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NASA NTRSDate not supplied

Tutorial on LuNaMaps Developed Tools andProcesses for Mapping the Lunar Surface

The main contribution of this project is the combined knowledge of terrain relative navigation experts and lunar scientists who are familiar with both the lunar orbital imagery and the instruments that collected the data as well as how a TRN system utilizes map data. This knowledge comes in the form of published technical papers, benchmark map data sets, and software tools that can help others automate the process of creating the necessary maps for their own landing sites in the future. This presentation provides a brief overview of the tools and processes developed by the project.

optical navigation↗

NASA NTRS1993

Results from the US/Russian Meteor-3/Total Ozone Mapping Spectrometer

The development of Meteor-3/TOMS (Total Ozone Mapping Spectrometer) was a joint project of the United States and Russia to fly a U.S. ozone measuring instrument (TOMS) onboard a Russian spacecraft (Meteor-3) and rocket (Cyclone), launched from Plesetsk, Russia. The Meteor-3/TOMS (M3TOMS) was launched into a 1202-km-high, near-polar orbit on 15 Aug. 1991, where it can obtain complete global coverage for most of each year. Both the U.S. and Russian sides have successfully received and processed data into ozone amounts from 25 Aug. 1991 to 1 Jun. 1992, and expect to continue for the life of the instrument and spacecraft. The successful development of the instrument hardware, spacecraft interface, data memory, telemetry systems, and software are described. Descriptions are given of the U.S. and Russian ground stations for receiving M3TOMS data. In addition, the data reduction software was independently developed by the U.S. and by the Russians, and is shown to agree to better than the precision of the measurements.

Herman, Jay R.↗

NASA NTRS1994

A versatile nondestructive evaluation imaging workstation

Ultrasonic C-scan and eddy current imaging systems are of the pointwise type evaluation systems that rely on a mechanical scanner to physically maneuver a probe relative to the specimen point by point in order to acquire data and generate images. Since the ultrasonic C-scan and eddy current imaging systems are based on the same mechanical scanning mechanisms, the two systems can be combined using the same PC platform with a common mechanical manipulation subsystem and integrated data acquisition software. Based on this concept, we have developed an IBM PC-based combined ultrasonic C-scan and eddy current imaging system. The system is modularized and provides capacity for future hardware and software expansions. Advantages associated with the combined system are: (1) eliminated duplication of the computer and mechanical hardware, (2) unified data acquisition, processing and storage software, (3) reduced setup time for repetitious ultrasonic and eddy current scans, and (4) improved system efficiency. The concept can be adapted to many engineering systems by integrating related PC-based instruments into one multipurpose workstation such as dispensing, machining, packaging, sorting, and other industrial applications.

