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This Software Interface Specification (SIS) describes the form and syntax of each S/C Event File (SEF) which is a product of the Mission Sequence System (MSS).
These data files contain the inflow measurements made with a laser velocimeter on a helicopter model in forward flight, volume X, rectangular planform blades at an advance ratio of .30, .50 chord above the tip path plane.
This slide presentation reviews the use of a simple text file to work with large, multi-component thermal models that present a post-processing challenge. This complexity is due to temperatures for many components, with varying requirements, need to be examined and that false color temperature maps, or rainbows, provide a qualitative assessment of results.
A program has been written to enable (1) fast and easy searching of symbolic files for one or more strings of characters, dates, or numerical values in specific fields or columns and (2) summarizing results of searching other fields or columns.
This presentation discusses the experiences of the NASA Dryden Flight Research Center's (DFRC) Western Aeronautical Test Range (WATR) in dealing with the problems encountered while performing post flight data processing using the WATR's data collection/processing system on Chapter 10 files from different Chapter 10 recorders. The transition to Chapter 10 recorders has brought Vvith it an assortment of issues that must be addressed: the ambiguities of language in the Chapter 10 standard, the unrealistic near-term expectations of the Chapter 10 standard, the incompatibility of data products generated from Chapter 10 recorders, and the unavailability of mature Chapter 10 applications. Some of these issues properly belong to the users of Chapter 10 recorders, some to the manufacturers, and some to the flight test community at large. The goal of this presentation is to share the WATR's lesson learned in processing data products from various Chapter 10 recorder vendors. The WATR could benefit greatly in the open forum Vvith lessons learned discussions with other members of the flight test community.
The CAST GPS 4000 simulator can create scenarios using external trajectories. The following information must be provided: time from a given epoch (a constant sampling rate must be used); position, velocity and acceleration in Earth Centered Earth Fixed (ECEF) coordinates; elements of the matrix that transforms from the body-axis coordinate system to the ECEF frame; and the angular velocity of the body-axis system relative to ECEF coordinates. The initial latitude, longitude, altitude, and UTC time must also be provided during the scenario setup. The simulator recomputes the positions and velocities using the given accelerations and a constant jerk model. The results are the internal "truth file".
NASA is utilizing Global Hawk aircraft in high-altitude, long-duration Earth science missions. Communications with the onboard research equipment and sensors (the science payload) is via Ku-Band radio utilizing satellites in geostationary orbits. All payload communications use standard Internet Protocols and routing, and much of the data to be transferred is comprised of very large files. The science community is interested in fully utilizing these communication links to retrieve data as quickly and reliably as possible. A test bed was developed at NASA Ames to evaluate modern transport protocols as well as Protocol Enhancing Proxies (PEPs) to determine what tools best fit the needs of the science community. This paper describes the test bed used, the protocols, the PEPs that were evaluated, the particular tests performed and the results and conclusions.
This software provides the service-level functionality to manage the delivery of files from a lander mission repository to an orbiter mission repository for eventual spacelink relay by the orbiter asset on a specific communications pass. It provides further functions to deliver and track a set of mission-defined messages detailing lander authorization instructions and orbiter data delivery state. All of the information concerning these transactions is persisted in a database providing a high level of accountability of the forward-link relay process.
The second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) is a NASA atmospheric reanalysis that begins in 1980. It replaces the original MERRA reanalysis (Rienecker et al., 2011) using an upgraded version of the Goddard Earth Observing System Model, Version 5 (GEOS-5) data assimilation system. The file collections for MERRA-2 are described in detail in this document, including some important changes from those of the MERRA dataset (Lucchesi, 2012).
