Nasa quality requirements and cost control
NASA quality requirements and cost control
QUALITY CONTROL↗
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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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A Modeling Approach for Handling Qualities and Controls Safety Analysis of Electric Air Taxi Vehicles
The combination of modern advances in electric propulsion, fly-by-wire controls, autonomy, and increasing demand for short range air taxi operations, is currently producing an outburst of vehicle designs more diverse than ever before. Advanced software tools are needed to support the rapid and safe introduction of any design into the airspace, including the safety of the deployed flight control system and vehicle handling qualities. This paper presents a methodology for building air taxi vehicle models with distributed electric propulsion for use in analyzing flight control system safety at the conceptual design level.The approach builds on existing software tools capable of outputting aeromechanics-based linear perturbation models for Vertical Take-off and Landing vehicles with multiple rotors. Rotor torque inputs are then converted into equivalent voltage control inputs, and the linear state and input dynamics matrices are modified to include electric motor dynamics with common parameters for direct-current electric motors. The linear perturbation dynamics are then stitched across multiple operating points into a quasi-Linear Parameter Varying model that covers the full flight envelope. A Model Predictive Controller is developed for use with the full envelope model, and a tradeoff analysis between handling quality and motor requirements is demonstrated using a six passenger NASA air taxi reference design.
Urban Air Mobility↗
Cloud Motion Vectors from MISR using Sub-pixel Enhancements
The operational retrieval of height-resolved cloud motion vectors by the Multiangle Imaging SpectroRadiometer on the Terra satellite has been significantly improved by using sub-pixel approaches to co-registration and disparity assessment, and by imposing stronger quality control based on the agreement between independent forward and aft triplet retrievals. Analysis of the fore-aft differences indicates that CMVs pass the basic operational quality control 67% of the time, with rms differences - in speed of 2.4 m/s, in direction of 17 deg, and in height assignment of 290 m. The use of enhanced quality control thresholds reduces these rms values to 1.5 m/s, 17 deg and 165 m, respectively, at the cost of reduced coverage to 45%. Use of the enhanced thresholds also eliminates a tendency for the rms differences to increase with height. Comparison of CMVs from an earlier operational version that had slightly weaker quality control, with 6-hour forecast winds from the Global Modeling and Assimilation Office yielded very low bias values and an rms vector difference that ranged from 5 m/s for low clouds to 10 m/s for high clouds.
Davies, Roger↗
Apperception of Clouds in AIRS Data
Our capacity to simulate the radiative characteristics of the Earth system has advanced greatly over the past decade. However, new space based measurements show that idealized simulations might not adequately represent the complexity of nature. For example, AIRS simulated multi-layer cloud clearing research provides an excellent groundwork for early Atmospheric Infra-Red Sounder (AIRS) operational cloud clearing and atmospheric profile retrieval. However, it doesn't reflect the complicated reality of clouds over land and coastal areas. Thus far, operational AIRS/AMSU (Advanced Microwave Sounding Unit) cloud clearing is not only of low yield but also of unsatisfying quality. This is not an argument for avoiding this challenging task, rather a powerful argument for exploring other synergistic approaches, and for adapting these strategies toward improving both indirect and direct use of cloudy infrared sounding data. Ample evidence is shown in this paper that the indirect use of cloudy sounding data by way of cloud clearing is sub-optimal for data assimilation. Improvements are needed in quality control, retrieval yield, and overall cloud clearing retrieval performance. For example, cloud clearing over land, especially over the desert surface, has led to much degraded retrieval quality and often a very low yield of quality controlled cloud cleared radiances. If these indirect cloud cleared radiances are instead to be directly assimilated into NWP models, great caution must be used. Our limited and preliminary cloud clearing results from AIRS/AMSU (with the use of MODIS data) and an AIRS/MODIS synergistic approach have, however, shown that higher spatial resolution multispectral imagery data can provide much needed quality control of the AIRS/AMSU cloud clearing retrieval. When AIRS and Moderate Resolution Imaging Spectroradiometer (MODIS) are used synergistically, a higher spatial resolution over difficult terrain (especially desert areas) can be achieved and with a much improved accuracy. Preliminary statistical analyses of cloud cleared radiances derived from (1) operational AIRS/AMSU, (2) operational AIRS/AMSU plus the use of MODIS data as quality control, and (3) AIRS/MODIS synergistic single channel and two field of views cloud clearing are Our capacity to simulate the radiative characteristics of the Earth system has