Chern, E. James↗

NASA NTRS2006

Non Radiation Hardened Microprocessors in Spaced Based Remote Sensing Systems

The CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) mission is a comprehensive suite of active and passive sensors including a 20Hz 230mj Nd:YAG lidar, a visible wavelength Earth-looking camera and an imaging infrared radiometer. CALIPSO flies in formation with the Earth Observing System Post-Meridian (EOS PM) train, provides continuous, near-simultaneous measurements and is a planned 3 year mission. CALIPSO was launched into a 98 degree sun synchronous Earth orbit in April of 2006 to study clouds and aerosols and acquires over 5 gigabytes of data every 24 hours. The ground track of one CALIPSO orbit as well as high and low intensity South Atlantic Anomaly outlines is shown. CALIPSO passes through the SAA several times each day. Spaced based remote sensing systems that include multiple instruments and/or instruments such as lidar generate large volumes of data and require robust real-time hardware and software mechanisms and high throughput processors. Due to onboard storage restrictions and telemetry downlink limitations these systems must pre-process and reduce the data before sending it to the ground. This onboard processing and realtime requirement load may mean that newer more powerful processors are needed even though acceptable radiation-hardened versions have not yet been released. CALIPSO's single board computer payload controller processor is actually a set of four (4) voting non-radiation hardened COTS Power PC 603r's built on a single width VME card by General Dynamics Advanced Information Systems (GDAIS). Significant radiation concerns for CALIPSO and other Low Earth Orbit (LEO) satellites include the South Atlantic Anomaly (SAA), the north and south poles and strong solar events. Over much of South America and extending into the South Atlantic Ocean the Van Allen radiation belts dip to just 200-800km and spacecraft entering this area are subjected to high energy protons and experience higher than normal Single Event Upset (SEU) and Single Event Latch-up (SEL) rates. Although less significant, spacecraft flying in the area around the poles experience similar upsets. Finally, powerful solar proton events in the range of 10MeV/10pfu to 100MeV/1pfu as are forecasted and tracked by NOAA's Space Environment Center in Colorado can result in Single Event Upset (SEU), Single Event Latch-up (SEL) and permanent failures such as Single Event Gate Rupture (SEGR) in some technologies. (Galactic Cosmic Rays (GCRs) are another source, especially for gate rupture) CALIPSO mitigates common radiation concerns in its data handling through the use of redundant processors, radiation-hardened Application Specific Integrated Circuits (ASIC), hardware-based Error Detection and Correction (EDAC), processor and memory scrubbing, redundant boot code and mirrored files. After presenting a system overview this paper will expand on each of these strategies. Where applicable, related on-orbit data collected since the CALIPSO initial boot on May 4, 2006 will be noted.

Decoursey, Robert J.↗

NASA NTRS2018

GMI-IPS: Python Processing Software for Aircraft Campaigns

NASA's Atmospheric Tomography Mission (ATom) seeks to understand the impact of anthropogenic air pollution on gases in the Earth's atmosphere. Four flight campaigns are being deployed on a seasonal basis to establish a continuous global-scale data set intended to improve the representation of chemically reactive gases in global atmospheric chemistry models. The Global Modeling Initiative (GMI), is creating chemical transport simulations on a global scale for each of the ATom flight campaigns. To meet the computational demands required to translate the GMI simulation data to grids associated with the flights from the ATom campaigns, the GMI ICARTT Processing Software (GMI-IPS) has been developed and is providing key functionality for data processing and analysis in this ongoing effort. The GMI-IPS is written in Python and provides computational kernels for data interpolation and visualization tasks on GMI simulation data. A key feature of the GMI-IPS, is its ability to read ICARTT files, a text-based file format for airborne instrument data, and extract the required flight information that defines regional and temporal grid parameters associated with an ATom flight. Perhaps most importantly, the GMI-IPS creates ICARTT files containing GMI simulated data, which are used in collaboration with ATom instrument teams and other modeling groups. The initial main task of the GMI-IPS is to interpolate GMI model data to the finer temporal resolution (1-10 seconds) of a given flight. The model data includes basic fields such as temperature and pressure, but the main focus of this effort is to provide species concentrations of chemical gases for ATom flights. The software, which uses parallel computation techniques for data intensive tasks, linearly interpolates each of the model fields to the time resolution of the flight. The temporally interpolated data is then saved to disk, and is used to create additional derived quantities. In order to translate the GMI model data to the spatial grid of the flight path as defined by the pressure, latitude, and longitude points at each flight time record, a weighted average is then calculated from the nearest neighbors in two dimensions (latitude, longitude). Using SciPya's Regular Grid Interpolator, interpolation functions are generated for the GMI model grid and the calculated weighted averages. The flight path points are then extracted from the ATom ICARTT instrument file, and are sent to the multi-dimensional interpolating functions to generate GMI field quantities along the spatial path of the flight. The interpolated field quantities are then written to a ICARTT data file, which is stored for further manipulation. The GMI-IPS is aware of a generic ATom ICARTT header format, containing basic information for all flight campaigns. The GMI-IPS includes logic to edit metadata for the derived field quantities, as well as modify the generic header data such as processing dates and associated instrument files. The ICARTT interpolated data is then appended to the modified header data, and the ICARTT processing is complete for the given flight and ready for collaboration. The output ICARTT data adheres to the ICARTT file format standards V1.1. The visualization component of the GMI-IPS uses Matplotlib extensively and has several functions ranging in complexity. First, it creates a model background curtain for the flight (time versus model eta levels) with the interpolated flight data superimposed on the curtain. Secondly, it creates a time-series plot of the interpolated flight data. Lastly, the visualization component creates averaged 2D model slices (longitude versus latitude) with overlaid flight track circles at key pressure levels. The GMI-IPS consists of a handful of classes and supporting functionality that have been generalized to be compatible with any ICARTT file that adheres to the base class definition. The base class represents a generic ICARTT entry, only defining a single time entry and 3D spatial positioning parameters. Other classes inherit from this base class; several classes for input ICARTT instrument files, which contain the necessary flight positioning information as a basis for data processing, as well as other classes for output ICARTT files, which contain the interpolated model data. Utility classes provide functionality for routine procedures such as: comparing field names among ICARTT files, reading ICARTT entries from a data file and storing them in data structures, and returning a reduced spatial grid based on a collection of ICARTT entries. Although the GMI-IPS is compatible with GMI model data, it can be adapted with reasonable effort for any simulation that creates Hierarchical Data Format (HDF) files. The same can be said of its adaptability to ICARTT files outside of the context of the ATom mission. The GMI-IPS contains just under 30,000 lines of code, eight classes, and a dozen drivers and utility programs. It is maintained with GIT source code management and has been used to deliver processed GMI model data for the ATom campaigns that have taken place to date.

