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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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At least 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Numerical Modeling of an Integrated Vehicle Fluids System Loop for Pressurizing a Cryogenic Tank

This paper presents a numerical model of the pressurization loop of the Integrated Vehicle Fluids (IVF) system using the Generalized Fluid System Simulation Program (GFSSP). The IVF propulsion system, being developed by United Launch Alliance to reduce system weight and enhance reliability, uses boiloff propellants to drive thrusters for the reaction control system as well as to run internal combustion engines to develop power and drive compressors to pressurize propellant tanks. NASA Marshall Space Flight Center (MSFC) conducted tests to verify the functioning of the IVF system using a flight-like tank. GFSSP, a finite volume based flow network analysis software developed at MSFC, has been used to support the test program. This paper presents the simulation of three different test series, comparison of numerical prediction and test data and a novel method of presenting data in a dimensionless form. The paper also presents a methodology of implementing a compressor map in a system level code.

LeClair, A. C.↗
NASA NTRS1990

Evaluation of the Trajectory Operations Applications Software Task (TOAST). Volume 2: Interview transcripts

The Trajectory Operations Applications Software Task (TOAST) is a software development project whose purpose is to provide trajectory operation pre-mission and real-time support for the Space Shuttle. The purpose of the evaluation was to evaluate TOAST as an Application Manager - to assess current and planned capabilities, compare capabilities to commercially-available off the shelf (COTS) software, and analyze requirements of MCC and Flight Analysis Design System (FADS) for TOAST implementation. As a major part of the data gathering for the evaluation, interviews were conducted with NASA and contractor personnel. Real-time and flight design users, orbit navigation users, the TOAST developers, and management were interviewed. Code reviews and demonstrations were also held. Each of these interviews was videotaped and transcribed as appropriate. Transcripts were edited and are presented chronologically.

Perkins, Sharon↗
NASA NTRS1992

The Software Engineering Laboratory: An operational software experience factory

For 15 years, the Software Engineering Laboratory (SEL) has been carrying out studies and experiments for the purpose of understanding, assessing, and improving software and software processes within a production software development environment at NASA/GSFC. The SEL comprises three major organizations: (1) NASA/GSFC, Flight Dynamics Division; (2) University of Maryland, Department of Computer Science; and (3) Computer Sciences Corporation, Flight Dynamics Technology Group. These organizations have jointly carried out several hundred software studies, producing hundreds of reports, papers, and documents, all of which describe some aspect of the software engineering technology that was analyzed in the flight dynamics environment at NASA. The studies range from small, controlled experiments (such as analyzing the effectiveness of code reading versus that of functional testing) to large, multiple project studies (such as assessing the impacts of Ada on a production environment). The organization's driving goal is to improve the software process continually, so that sustained improvement may be observed in the resulting products. This paper discusses the SEL as a functioning example of an operational software experience factory and summarizes the characteristics of and major lessons learned from 15 years of SEL operations.

Basili, Victor R.↗
NASA NTRS1996

Parallelization and Algorithmic Enhancements of High Resolution IRAS Image Construction

The Infrared Astronomical Satellite caried out a nearly complete survey of the infrared sky, and the survey data are important for the study of many astrophysical phenomena. However, many data sets at other wavelengths have higher resolutions than that of the co-added IRAS maps, and high resolution IRAS images are strongly desired both for their own information content and their usefulness in correlation. The HIRES program was developed by the Infrared Processing and Analysis Center (IPAC) to produce high resolution (approx. 1') images from IRAS data using the Maximum Correlation Method (MCM). We describe the port of HIRES to the Intel Paragon, a massively parallel supercomputer, other software developments for mass production of HIRES images, and the IRAS Galaxy Atlas, a project to map the Galactic plane at 60 and 100(micro)m.

Satellite infrared IRAS IRAS maps IRAS images↗
NASA NTRSDate not supplied

Introduction to Quantum Computing

Quantum computing offers the potential to revolutionize high-performance computing by providing a means to solve certain computational problems asymptotically faster than any classical computer. Quantum computing has advanced recently from merely a theoretical possibility to engineered reality, including commercial entities offering early prototype quantum processors, both special-purpose quantum annealers and general-purpose gate-model processors. The media have been showcasing each new development and implicitly conveying the message that quantum-computing ubiquity is nigh. Here, we will respond to this hype and provide an overview of the exciting but still early state of the field. In this tutorial, we introduce participants to the computational models that give quantum computing its immense computational power. We examine the thought processes that programmers need to map problems to quantum computers. And we discuss hardware and algorithmic challenges that must be overcome before quantum computing becomes a component of every software developer's repertoire.

