PSL ASME Nozzle Test: Uncertainty Analysis Methods and Results
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propulsion↗
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Impact of DORISx Post Seismic Deformation and Seasonal Corrections on the DPOD2020 Solution
As one of the tracking systems used for the altimeter missions (such as TOPEX/Poseidon, Envisat, Jason-1/-2/-3, CryoSat-2, Saral/AltiKa, Sentinel-3A/-3B, HY-2A/C/D, Jason-CS/Sentinel-6A, SWOT), the position of the DORIS tracking stations provides a fundamental reference for the estimation of the precise orbits and so, by extension is fundamental for the quality of the altimeter data analysis and derived products. Due to the time evolution of the DORIS ground network, stations included in ITRF2020 may have been decommissioned and stations that were added to the tracking network after 2021.0 are, by definition, not part of ITRF2020. Therefore, to satisfy operational requirements for precise orbit determination and routine delivery of geodetic products, the International DORIS Service maintains the DORIS terrestrial reference frame for Precise Orbit Determination (DPOD) solutions. Since 2016, the DPOD products are computed by the IDS Combination Center (CC) as a DORIS cumulative position and linear velocity solution aligned to the latest available ITRF and using the latest IDS weekly combined series. Mid-2023, the IDS CC started the computation of the second version of the DPOD2020 based on the IDS 20 weekly solutions from 1993.0 to 2023.0. With that new solution, the IDS CC will include Post Seismic Deformation (PSD) corrections for some DORIS sites such as Socorro Island. These DPOD PSD corrections are determined from the analysis of DORIS coordinate time series only. The second version will also include optional annual and semi-annual station corrections. The presentation will describe the analysis used for extracting the PSD and seasonal DORIS station corrections, compare such corrections to those derived for ITRF2020, and evaluate the impact these new corrections have on station positioning and satellite POD.
Guilhem Moreaux↗
Agricultural Burning and Air Quality over Northern India: A Synergistic Analysis Using NASA's A-Train Satellite Data and Ground Measurements
In the recent years, New Delhi, the capital city of India, has ranked among the most polluted cities in the world regarding its air quality related to the submicron Particulate Matter (PM(sub 2.5)). Using NASA's A-train satellite data (MODIS, OMI, and CALIOP), ground-level PM2.5 measured in New Delhi (2013-2016), and back-trajectory calculations, we show that the PM(sub 2.5). over New Delhi is strongly affected by the agricultural fires in the northwestern Indian states of Punjab and Haryana during the post-monsoon season (October and November). The mass concentration of PM2.5 escalates from ~50 μg m(exp -3) measured prior to the onset of residue burning in early October to as high as 300 μg m(exp -3) (24-hour averaged, 7- day running mean) during the peak burning period in early November. A linear regression analysis reveals that the variations in PM(sub 2.5) over New Delhi can be attributed to the concurrent changes in the satellite retrievals of fire counts and aerosols over the crop burning area. The back-trajectory analysis shows that most clusters (> 80%) of the northwesterly flow near the ground intercepted the crop burning region before arriving at the receptor location in New Delhi; this further corroborates the transport patterns inferred from the satellite data. A 15-year long satellite record (2002-2016) reveals an increasing trend in agricultural fires (~617 per year) and aerosol loading (0.031 and 0.04 per year in aerosol optical depth and UV aerosol index) in November. Increasing levels of crop residue burning and resulting particulate matter pollution at an alarming rate over northern India is a pressing concern demanding corrective measures to substantially reduce or completely diminish the crop burning through an effective residue management system.
Crop Residue Fires↗
Upper limits for gravitational radiation from supermassive coalescing binaries
We report a search for waves from supermassive coalescing binaries using a 10.5 day Pioneer 10 data set taken in 1988. Depending on the time to coalescence, the initial frequency of the wave, and the length of the observing interval, a coalescing binary waveform appears in the tracking record either as a sinusoid, a 'chirp', or as a more complicated signal. We searched our data for coalescing binary waveforms in all three regimes. We successfully detected a (fortuitous) 'chirp' signal caused by the varying spin rate of the spacecraft; this nicely served as a calibration of the data quality and as a test of our analysis procedures on real data. We did not detect any signals of astronomical origin in the millihertz band to an upper limit of about 7 x 10 exp -15 (rms amplitude). This is the first time spacecraft Doppler data have been analyzed for coalescing binary waveforms, and the upper limits reported here are the best to date for any waveform in the millihertz band.