Damon, M. R.↗

NASA NTRS2002

Systems Architecture for Fully Autonomous Space Missions

The NASA Goddard Space Flight Center is working to develop a revolutionary new system architecture concept in support of fully autonomous missions. As part of GSFC's contribution to the New Millenium Program (NMP) Space Technology 7 Autonomy and on-Board Processing (ST7-A) Concept Definition Study, the system incorporates the latest commercial Internet and software development ideas and extends them into NASA ground and space segment architectures. The unique challenges facing the exploration of remote and inaccessible locales and the need to incorporate corresponding autonomy technologies within reasonable cost necessitate the re-thinking of traditional mission architectures. A measure of the resiliency of this architecture in its application to a broad range of future autonomy missions will depend on its effectiveness in leveraging from commercial tools developed for the personal computer and Internet markets. Specialized test stations and supporting software come to past as spacecraft take advantage of the extensive tools and research investments of billion-dollar commercial ventures. The projected improvements of the Internet and supporting infrastructure go hand-in-hand with market pressures that provide continuity in research. By taking advantage of consumer-oriented methods and processes, space-flight missions will continue to leverage on investments tailored to provide better services at reduced cost. The application of ground and space segment architectures each based on Local Area Networks (LAN), the use of personal computer-based operating systems, and the execution of activities and operations through a Wide Area Network (Internet) enable a revolution in spacecraft mission formulation, implementation, and flight operations. Hardware and software design, development, integration, test, and flight operations are all tied-in closely to a common thread that enables the smooth transitioning between program phases. The application of commercial software development techniques lays the foundation for delivery of product-oriented flight software modules and models. Software can then be readily applied to support the on-board autonomy required for mission self-management. An on-board intelligent system, based on advanced scripting languages, facilitates the mission autonomy required to offload ground system resources, and enables the spacecraft to manage itself safely through an efficient and effective process of reactive planning, science data acquisition, synthesis, and transmission to the ground. Autonomous ground systems in turn coordinate and support schedule contact times with the spacecraft. Specific autonomy software modules on-board include mission and science planners, instrument and subsystem control, and fault tolerance response software, all residing within a distributed computing environment supported through the flight LAN. Autonomy also requires the minimization of human intervention between users on the ground and the spacecraft, and hence calls for the elimination of the traditional operations control center as a funnel for data manipulation. Basic goal-oriented commands are sent directly from the user to the spacecraft through a distributed internet-based payload operations "center". The ensuing architecture calls for the use of spacecraft as point extensions on the Internet. This paper will detail the system architecture implementation chosen to enable cost-effective autonomous missions with applicability to a broad range of conditions. It will define the structure needed for implementation of such missions, including software and hardware infrastructures. The overall architecture is then laid out as a common thread in the mission life cycle from formulation through implementation and flight operations.