Quantum computing↗
NASA NTRS2020

RMIT AR Android Application Abstract

This summer, I've worked as an intern for IT-C1's Rapid Model Import Tool (RMIT) project under Bill Little. The goal of this project was to develop a mobile application for IT-C1's larger project, RMIT, so that it could be deployed in a convenient way. The current function of RMIT is to import file types that are not normally compatible with the Unity 3D software development engine and make them into files that can be placed into Unity for the specific purpose of viewing CAD models in virtual reality (VR). The mobile application that I worked on uses augmented reality (AR), using the camera on a mobile device, to show virtual models in the real world for the purpose of visualization and understanding. In addition to single-player capabilities, this application will include a multi-player mode so that collaborating engineers can see each other's work on their own devices.Working on this application required many steps. First, I hard to learn a lot about how mobile development is different from desktop development, and what the limitations of augmented reality are at its current state. From there, I was assigned new tasks and goals every two weeks, which included addingground plane and air plane functionality, designing a user interface, adding multi-player capability and allowing the user to manipulate models placed in a scene.

Dorian Thompson↗
NASA NTRSDate not supplied

A Survey of ISS and Visiting Vehicle Returned Surfaces for Environmental Characterization and Computer Model Development

The Orbital Debris Engineering Model (ORDEM) developed by the NASA Orbital Debris Program Office (ODPO) is a data-driven model — extensive radar, optical, laboratory, and in situ measurement data sets have been used to build the model since its earliest versions. A salient aspect of professional software development is the verification and validation (V&V) process. Verification answers the question “Is the model built correctly?” while validation addresses the question “Did we build the correct model?” Less extensive, reserved, or independent data sets serve the validation requirement. Due to the dynamic nature of the orbital debris environment, it is critical to use contemporaneous data sources that represent the current environment to support ORDEM development and validation. ORDEM has utilized in situ data collected from Space Shuttle and Hubble Space Telescope surface inspections, now over a decade old. This historical dataset is fundamental for providing baseline in situ measurement data for sizes between 10 to 300 microns, but new data sources are being evaluated using returned surfaces from or near the International Space Station (ISS). This paper reviews a general microscopic survey of ISS soft goods, the Pressurized Mating Adapter 2 (PMA-2) blanket, and a limited-scope feasibility study conducted on the Space Exploration Technologies Corporation (SpaceX) Dragon capsule’s Thermal Protection System (TPS) material. The PMA-2 blanket, exposed to the space environment between 09 July 2013 and 25 February 2015, is an approximately 3.7 m2-area blanket composed of a betacloth outer layer and multiple ballistic fabric inner layers. The SpaceX Cargo Dragon capsule regularly visited the ISS from 2012 through 2020 and potentially provides a timely and well-characterized source of data for modeling purposes. The capsule’s lateral surfaces use SpaceX Proprietary Ablative Material (SPAM) TPS material, a syntactic foam, for thermal management during all mission phases. Seven SPAM extracted samples have been analyzed to date. This paper will provide an overview of the characterization completed for impact features by size, depth, impactor diameter, and the impactor residues chemical analyses, allowing a differentiation between micrometeoroids and orbital debris and a categorization by mass density and density class. Impactor diameter is estimated using damage equations generated from ground-based hypervelocity impact testing. The orbital debris impactors are compared to the current ORDEM 3.2 model of the environment at ISS altitudes. We briefly discuss the meteoroid impactors, including constituents and mass densities, in the general context of current models.

Phillip Anz-meador↗
NASA NTRSDate not supplied

A Survey of ISS and Visiting Vehicle Returned Surfaces for Environmental Characterization and Computer Model Development

The Orbital Debris Engineering Model (ORDEM) developed by the NASA Orbital Debris Program Office (ODPO) is a data-driven model — extensive radar, optical, laboratory, and in situ measurement data sets have been used to build the model since its earliest versions. A salient aspect of professional software development is the verification and validation (V&V) process. Verification answers the question “Is the model built correctly?” while validation addresses the question “Did we build the correct model?” Less extensive, reserved, or independent data sets serve the validation requirement. Due to the dynamic nature of the orbital debris environment, it is critical to use contemporaneous data sources that represent the current environment to support ORDEM development and validation. ORDEM has utilized in situ data collected from Space Shuttle and Hubble Space Telescope surface inspections, now over a decade old. This historical dataset is fundamental for providing baseline in situ measurement data for sizes between 10 to 300 microns, but new data sources are being evaluated using returned surfaces from or near the International Space Station (ISS). This paper reviews a general microscopic survey of ISS soft goods, the Pressurized Mating Adapter 2 (PMA-2) blanket, and a limited-scope feasibility study conducted on the Space Exploration Technologies Corporation (SpaceX) Dragon capsule’s Thermal Protection System (TPS) material. The PMA-2 blanket, exposed to the space environment between 09 July 2013 and 25 February 2015, is an approximately 3.7 m2-area blanket composed of a betacloth outer layer and multiple ballistic fabric inner layers. The SpaceX Cargo Dragon capsule regularly visited the ISS from 2012 through 2020 and potentially provides a timely and well-characterized source of data for modeling purposes. The capsule’s lateral surfaces use SpaceX Proprietary Ablative Material (SPAM) TPS material, a syntactic foam, for thermal management during all mission phases. Seven SPAM extracted samples have been analyzed to date. This paper will provide an overview of the characterization completed for impact features by size, depth, impactor diameter, and the impactor residues chemical analyses, allowing a differentiation between micrometeoroids and orbital debris and a categorization by mass density and density class. Impactor diameter is estimated using damage equations generated from ground-based hypervelocity impact testing. The orbital debris impactors are compared to the current ORDEM 3.2 model of the environment at ISS altitudes. We briefly discuss the meteoroid impactors, including constituents and mass densities, in the general context of current models.