This document describes the gridded output files produced by the Goddard Earth Observing System version 5 (GEOS-5) Goddard Aerosol Assimilation System (GAAS) from July 2002 through December 2014. The MERRA Aerosol Reanalysis (MERRAero) is produced with the hydrostatic version of the GEOS-5 Atmospheric Global Climate Model (AGCM). In addition to standard meteorological parameters (wind, temperature, moisture, surface pressure), this simulation includes 15 aerosol tracers (dust, sea-salt, sulfate, black and organic carbon), ozone, carbon monoxide and carbon dioxide. This model simulation is driven by prescribed sea-surface temperature and sea-ice, daily volcanic and biomass burning emissions, as well as high-resolution inventories of anthropogenic emission sources. Meteorology is replayed from the MERRA Reanalysis.
Command File Errors (CFE) are managed using standard risk management approaches at the Jet Propulsion Laboratory. Over the last few years, more emphasis has been made on the collection, organization, and analysis of these errors for the purpose of reducing the CFE rates. More recently, probabilistic modeling techniques have been used for more in depth analysis of the perceived error rates of the DAWN mission and for managing the soft factors in the upcoming phases of the mission. We broadly classify the factors that can lead to CFE's as soft factors, which relate to the cognition of the operators and hard factors which relate to the Mission System which is composed of the hardware, software and procedures used for the generation, verification & validation and execution of commands. The focus of this paper is to use probabilistic models that represent multiple missions at JPL to determine the root cause and sensitivities of the various components of the mission system and develop recommendations and techniques for addressing them. The customization of these multi-mission models to a sample interplanetary spacecraft is done for this purpose.
Virtually all of the data distribution strategies being contemplated for the EOSDIS era revolve around the use of files.
Progress on NASA’s Safe and Precise Landing Integrated Capabilities Evolution (SPLICE) project continues, specifically with this development of the Descent and Landing Computer (DLC). One of the DLC’s primary contributions as a SPLICE technology is its implementation of algorithms and operation of sensors to autonomously guide a spacecraft in performing more precise and safer landings on celestial bodies such as the Moon and Mars [1]. The second iteration of the DLC is known as the Engineering Test Unit (ETU) and one of its desired functionalities is the ability to preserve the fidelity of the system’s boot file through the use of memory scrubbing [2]. The ETU has two primary boards, one for housing a Multi-Processor System on a Chip (MPSoC) and the other for housing a Xilinx Kintex Ultrascale FPGA*. To emulate a memory scrubbing function implemented on the ETU’s FPGA board, the design and testing of a software application was performed on a Xilinx KCU105 FPGA evaluation board. The memory scrubbing application had to meet certain key criteria such as (1) properly utilize with the flash memory’s Serial Peripheral Interface (SPI) to read, write, and erase flash memory properly, (2) be able to detect arbitrarily large or small amounts of bit-errors, (3) be able to correct all detected errors, and (4) perform memory scrubbing indefinitely and autonomously. A prototype implementation was constructed and tested, demonstrating successful detection and correction of bit errors in multiple configurations. In the form of burst errors or singular bit flips, and in amounts of errors ranging from one to fifteen (per 256 Bytes), the application was successful in preserving memory fidelity.
Progress on NASA’s Safe and Precise Landing Integrated Capabilities Evolution (SPLICE)project continues, specifically with this development of the Descent and Landing Computer(DLC). One of the DLC’s primary contributions as a SPLICE technology is its implementationof algorithms and operation of sensors to autonomously guide a spacecraft in performing moreprecise and safer landings on celestial bodies such as the Moon and Mars. The second iterationof the DLC is known as the Engineering Test Unit (ETU) and one of its desired functionalitiesis the ability to preserve the fidelity of the system’s boot file through the use of memoryscrubbing. The ETU has two primary boards, one for housing a Multi-Processor System ona Chip (MPSoC) and the other for housing a Xilinx Kintex Ultrascale FPGA3. To emulate amemory scrubbing function implemented on the ETU’s FPGA board, the design and testingof a software application was performed on a Xilinx KCU105 FPGA evaluation board. Thememory scrubbing application had to meet certain key criteria such as (1) properly utilize withthe flash memory’s Serial Peripheral Interface (SPI) to read, write, and erase flash memoryproperly, (2) be able to detect arbitrarily large or small amounts of bit-errors, (3) be able tocorrect all detected errors, and (4) perform memory scrubbing indefinitely and autonomously.A prototype implementation was constructed and tested, demonstrating successful detectionand correction of bit errors in multiple configurations. In the form of burst errors or singularbit flips, and in amounts of errors ranging from one to fifteen (per 256 Bytes), the applicationwas successful in preserving memory fidelity.