Huang, Hung-Lung↗
Recent Theoretical Advances in Analysis of AIRS/AMSU Sounding Data
AIRS was launched on EOS Aqua on May 4,2002, together with AMSU-A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. This paper describes the AIRS Science Team Version 5.0 retrieval algorithm. Starting in early 2007, the Goddard DAAC will use this algorithm to analyze near real time AIRS/AMSU observations. These products are then made available to the scientific community for research purposes. The products include twice daily measurements of the Earth's three dimensional global temperature, water vapor, and ozone distribution as well as cloud cover. In addition, accurate twice daily measurements of the earth's land and ocean temperatures are derived and reported. Scientists use this important set of observations for two major applications. They provide important information for climate studies of global and regional variability and trends of different aspects of the earth's atmosphere. They also provide information for researchers to improve the skill of weather forecasting. A very important new product of the AIRS Version 5 algorithm is accurate case-by-case error estimates of the retrieved products. This heightens their utility for use in both weather and climate applications. These error estimates are also used directly for quality control of the retrieved products. Version 5 also allows for accurate quality controlled AIRS only retrievals, called "Version 5 AO retrievals" which can be used as a backup methodology if AMSU fails. Examples of the accuracy of error estimates and quality controlled retrieval products of the AIRS/AMSU Version 5 and Version 5 AO algorithms are given, and shown to be significantly better than the previously used Version 4 algorithm. Assimilation of Version 5 retrievals are also shown to significantly improve forecast skill, especially when the case-by-case error estimates are utilized in the data assimilation process.
Susskind, Joel↗
Development of Global Operational Snow Analysis at the US Air Force 557th Weather Wing
The outdated SNODEP snow depth retrieval algorithm is replaced by the Foster et al. (1997; 2005) approach, which considers the effects of variations in forest cover. The simple blending algorithm (IDW) is replaced by the Bratseth scheme, a successive correction algorithm that converges to the solution provided by Optimal Interpolation (OI). Outdated quality control datasets are updated and quality control algorithms are reorganized to ensure the performance of the snow analysis. The spatial resolution of snow and ice estimates are increased from 25-km to 10-km.USAF-SI are fully integrated into the global operational land analysis configuration at the USAF 557th WW.
Yoon, Yeosang↗
Climatological Processing of Radar Data for the TRMM Ground Validation Program
The Tropical Rainfall Measuring Mission (TRMM) satellite was successfully launched in November, 1997. The main purpose of TRMM is to sample tropical rainfall using the first active spaceborne precipitation radar. To validate TRMM satellite observations, a comprehensive Ground Validation (GV) Program has been implemented. The primary goal of TRMM GV is to provide basic validation of satellite-derived precipitation measurements over monthly climatologies for the following primary sites: Melbourne, FL; Houston, TX; Darwin, Australia; and Kwajalein Atoll, RMI. As part of the TRMM GV effort, research analysts at NASA Goddard Space Flight Center (GSFC) generate standardized TRMM GV products using quality-controlled ground-based radar data from the four primary GV sites as input. This presentation will provide an overview of the TRMM GV climatological processing system. A description of the data flow between the primary GV sites, NASA GSFC, and the TRMM Science and Data Information System (TSDIS) will be presented. The radar quality control algorithm, which features eight adjustable height and reflectivity parameters, and its effect on monthly rainfall maps will be described. The methodology used to create monthly, gauge-adjusted rainfall products for each primary site will also be summarized. The standardized monthly rainfall products are developed in discrete, modular steps with distinct intermediate products. These developmental steps include: (1) extracting radar data over the locations of rain gauges, (2) merging rain gauge and radar data in time and space with user-defined options, (3) automated quality control of radar and gauge merged data by tracking accumulations from each instrument, and (4) deriving Z-R relationships from the quality-controlled merged data over monthly time scales. A summary of recently reprocessed official GV rainfall products available for TRMM science users will be presented. Updated basic standardized product results and trends involving monthly accumulation, Z-R relationship, and gauge statistics for each primary GV site will be also displayed.