Anderson, J. D.↗
EDGE COVID-19: a web platform to generate submission-ready genomes from SARS-CoV-2 sequencing efforts
Abstract Summary Genomics has become an essential technology for surveilling emerging infectious disease outbreaks. A range of technologies and strategies for pathogen genome enrichment and sequencing are being used by laboratories worldwide, together with different and sometimes ad hoc, analytical procedures for generating genome sequences. A fully integrated analytical process for raw sequence to consensus genome determination, suited to outbreaks such as the ongoing COVID-19 pandemic, is critical to provide a solid genomic basis for epidemiological analyses and well-informed decision making. We have developed a web-based platform and integrated bioinformatic workflows that help to provide consistent high-quality analysis of SARS-CoV-2 sequencing data generated with either the Illumina or Oxford Nanopore Technologies (ONT). Using an intuitive web-based interface, this workflow automates data quality control, SARS-CoV-2 reference-based genome variant and consensus calling, lineage determination and provides the ability to submit the consensus sequence and necessary metadata to GenBank, GISAID and INSDC raw data repositories. We tested workflow usability using real world data and validated the accuracy of variant and lineage analysis using several test datasets, and further performed detailed comparisons with results from the COVID-19 Galaxy Project workflow. Our analyses indicate that EC-19 workflows generate high-quality SARS-CoV-2 genomes. Finally, we share a perspective on patterns and impact observed with Illumina versus ONT technologies on workflow congruence and differences. Availability and implementation https://edge-covid19.edgebioinformatics.org, and https://github.com/LANL-Bioinformatics/EDGE/tree/SARS-CoV2. Supplementary information Supplementary data are available at Bioinformatics online.
59 BASIC BIOLOGICAL SCIENCES↗
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↗
Polished Panel Optical Receiver for Simultaneous RF/Optical Telemetry with Large DSN Antennas
The polished panel optical receiver concept described here makes use of aluminum panels on the main reflector of the Deep Space Network's (DSN's) 34-meter antennas at optical wavelengths by polishing and coating their surface to efficiently reflect near-infrared wavelengths in the 1,064 1,550-nanometer range. Achievable surface smoothness is not a limiting factor for aluminum panels, and initial field experiments indicate that the surface quality of microwave aluminum panels is sufficient to concentrate the light into small, but not diffraction-limited, spots at their primary focus. Preliminary analysis of data from high-quality microwave panels has shown that the light can be concentrated into 200 400 microradian cones, resulting in spot diameters of 2-4 mm at the 10-meter primary focus F(0) shown in the figure, or 2-4 cm spots at F(1) after magnification by the subreflector, which results in an effective focal length of about 100 meters. Three distinct implementation options are possible, with theoretically identical tracking and communications performance: Option 1: The communications assembly could be placed directly behind the subreflector at F(0), but this placement would require replacing the existing all-aluminum subreflector with a new design that transmits optical wavelengths but reflects RF, thus transmitting the optical signal to the primary focus of the parabolic polished aluminum panels at F(0), as shown in the figure. Option 2: Alternately, the optical communications assembly could be located near the first available focal-spot F(1) following reflection by the subreflector (which would have to be polished), next to the input to the beam waveguide on the main reflector as shown in the figure. Option 3: Finally, the optical communications assembly could be placed inside the pedestal room, and separated from the RF signal after the ellipsoid and before the signal reached the microwave receiver via an RF/optical dichroic near F(3).