This document provides a brief description of the output collections from the MERRA-2 Stratospheric Composition Reanalysis of the Aura Microwave Limb Sounder (M2-SCREAM) produced at NASA’s Global Modeling and Assimilation Office. These data are generated by assimilating retrievals from the Microwave Limb Sounder (MLS) and the Ozone Monitoring Instrument (OMI) into the Global Earth Observing System (GEOS) Constituent Data Assimilation System (CoDAS) driven by meteorological fields from MERRA-2. M2-SCREAM assimilates hydrochloric acid (HCl), nitric acid (HNO3), stratospheric water vapor (H2O), nitrous oxide (N2O) and ozone with a system equipped with a version of the GEOS general circulation model and a stratospheric chemistry model, StratChem. Assimilated fields are provided globally at 0.5° by 0.625° resolution at three-hourly frequencies from 2004/09/01 to 2021. Assimilation uncertainties for each of the assimilated constituents are calculated from the CoDAS statistical output (Wargan et al., 2022) and provided as global full-resolution three-dimensional monthly files.
In order to improve the quality of geodetic results, we have developed an infrastructure for timely processing of telemetry from IVS observing stations. We check every hour for new log files with telemetry from both VLBI observing sessions, single dish experiments, and stow-in data collection and automatically process them. The telemetry data we use is the system temperature, phase calibration phases and amplitudes, system equivalent flux density, and the differences between formatter clock and GPS clock. For the system temperature and phase calibration, processing includes filtering out outliers and computing averages and rms of the scatter in each scan. Furthermore, for the phase calibration we also compute the group delay and detect spurious signals. Cleaned and post-processed telemetry is archived. Our process detects abnormalities, such as, anomalously high system temperature, unstable phase calibration phases, jumps in the GPS and formatter clock differences, and others. With our procedure, the latency of detection of station abnormalities is reduced to less than two hours. Early detection of abnormalities reduces the amount of affected data since station personnel get early alerts. We discuss our experience of running this system since 2022.
In order to improve the quality of geodetic results, we have developed an infrastructure for timely processing of telemetry from IVS observing stations. We check every hour for new log files with telemetry from both VLBI observing sessions, single dish experiments, and stow-in data collection and automatically process them. The telemetry data we use is the system temperature, phase calibration phases and amplitudes, system equivalent flux density, and the differences between formatter clock and GPS clock. For the system temperature and phase calibration, processing includes filtering out outliers and computing averages and rms of the scatter in each scan. Furthermore, for the phase calibration we also compute the group delay and detect spurious signals. Cleaned and post-processed telemetry is archived. Our process detects abnormalities, such as, anomalously high system temperature, unstable phase calibration phases, jumps in the GPS and formatter clock differences, and others. With our procedure, the latency of detection of station abnormalities is reduced to less than two hours. Early detection of abnormalities reduces the amount of affected data since station personnel get early alerts. We discuss our experience of running this system since 2022.
The use of proxy caches has been extensively studied in the HEP environment for efficient access of database data and showed significant performance with only very moderate operational effort at higher grid tiers (T2, T3). In this contribution we propose to apply the same concept to the area of file access and analyze the possible performance gains, operational impact on site services and applicability to different HEP use cases. Base on a proof-of-concept studies with a modified XROOT proxy server we review the cache efficiency and overheads for access patterns of typical ROOT based analysis programs. We conclude with a discussion of the potential role of this new component at the different tiers of a distributed computing grid.