Kulie, Mark↗
Improving Forecast Skill by Assimilation of AIRS Temperature Soundings
AIRS was launched on EOS Aqua on May 4, 2002, together with AMSU-A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. The primary products of AIRS/AMSU-A are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. The AIRS Version 5 retrieval algorithm, is now being used operationally at the Goddard DISC in the routine generation of geophysical parameters derived from AIRS/AMSU data. A major innovation in Version 5 is the ability to generate case-by-case level-by-level error estimates delta T(p) for retrieved quantities and the use of these error estimates for Quality Control. We conducted a number of data assimilation experiments using the NASA GEOS-5 Data Assimilation System as a step toward finding an optimum balance of spatial coverage and sounding accuracy with regard to improving forecast skill. The model was run at a horizontal resolution of 0.5 deg. latitude X 0.67 deg longitude with 72 vertical levels. These experiments were run during four different seasons, each using a different year. The AIRS temperature profiles were presented to the GEOS-5 analysis as rawinsonde profiles, and the profile error estimates delta (p) were used as the uncertainty for each measurement in the data assimilation process. We compared forecasts analyses generated from the analyses done by assimilation of AIRS temperature profiles with three different sets of thresholds; Standard, Medium, and Tight. Assimilation of Quality Controlled AIRS temperature profiles significantly improve 5-7 day forecast skill compared to that obtained without the benefit of AIRS data in all of the cases studied. In addition, assimilation of Quality Controlled AIRS temperature soundings performs better than assimilation of AIRS observed radiances. Based on the experiments shown, Tight Quality Control of AIRS temperature profile performs best on the average from the perspective of improving Global 7 day forecast skill.
Susskind, Joel↗
Data Quality Screening Service
A report describes the Data Quality Screening Service (DQSS), which is designed to help automate the filtering of remote sensing data on behalf of science users. Whereas this process often involves much research through quality documents followed by laborious coding, the DQSS is a Web Service that provides data users with data pre-filtered to their particular criteria, while at the same time guiding the user with filtering recommendations of the cognizant data experts. The DQSS design is based on a formal semantic Web ontology that describes data fields and the quality fields for applying quality control within a data product. The accompanying code base handles several remote sensing datasets and quality control schemes for data products stored in Hierarchical Data Format (HDF), a common format for NASA remote sensing data. Together, the ontology and code support a variety of quality control schemes through the implementation of the Boolean expression with simple, reusable conditional expressions as operands. Additional datasets are added to the DQSS simply by registering instances in the ontology if they follow a quality scheme that is already modeled in the ontology. New quality schemes are added by extending the ontology and adding code for each new scheme.
Strub, Richard↗
Data acquisition and processing history for the Explorer 33 (AIMP-D) satellite
The quality control monitoring system, using accounting and quality control data bases, made it possible to perform an in-depth analysis. Results show that the percentage of useable data files for experimenter analysis was 97.7%; only 0.4% of the data sequences supplied to the experimenter exhibited missing data. The 50 percentile probability delay values (referenced to station record data) indicate that the analog tapes arrived within 11 days, the data were digitized within 4.2 weeks, and the experimenter tapes were delivered in 8.95 weeks or less.
Karras, T. J.↗
Supportability Technologies for Future Exploration Missions
Future long-duration human exploration missions will be challenged by resupply limitations and mass and volume constraints. Consequently, it will be essential that the logistics footprint required to support these missions be minimized and that capabilities be provided to make them highly autonomous from a logistics perspective. Strategies to achieve these objectives include broad implementation of commonality and standardization at all hardware levels and across all systems, repair of failed hardware at the lowest possible hardware level, and manufacture of structural and mechanical replacement components as needed. Repair at the lowest hardware levels will require the availability of compact, portable systems for diagnosis of failures in electronic systems and verification of system functionality following repair. Rework systems will be required that enable the removal and replacement of microelectronic components with minimal human intervention to minimize skill requirements and training demand for crews. Materials used in the assembly of electronic systems (e.g. solders, fluxes, conformal coatings) must be compatible with the available repair methods and the spacecraft environment. Manufacturing of replacement parts for structural and mechanical applications will require additive manufacturing systems that can generate near-net-shape parts from the range of engineering alloys employed in the spacecraft structure and in the parts utilized in other surface systems. These additive manufacturing processes will need to be supported by real-time non-destructive evaluation during layer-additive processing for on-the-fly quality control. This will provide capabilities for quality control and may serve as an input for closed-loop process control. Additionally, non-destructive methods should be available for material property determination. These nondestructive evaluation processes should be incorporated with the additive manufacturing process - providing an in-process capability to ensure that material deposited during layer-additive processing meets required material property criteria.