Esper, Jamie↗

NASA NTRS2003

TOPEX Software Document Series: Rev. 1 - Volume 5

This document is a compendium of the WFF TOPEX Software Development Team's knowledge regarding Geophysical Data Record (GDR) Processing. It includes many elements of a requirements document, a software specification document, a software design document, and a user's manual. In the more technical sections, this document assumes the reader is familiar with TOPEX and instrument files.

Lee, Jeffrey↗

NASA NTRS2003

TOPEX SDR Processing, October 1998

This document is a compendium of the WFF TOPEX Software Development Team's knowledge regarding Sensor Data Record (SDR) Processing. It includes many elements of a requirements document, a software specification document, a software design document, and a user's manual. In the more technical sections, this document assumes the reader is familiar with TOPEX and instrument files.

Lee, Jeffrey E.↗

DOE OSTI2021

Tools for supporting solution scattering during the COVID-19 pandemic

During the COVID-19 pandemic, synchrotron beamlines were forced to limit user access. Performing routine measurements became a challenge. At the Life Science X-ray Scattering (LiX) beamline, new instrumentation and mail-in protocols have been developed to remove the access barrier to solution scattering measurements. Our efforts took advantage of existing instrumentation and coincided with the larger effort at NSLS-II to support remote measurements. Given the limited staff–user interaction for mail-in measurements, additional software tools have been developed to ensure data quality, to automate the adjustments in data processing, as users would otherwise rely on the experience of the beamline staff, and produce a summary of the initial assessments of the data. This report describes the details of these developments.

99 GENERAL AND MISCELLANEOUS↗

NASA NTRS1983

Digital Instrumentation Analysis and Navigation System (DIANS) for system identification

Hardware, software, and performance features of the Digital Instrumentation and Navigation System (DIANS) designed for NASA research to collect flight data as a strap-down system are detailed. The support software for the system has a cross compiler, a linkage editor, and cross assembler, extended communication capabilities, postflight processing applications, and compilers for PASCAL, FORTRAN, CBASIC and MT. The DIANS microcomputer has a 1 Mbyte RAM module, a fast floating point processor board, a 68000 monoboard computer with 64 RAM, a 128 Kbyte bubble memory card, and a navigation radio. The system also carries a battery for full system operation for over an hour. The support software is also stored on a host mainframe computer, which has a CP/M operating system. Pitch, roll, and heading data are gathered from the on-board system, and communication is possible between the airborne and ground-based computer.

Smyth, R. K.↗

NASA NTRS1999

Polar Magnetic Field Experiment

This grant covers the initial data reduction and analysis of the magnetic field measurements of the Polar spacecraft. At this writing data for the first three years of the mission have been processed and deposited in the key parameter database. These data are also available in a variety of time resolutions and coordinate systems via a webserver at UCLA that provides both plots and digital data. The flight software has twice been reprogrammed: once to remove a glitch in the data where there were rare collisions between commands in the central processing unit and once to provide burst mode data at 100 samples per second on a regular basis. The instrument continues to function as described in the instrument paper (1.1 in the bibliography attached below). The early observations were compared with observations on the same field lines at lower altitude. The polar magnetic measurements also proved to be most useful for testing the accuracy of MHD models. WE also made important contributions to study of waves and turbulence.