Vilnrotter, Victor A.↗
FAIRification, Quality Assessment, and Missingness Pattern Discovery for Spatiotemporal Photovoltaic Data
The ongoing growth of the photovoltaic market has pushed the demand for power forecasting and performance evaluation for a huge population of PV power plants. Through access to a large number of time series data sets from different power plants, we have found common issues that impede the modeling process. Namely, the time series data are hard to transfer between groups due to differences in variable nomenclature, and the quality of the data sets can vary. We address the issue of variable nomenclature by FAIRifying spatiotemporal PV time series data. Through the creation of a solar power plant ontology, we propose standards for the naming and structure of metadata used to describe the data from these power plants. Using the structure from this ontology, we have developed both R and Python packages for the automation of the FAIRification process. We have also developed an R package that automates the analysis of the quality of a data set through the designation of letter grades. With access to large time series data sets across many power plants, we can utilize spatiotemporal coherence between the sites in order to improve the quality of our data. To solve the issue of data missingness, we propose the use of Spatiotemporal-GNN autoencoders to detect and impute missing values from a data set by utilizing data from power plants nearby.
14 SOLAR ENERGY↗
Investigation of several aspects of LANDSAT-4 data quality
No insurmountable problems in change detection analysis were found when portions of scenes collected simultaneously by LANDSAT 4 MSS and either LANDSAT 2 or 3. The cause of the periodic noise in LANDSAT 4 MSS images which had a RMS value of approximately 2DN should be corrected in the LANDSAT D instrument before its launch. Analysis of the P-tape of the Arkansas scene shows bands within the same focal plane very well registered except for the thermal band which was misregistered by approximately three 28.5 meter pixels in both directions. It is possible to derive tight confidence bounds for the registration errors. Preliminary analyses of the Sacramento and Arkansas scenes reveals a very high degree of consistency with earlier results for bands 3 vs 1, 3 vs 4, and 3 vs 5. Results are presented in table form. It is suggested that attention be given to the standard deviations of registrations errors to judge whether or not they will be within specification once any known mean registration errors are corrected. Techniques used for MTF analysis of a Washington scene produced noisy results.
Wrigley, R. C.↗
Analysis And Control System For Automated Welding
Automated variable-polarity plasma arc (VPPA) welding apparatus operates under electronic supervision by welding analysis and control system. System performs all major monitoring and controlling functions. It acquires, analyzes, and displays weld-quality data in real time and adjusts process parameters accordingly. Also records pertinent data for use in post-weld analysis and documentation of quality. System includes optoelectronic sensors and data processors that provide feedback control of welding process.
Powell, Bradley W.↗
FAIRification, Quality Assessment, and Missingness Pattern Discovery for Spatiotemporal Photovoltaic Data
The growth of the photovoltaic market has pushed the demand for power forecasting and performance evaluation for a huge population of PV power plants. Many of these power plants have spatiotemporal coherence that can be utilized for improving model accuracy. We have demonstrated in this paper the FAIRification of spatiotemporal PV time series data. Through the creation of a solar power plant ontology, we propose standards for the naming and structure of metadata used to describe the data from these power plants. Using the structure from this ontology, we have developed both R and Python packages for the automation of the FAIRification process. Going further, we have also developed an R package that automates the analysis of the quality of a data set through the designation of letter grades. To solve the issue of data missingness, we propose the use of St-GNN autoencoders to detect and impute missing values from a data set by utilizing data from power plants nearby.
14 SOLAR ENERGY↗
International Space Station Remote Sensing Pointing Analysis
This paper analyzes the geometric and disturbance aspects of utilizing the International Space Station for remote sensing of earth targets. The proposed instrument (in prototype development) is SHORE (Station High-Performance Ocean Research Experiment), a multiband optical spectrometer with 15 m pixel resolution. The analysis investigates the contribution of the error effects to the quality of data collected by the instrument. This analysis supported the preliminary studies to determine feasibility of utilizing the International Space Station as an observing platform for a SHORE type of instrument. Rigorous analyses will be performed if a SHORE flight program is initiated. The analysis begins with the discussion of the coordinate systems involved and then conversion from the target coordinate system to the instrument coordinate system. Next the geometry of remote observations from the Space Station is investigated including the effects of the instrument location in Space Station and the effects of the line of sight to the target. The disturbance and error environment on Space Station is discussed covering factors contributing to drift and jitter, accuracy of pointing data and target and instrument accuracies.