Watson, Kevin↗
Process and quality verification controls for solid propellant manufacturing
It is pointed out that in-process tests to verify quality and detect discrepant propellant which could compromise motor performance are essential elements of the solid composite propellant manufacturing process. The successful performance of the 260SL-1 and 260SL-2 motors aptly verified the controls used for manufacturing the propellant. The present investigation is concerned with the selected control parameters, and their relationships to composition and final propellant properties. Control performance is evaluated by comparison with processing data experienced in the manufacture of the propellant for the 260SL-1 motor. It is found that the in-process quality verification controls utilized in the propellant manufacturing process for the 260-in. diameter motor contributed significantly to the confidence of successful and predictable motor performance.
Rogers, C. J.↗
Some Improvements in H-PDLCs
Some improvements have been made in the formulation of holographically formed polymer-dispersed liquid crystals (H-PDLCs) and in the fabrication of devices made from these materials, with resulting improvements in performance. H-PDLCs are essentially volume Bragg gratings. Devices made from H-PDLCs function as electrically switchable reflective filters. Heretofore, it has been necessary to apply undesirably high drive voltages in order to switch H-PDLC devices. Many scientific papers on H-PDLCs and on the potential utility of H-PDLC devices for display and telecommunication applications have been published. However, until now, little has been published about improving quality control in synthesis of H-PDLCs and fabrication of H-PDLC devices to minimize (1) spatial nonuniformities within individual devices, (2) nonuniformities among nominally identical devices, and (3) variations in performance among nominally identical devices. The improvements reported here are results of a research effort directed partly toward solving these quality-control problems and partly toward reducing switching voltages. The quality-control improvements include incorporation of a number of process controls to create a relatively robust process, such that the H-PDLC devices fabricated in this process are more nearly uniform than were those fabricated in a prior laboratory-type process. The improved process includes ultrasonic mixing, ultrasonic cleaning, the use of a micro dispensing technique, and the use of a bubble press.
Crawford, Gregory P.↗
Hydrogen Membrane & MEA Diagnostics and Metrics: Cooperative Research and Development (Final Report)
This project will focus on diagnostics and quality control understandings of continuously produced FFI membranes [both Anion Exchange Membrane (AEM) and Proton Exchange Membrane (PEM)] and continuously produced FFI electrodes. Optimization of methods and novel quality control techniques will be developed as needed.
08 HYDROGEN↗
Ground Simulator Studies of the Effects of Valve Friction, Stick Friction, Flexibility, and Backwash on Power Control System Quality
Report presents results of tests made on a power control system by means of a ground simulator to determine the effects of various combinations of valve friction and stick friction on the ability of the pilot to control the system. Various friction conditions were simulated with a rigid control system, a flexible system, and a rigid system having some backlash. For the tests, the period and damping of the simulated airplane were held constant.
Brown, B Porter↗
Collaborative, Rapid Mapping of Water Extents During Hurricane Harvey Using Optical and Radar Satellite Sensors
On August 25, 2017, Hurricane Harvey made landfall between Port Aransas and Port O'Connor, Texas, bringing with it unprecedented amounts of rainfall and record flooding. In times of natural disasters of this nature, emergency responders require timely and accurate information about the hazard in order to assess and plan for disaster response. Due to the extreme flooding impacts associated with Hurricane Harvey, delineations of water extent were crucial to inform resource deployment. Through the USGS's Hazards Data Distribution System, government and commercial vendors were able to acquire and distribute various satellite imagery to analysts to create value-added products that can be used by these emergency responders. Rapid-response water extent maps were created through a collaborative multi-organization and multi-sensor approach. One team of researchers created Synthetic Aperture Radar (SAR) water extent maps using modified Copernicus Sentinel data (2017), processed by ESA. This group used backscatter images, pre-processed by the Alaska Satellite Facility's Hybrid Pluggable Processing Pipeline (HyP3), to identify and apply a threshold to identify water in the image. Quality control was conducted by manually examining the image and correcting for potential errors. Another group of researchers and graduate student volunteers derived water masks from high resolution DigitalGlobe and SPOT images. Through a system of standardized image processing, quality control measures, and communication channels the team provided timely and fairly accurate water extent maps to support a larger NASA Disasters Program response. The optical imagery was processed through a combination of various band thresholds and by using Normalized Difference Water Index (NDWI), Modified Normalized Water Index (MNDWI), Normalized Difference Vegetation Index (NDVI), and cloud masking. Several aspects of the pre-processing and image access were run on internal servers to expedite the provision of images to analysts who could focus on manipulating thresholds and quality control checks for maximum accuracy within the time constraints. The combined results of the radar- and optical-derived value-added products through the coordination of multiple organizations provided timely information for emergency response and recovery efforts.