Russell, C. T.↗

DOE OSTI2021

A Preprocessing Tool for Enhanced Ion Mobility–Mass Spectrometry-Based Omics Workflows

The ability to improve the data quality of ion mobility–mass spectrometry (IM-MS) measurements is of great importance for enabling modular and efficient computational workflows and gaining better qualitative and quantitative insights from complex biological and environmental samples. We developed the PNNL PreProcessor, a standalone and user-friendly software housing various algorithmic implementations to generate new MS-files with enhanced signal quality and in the same instrument format. Different experimental approaches are supported for IM-MS based on Drift-Tube (DT) and Structures for Lossless Ion Manipulations (SLIM), including liquid chromatography (LC) and infusion analyses. The algorithms extend the dynamic range of the detection system, while reducing file sizes for faster and memory-efficient downstream processing. Specifically, multidimensional smoothing improves peak shapes of poorly defined low-abundance signals, and saturation repair reconstructs the intensity profile of high-abundance peaks from various analyte types. Further, other functionalities are data compression and interpolation, IM demultiplexing, noise filtering by low intensity threshold and spike removal, and exporting of acquisition metadata. Several advantages of the tool are illustrated, including an increase of 19.4% in lipid annotations and a two-times faster processing of LC-DT IM-MS data-independent acquisition spectra from a complex lipid extract of a standard human plasma sample. The software is freely available at https://omics.pnl.gov/software/pnnl-preprocessor.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRSDate not supplied

L'Ralph's Advanced Thermal Model Correlation Using Veritrek

Thermal model correlation uses data from thermal balance tests to better estimate uncertain input parameter values. During the correlation process, input parameters are modified in an iterative manner which can become computationally expensive since this requires that the high-fidelity thermal model be run for each iteration. Depending on the number of thermal balance test points there can be many sets of correlation parameters that satisfy correlation criteria; and having enough data to ascertain the best set of correlation parameters to use, further increases the computational expense. Reduced-order models (ROMs) provide computationally efficient surrogates of high-fidelity models and are often built to reduce development cycle times and cost. By leveraging the speed of reduced-order models and the Correlation Analysis feature in the Veritrek software, the typical computational expense of a traditional thermal model correlation process can be significantly reduced and having access to hundreds of thousands of iteration results provides an advanced means of intelligently determining the best set of correlation parameters to use. The L’Ralph thermal team at NASA Goddard Space Flight Center explored the use of the Veritrek software for their thermal model correlation efforts. The ROM that was created allowed for the variation of 15 input parameters to match 70 temperature sensor readouts from 3 thermal balance plateus and required 125 runs of the high-fidelity Thermal Desktop® model to generate a ROM that could predict the detailed model’s results to within 0.2 K (RMS). The ROM was then used to find dozens of plausible correlation parameter values based on L’Ralph instrument test data within a few seconds. By providing several plausible correlation parameter combinations, Veritrek allowed the thermal team to explore different uncertain parameter value combinations and provided insight into how deterministic each input parameter was. This allowed for a more confident decision on the best set of correlation parameters to use, compared to traditional model correlation techniques. In this presentation, the L’Ralph thermal team will be presenting their experience with the Veritrek software and how the software was utilized to provide additional insights during the correlation process.

Daniel Bae↗

NASA NTRSDate not supplied

L'Ralph's Advanced Thermal Model Correlation Using Veritrek

Daniel Bae↗

DOE OSTI2020

Methods and Experiences for Developing Abstractions for Data-intensive, Scientific Applications

Developing software for scientific applications that require the integration of diverse types of computing, instruments, and data present challenges that are distinct from commercial software. These applications require scale, and the need to integrate various programming and computational models with evolving and heterogeneous infrastructure. Pervasive and effective abstractions for distributed infrastructures are thus critical; however, the process of developing abstractions for scientific applications and infrastructures is not well understood. While theory-based approaches for system development are suited for well-defined, closed environments, they have severe limitations for designing abstractions for scientific systems and applications. The design science research (DSR) method provides the basis for designing practical systems that can handle real-world complexities at all levels. In contrast to theory-centric approaches, DSR emphasizes both practical relevance and knowledge creation by building and rigorously evaluating all artifacts. In this work, we show how DSR provides a well-defined framework for developing abstractions and middleware systems for distributed systems. Specifically, we address the critical problem of distributed resource management on heterogeneous infrastructure over a dynamic range of scales, a challenge that currently limits many scientific applications. We use the pilot-abstraction, a widely used resource management abstraction for high-performance, high throughput, big data, and streaming applications, as a case study for evaluating the DSR activities. For this purpose, we analyze the research process and artifacts produced during the design and evaluation of the pilot-abstraction. We find DSR provides a concise framework for iteratively designing and evaluating systems. Finally, we capture our experiences and formulate different lessons learned.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1995