Phillip Anz-Meador↗
NASA NTRS1987

Structured Data in Structural Analysis Software

This paper discusses the use of computer data structures in finite-element structural analysis programs. A number of data structure types that have been shown to be useful in such programs are introduced and described. A simple finite-element model is used to demonstrate how the given set of data structure types naturally lend themselves to developing software for the model. Different methods of implementing data structures in the context of a program are discussed.

Kunz, Donald L.↗
NASA NTRS1981

Guide to data collection

Guidelines and recommendations are presented for the collection of software development data. Motivation and planning for, and implementation and management of, a data collection effort are discussed. Topics covered include types, sources, and availability of data; methods and costs of data collection; types of analyses supported; and warnings and suggestions based on software engineering laboratory (SEL) experiences. This document is intended as a practical guide for software managers and engineers, abstracted and generalized from 5 years of SEL data collection.

Source record↗
NASA NTRS1997

A Case Study of 4 & 5 Cost Effectiveness

This paper looks at the Independent Verification and Validation (IV&V) of NASA's Space Shuttle Day of Launch I-Load Update (DoLILU) project. IV&V is defined. The system's development life cycle is explained. Data collection and analysis are described. DoLILU Issue Tracking Reports (DITRs) authored by IV&V personnel are analyzed to determine the effectiveness of IV&V in finding errors before the code, testing, and integration phase of the software development life cycle. The study's findings are reported along with the limitations of the study and planned future research.

Neal, Ralph D.↗
NASA NTRS1977

Implementation of a maximum likelihood convolutional decoder in the DSN

The development status of the decoder and the factors which were considered in defining the specific functional requirements are described. The design is discussed to the block diagram level. A description of the detailed design is provided, along with a description of the test software developed and a brief summary of the performance evaluation testing completed so far.

Alberda, M. E.↗
NASA NTRS2016

Leadership Development Program Final Project

TOSC is NASA's prime contractor tasked to successfully assemble, test, and launch the EM1 spacecraft. TOSC success is highly dependent on design products from the other NASA Programs manufacturing and delivering the flight hardware; Space Launch System(SLS) and Multi-Purpose Crew Vehicle(MPCV). Design products directly feed into TOSC's: Procedures, Personnel training, Hardware assembly, Software development, Integrated vehicle test and checkout, Launch. TOSC senior management recognized a significant schedule risk as these products are still being developed by the other two (2) programs; SVE and ACE positions were created.

Design products required for Engineering↗
NASA NTRS2004

Integrated Control Modeling for Propulsion Systems Using NPSS

The Numerical Propulsion System Simulation (NPSS), an advanced engineering simulation environment used to design and analyze aircraft engines, has been enhanced by integrating control development tools into it. One of these tools is a generic controller interface that allows NPSS to communicate with control development software environments such as MATLAB and EASY5. The other tool is a linear model generator (LMG) that gives NPSS the ability to generate linear, time-invariant state-space models. Integrating these tools into NPSS enables it to be used for control system development. This paper will discuss the development and integration of these tools into NPSS. In addition, it will show a comparison of transient model results of a generic, dual-spool, military-type engine model that has been implemented in NPSS and Simulink. It will also show the linear model generator s ability to approximate the dynamics of a nonlinear NPSS engine model.