SERVIR↗
Videos, photos, and AI-derived grain size data associated with “High-throughput AI Video Surveys Enable Reproducible Multiscale Sediment Size Mapping, with Implications for Hydrobiogeochemical Parameterization”
NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the manuscript “High-throughput AI Video Surveys Enable Reproducible Multiscale Sediment Size Mapping, with Implications for Hydrobiogeochemical Parameterization” under review. This data package includes five data types: 1) raw photos and videos from drone survey and walking smartphone surveys; 2) images derived from raw videos; 3) manual labeling of reference scales; 4) metadata for all images and photo resolution derived from artificial intelligence (AI) models or manual labels, 5) grain size data obtained from AI models for all photos, 6) metadata and grain size data after quality control, 7) summaries of sample efficiency for all data, and 8) computational fluid dynamics (CFD) data used to support hydro-biogeochemical (HBGC) parameter estimation. Such data is used to 1) demonstrate significant improvements in accuracy, efficiency, and quality control for grain size data collection with the help of AI models, 2) study the spatial heterogeneity of grain size and observation reproducibility based on tens of thousands of data points generated by the AI models, and 3) evaluate the impacts of grain size heterogeneity on key HBGC parameters across sediment-to-reach and hourly-to-yearly scales. In particular, the data package contains 116 folders and 179696 files. The files include 41 videos in .mov format, 64047 photos in .jpg format, 13541 video-derived photos in .png format, 12747 segmentation mask data in .tif format, 12747 segmentation data in .json format, 24771 .csv files that with metadata and grain size for each individual photo as well as water depth and velocity data from CFD and observation, 51791 .txt files of raw AI predicted labels, and 11 flight record data in .srt format. The summary for all metadata and grain size statistics information is included in “Scales_V3_NG.csv” and “Statistics_V3_NG.csv”. The summary for data that pass data quality control (QC) level 0-2 is included in “QCStatistics_V3_NG.csv”. The QC level 0 represents photos whose photo resolution is positive, excluding photos that miss reference scale. The QC level 1 means reference scale circularity uncertainty is less than 5% for smartphone images while representing photo resolution is larger than 0.44 mm/pixel for drone images. The QC level 2 means excluding photos whose grain number is less than 100, a minimum number of grains recommended by classic literature. The summary for each video’s name, length, frame rates, survey area, grain number, survey efficiency, etc. can be found in “QCSummary_V3_NG.csv”. The summary for site name, GPS coordinates, and number of images at each site can be found in “SitesSummary_V3_*.csv” files. Overall computational efficiency summary is reported in Table 4 of accompanying manuscript. Additionally, the nitrate concentration data used in this work was downloaded from an existing dataset published on ESS-DIVE (Boat-Dragged Sensor Hanford Reach.csv; Conner A. et al., 2020). We thank the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, Cowiche Canyon Conservatory, Port of Benton, and the Confederated Tribes and Bands of the Yakama Nation for access to field locations where the data were collected. We also thank the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate data collection and optimization of data usage according to their values and worldview.
54 ENVIRONMENTAL SCIENCES↗
Operational Processing of Ground Validation Data for the Tropical Rainfall Measuring Mission
The Tropical Rainfall Measuring Mission (TRMM) satellite was successfully launched in November 1997. A primary goal of TRMM is to sample tropical rainfall using the first active spaceborne precipitation radar. To validate TRMM satellite observations, a comprehensive Ground Validation (GV) Program has been implemented for this mission. A key component of GV is the analysis and quality control of meteorological ground-based radar data from four primary sites: Melbourne, FL; Houston, TX; Darwin, Australia; and Kwajalein Atoll, RMI. As part of the TRMM GV effort, the Joint Center for Earth Systems Technology (JCET) at the University of Maryland, Baltimore County, has been tasked with developing and implementing an operational system to quality control (QC), archive, and provide data for subsequent rainfall product generation from the four primary GV sites. This paper provides an overview of the JCET operational environment. A description of the QC algorithm and performance, in addition to the data flow procedure between JCET and the TRNM science and Data Information System (TSDIS), are presented. The impact of quality-controlled data on higher level rainfall and reflectivity products will also be addressed, Finally, a brief description of JCET's expanded role into producing reference rainfall products will be discussed.
Kulie, Mark S.↗