Software For Diagnosis Of Parallel Processing

Ames Instrumentation System (AIMS) computer program package of software tools measuring and analyzing performances of parallel-processing application programs. Helps programmer to debug and refine, and to monitor and visualize execution of, parallel-processing application software for Intel iPSC/860 (or equivalent) multicomputer. Performance data collected displayed graphically on computer workstations supporting X-Windows.

Hontalas, Philip↗

NASA NTRS2011

Telemetry and Science Data Software System

The Telemetry and Science Data Software System (TSDSS) was designed to validate the operational health of a spacecraft, ease test verification, assist in debugging system anomalies, and provide trending data and advanced science analysis. In doing so, the system parses, processes, and organizes raw data from the Aquarius instrument both on the ground and while in space. In addition, it provides a user-friendly telemetry viewer, and an instant pushbutton test report generator. Existing ground data systems can parse and provide simple data processing, but have limitations in advanced science analysis and instant report generation. The TSDSS functions as an offline data analysis system during I&T (integration and test) and mission operations phases. After raw data are downloaded from an instrument, TSDSS ingests the data files, parses, converts telemetry to engineering units, and applies advanced algorithms to produce science level 0, 1, and 2 data products. Meanwhile, it automatically schedules upload of the raw data to a remote server and archives all intermediate and final values in a MySQL database in time order. All data saved in the system can be straightforwardly retrieved, exported, and migrated. Using TSDSS s interactive data visualization tool, a user can conveniently choose any combination and mathematical computation of interesting telemetry points from a large range of time periods (life cycle of mission ground data and mission operations testing), and display a graphical and statistical view of the data. With this graphical user interface (GUI), the data queried graphs can be exported and saved in multiple formats. This GUI is especially useful in trending data analysis, debugging anomalies, and advanced data analysis. At the request of the user, mission-specific instrument performance assessment reports can be generated with a simple click of a button on the GUI. From instrument level to observatory level, the TSDSS has been operating supporting functional and performance tests and refining system calibration algorithms and coefficients, in sync with the Aquarius/SAC-D spacecraft. At the time of this reporting, it was prepared and set up to perform anomaly investigation for mission operations preceding the Aquarius/SAC-D spacecraft launch on June 10, 2011.

Bates, Lakesha↗

NASA NTRS2014

GPU Lossless Hyperspectral Data Compression System

Hyperspectral imaging systems onboard aircraft or spacecraft can acquire large amounts of data, putting a strain on limited downlink and storage resources. Onboard data compression can mitigate this problem but may require a system capable of a high throughput. In order to achieve a high throughput with a software compressor, a graphics processing unit (GPU) implementation of a compressor was developed targeting the current state-of-the-art GPUs from NVIDIA(R). The implementation is based on the fast lossless (FL) compression algorithm reported in "Fast Lossless Compression of Multispectral-Image Data" (NPO- 42517), NASA Tech Briefs, Vol. 30, No. 8 (August 2006), page 26, which operates on hyperspectral data and achieves excellent compression performance while having low complexity. The FL compressor uses an adaptive filtering method and achieves state-of-the-art performance in both compression effectiveness and low complexity. The new Consultative Committee for Space Data Systems (CCSDS) Standard for Lossless Multispectral & Hyperspectral image compression (CCSDS 123) is based on the FL compressor. The software makes use of the highly-parallel processing capability of GPUs to achieve a throughput at least six times higher than that of a software implementation running on a single-core CPU. This implementation provides a practical real-time solution for compression of data from airborne hyperspectral instruments.

Aranki, Nazeeh I.↗