of temperature and extreme moisture exposure. The findings illustrate the need for careful specimen preparation, studies of flaw sensitvity, and careful quality control in any study of composite materials. Previously announced in STAR as N80-33493
Clements, L. L.↗
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↗
CRN5EXP: Expert system for statistical quality control
The purpose of the Expert System CRN5EXP is to assist in checking the quality of the coils at two very important mills: Hot Rolling and Cold Rolling in a steel plant. The system interprets the statistical quality control charts, diagnoses and predicts the quality of the steel. Measurements of process control variables are recorded in a database and sample statistics such as the mean and the range are computed and plotted on a control chart. The chart is analyzed through patterns using the C Language Integrated Production System (CLIPS) and a forward chaining technique to reach a conclusion about the causes of defects and to take management measures for the improvement of the quality control techniques. The Expert System combines the certainty factors associated with the process control variables to predict the quality of the steel. The paper presents the approach to extract data from the database, the reason to combine certainty factors, the architecture and the use of the Expert System. However, the interpretation of control charts patterns requires the human expert's knowledge and lends to Expert Systems rules.
Hentea, Mariana↗
Manufacturing and quality control requirements for space systems electrical harnesses
Manufacturing and quality control requirements for space vehicle electrical harnesses
QUALITY CONTROL↗
Manufacturing design and quality control: A compilation
Testing equipment and quality control procedures are described. Articles that are helpful in the evaluation, analysis, and selection of materials are presented along with patent information.
Source record↗
Automated quality control for stitching of textile articles
Quality control for stitching of a textile article is performed by measuring thread tension in the stitches as the stitches are being made, determining locations of the stitches, and generating a map including the locations and stitching data derived from the measured thread tensions. The stitching data can be analyzed, off-line or in real time, to identify defective stitches. Defective stitches can then be repaired. Real time analysis of the thread tensions allows problems such as broken needle threads to be corrected immediately.
Miller, Jeffrey L.↗
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↗
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↗
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↗
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↗
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.↗
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↗
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↗