Jacobson, Craig A.↗
Perspectives on Citizen Science Data Quality
Information about data quality helps potential data users to determine whether and how data can be used and enables the analysis and interpretation of such data. Providing data quality information improves opportunities for data reuse by increasing the trustworthiness of the data. Recognizing the need for improving the quality of citizen science data, we describe quality assessment and quality control (QA/QC) issues for these data and offer perspectives on aspects of improving or ensuring citizen science data quality and for conducting research on related issues.
54 ENVIRONMENTAL SCIENCES↗
Genome Extraction from Shotgun Metagenome Sequence Data
Uncultivated Bacteria and Archaea comprise the vast majority of species on Earth, but obtaining their genomes directly from the environment, using shotgun sequencing, has only recently become possible. To realize the hope of capturing Earth’s microbial genetic complement, technologies that accelerate recovery of high-quality genomes are necessary. We present a series of analysis steps and data products for the extraction of high quality metagenome-assembled genomes (MAGs) from microbiomes using the U.S. Department of Energy Systems Biology Knowledgebase (KBase) platform (http://www.kbase.us/). In KBase, the process is end-to-end, allowing a user to go from the initial sequencing reads all the way through to MAG genomes, which can then be analyzed with other KBase capabilities such as phylogenetic placement, functional assignment, metabolic modeling, pangenome functional profiling, RNA-Seq, and others. While portions of such capabilities are individually available from other resources, the combination of the intuitive usability, data interoperability, and integration of tools in a freely available compute resource makes KBase a uniquely powerful platform for obtaining MAGs from microbiomes. While this workflow offers tools for each of the key steps in the genome extraction process, it also provides a scaffold that can be easily extended, with additional MAG recovery and analysis tools, via the KBase SDK (Software Development Kit).
Chivian, Dylan↗
Atmospheric Boundary Layer Wind Data During the Period January 1, 1998 Through January 21, 1999 at the Dallas-Fort Worth Airport: Data and Processing - Volume 2
The NASA Langley Research Center's Aircraft Vortex Spacing System (AVOSS) requires accurate winds and turbulence to determine aircraft wake vortex behavior near the ground. Volume 1 described the wind input and quality analysis process. This volume documents the data available during the period January 1998 through January 1999 and the partitioning and concatenation of files for time of day, turbulence, non duplication, cross wind profile quality and ceiling and visibility. It provides the resultant filtered files for the first three partitions as well as identification of ceiling/visibility conditions when they were below 5000 feet and 5 miles respectively. It also includes the wind profile quality flags to permit automatic selection of files for AVOSS application using selected ceiling/visibility and wind profile quality values and flags (or no flags).
Zak, J. Allen↗
Protein crystal growth aboard the U.S. Space Shuttle flights STS-31 and STS-32
Results obtained from the Shuttle flight STS-32 flown in January 1990, and preliminary results from the most recent Shuttle flight, STS-31, flown in April 1990, are presented. Crystals grown in microgravity environment include Canavalin, isocitrate lyase, human serum albumin, and Anti-HPr Fab. It is concluded that about 20 percent of proteins flown exhibit better morphologies or better quality data than their earth-grown counterparts. About 40 percent do not yield crystals at all and the remaining 40 percent yield crystals that are either too small for X-ray analysis or produce data of poorer quality than the best earth-grown crystals.
Delucas, Lawrence J.↗
Automated GPS Data Analysis Service
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Automatic analysis Geodetic-quality GPS data e-mai↗
Preliminary Geologic/spectral Analysis of LANDSAT-4 Thematic Mapper Data, Wind River/bighorn Basin Area, Wyoming
A LIDQA evaluation for geologic applications of a LANDSAT TM scene covering the Wind River/Bighorn Basin area, Wyoming, is examined. This involves a quantitative assessment of data quality including spatial and spectral characteristics. Analysis is concentrated on the 6 visible, near infrared, and short wavelength infrared bands. Preliminary analysis demonstrates that: (1) principal component images derived from the correlation matrix provide the most useful geologic information. To extract surface spectral reflectance, the TM radiance data must be calibrated. Scatterplots demonstrate that TM data can be calibrated and sensor response is essentially linear. Low instrumental offset and gain settings result in spectral data that do not utilize the full dynamic range of the TM system.
Lang, H. R.↗