Parker, Khary I.↗
NASA NTRS2004

Software for Generating Strip Maps from SAR Data

Jurassicprok is a computer program that generates strip-map digital elevation models and other data products from raw data acquired by an airborne synthetic-aperture radar (SAR) system. This software can process data from a variety of airborne SAR systems but is designed especially for the GeoSAR system, which is a dual-frequency (P- and X-band), single-pass interferometric SAR system for measuring elevation both at the bare ground surface and top of the vegetation canopy. Jurassicprok is a modified version of software developed previously for airborne-interferometric- SAR applications. The modifications were made to accommodate P-band interferometric processing, remove approximations that are not generally valid, and reduce processor-induced mapping errors to the centimeter level. Major additions and other improvements over the prior software include the following: a) A new, highly efficient multi-stage-modified wave-domain processing algorithm for accurately motion compensating ultra-wideband data; b) Adaptive regridding algorithms based on estimated noise and actual measured topography to reduce noise while maintaining spatial resolution; c) Exact expressions for height determination from interferogram data; d) Fully calibrated volumetric correlation data based on rigorous removal of geometric and signal-to-noise decorrelation terms; e) Strip range-Doppler image output in user-specified Doppler coordinates; f) An improved phase-unwrapping and absolute-phase-determination algorithm; g) A more flexible user interface with many additional processing options; h) Increased interferogram filtering options; and i) Ability to use disk space instead of random- access memory for some processing steps.

Hensley, Scott↗
NASA NTRS2020

Integration Test and Evaluation (IT&E) Flight Test Series 6 Live Virtual Constructive - Distributed Environment (LVC-DE) Test Report

The goals of the Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) (also UAS-NAS) Project are to reduce the barriers for UAS access and its integration into the NAS. The UAS-NAS project and industry stakeholders conducted a series of flight tests integrating technologies from the Modeling & Simulation (M&S), Human Systems Integration (HSI), and Communication and Control (C2), and Integration, Test & Evaluation (IT&E) research areas. The last of the flight test series, Flight Test Series 6 (FT6) was conducted in late 2019 and focused on evaluating the interaction of the airborne non-cooperative surveillance system and the Detect and Avoid (DAA) technology. The DAA system generated conflict alert and guidance for pilots using a Research Ground Control System (RGCS) to avoid intruder aircraft. The conflict alerting and guidance information was presented on the RGCS’s display using symbology developed by the human factors team. The objective of FT6 was to investigate the interoperability of Low Size, Weight, and Power (Low SWaP) sensors with the DAA alerting, guidance, and display requirements. To support this goal, the distributed test environments (DTE) were developed at Ames Research Center (ARC) and Armstrong Flight Research Center (AFRC) and securely linked over a Virtual Private Network (VPN). These environments took advantage of existing Live Virtual Constructive (LVC) technologies to support research observation at both Centers with the insertion of live UAS and manned intruder aircraft into a simulated NAS environment with Air Traffic Control (ATC) and constructive manned aircraft. The experiment was distributed between AFRC flight operations and research facilities and the Distributed Simulation Research Laboratory (DSRL) and Software Development Laboratory (SDL) in building N243 at ARC. The Air Traffic Controller and pseudo pilots operated from the DSRL and SDL, respectively, using the Multi-Aircraft Control System (MACS). The test subject and researchers operated from the Research Ground Control Station (RGCS) at AFRC using the Vigilant Spirit Control Station (VSCS) and associated DAA software and displays. Flight Operation for the unmanned aircraft (UA) and manned intruder traffic was conducted at AFRC. Virtual traffic was managed by ARC. Voice distribution was accomplished using a combination of disparate communication systems at ARC and AFRC. The purpose of this document is to record the development, design, and execution of activities in support of the FT6 efforts from the perspective of the ARC IT&E team. Furthermore, the Armstrong IT&E team has published a thorough FT6 Test Report, with emphasis on flight test support, facilities and vehicle development; this report complements the Armstrong report. Analysis of collected FT6 data will be conducted and reported by the M&S and HSI teams and will be published in separate reports.

UAS-NAS↗
NASA NTRS2010

Kepler Science Operations Center Architecture

We give an overview of the operational concepts and architecture of the Kepler Science Data Pipeline. Designed, developed, operated, and maintained by the Science Operations Center (SOC) at NASA Ames Research Center, the Kepler Science Data Pipeline is central element of the Kepler Ground Data System. The SOC charter is to analyze stellar photometric data from the Kepler spacecraft and report results to the Kepler Science Office for further analysis. We describe how this is accomplished via the Kepler Science Data Pipeline, including the hardware infrastructure, scientific algorithms, and operational procedures. The SOC consists of an office at Ames Research Center, software development and operations departments, and a data center that hosts the computers required to perform data analysis. We discuss the high-performance, parallel computing software modules of the Kepler Science Data Pipeline that perform transit photometry, pixel-level calibration, systematic error-correction, attitude determination, stellar target management, and instrument characterization. We explain how data processing environments are divided to support operational processing and test needs. We explain the operational timelines for data processing and the data constructs that flow into the Kepler Science Data Pipeline.

Middour, Christopher↗