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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

Evaluating software development by analysis of changes: The data from the software engineering laboratory

An effective data collection methodology for evaluating software development methodologies was applied to four different software development projects. Goals of the data collection included characterizing changes and errors, characterizing projects and programmers, identifying effective error detection and correction techniques, and investigating ripple effects. The data collected consisted of changes (including error corrections) made to the software after code was written and baselined, but before testing began. Data collection and validation were concurrent with software development. Changes reported were verified by interviews with programmers.

Source record↗
NASA NTRS1974

Apollo experience report: Data management for postflight engineering evaluation

The Apollo management of data for postflight engineering evaluation is described. The sources of Apollo telemetry data, the control of data processing by a single data team, the data techniques used to assist in evaluation of the large quantity of data, and the operation of the data team before the mission and during the evaluation phase are described. The techniques used to ensure the output of valid data and to determine areas in which data were of questionable quality are also included.

Foster, G. B., Jr.↗
NASA NTRS1996

Forced response testing of an axi-centrifugal turboshaft engine

Dynamic data from tests of a T55-L-712 engine are presented. Engine stall/surge data were analyzed using digital signal processing techniques. In addition, forced response testing (system identification studies) was done at various engine speeds. Forced response testing was done using eight jet ejectors approximately equally circumferentially spaced about the compressor front face. This paper presents some preliminary results for the ground idle (approximately 60% of design speed) point. Brief descriptions of the jet injection system, the test matrix, and analysis techniques used are presented. Results of these analyses indicate a substantial transfer of energy across the compressor first stage at some frequencies and that the ejectors are effective in modifying the local flow conditions in front of the first compressor stage.

Owen, A. Karl↗
NASA NTRS1996

Forced Response Testing of an Axi-Centrifugal Turboshaft Engine

Dynamic data from tests of a T55-L,712 engine are presented. Engine stall/surge data were analyzed using digital signal processing techniques. In addition, forced response testing (system identification studies) was done at various engine speeds. Forced response testing was done using eight jet ejectors approximately equally circumferentially spaced about the compressor front face. This paper presents some preliminary results for the ground idle (approximately 60% of design speed) point. Brief descriptions of the jet injection system, the test matrix, and analysis techniques used are presented. Results of these analyses indicate a substantial transfer of energy across the compressor first stage at some frequencies and that the ejectors are effective in modifying the local flow conditions in front of the first compressor stage.

Owen, A. Karl↗
DOE OSTI2021

2020 ETI Annual Summer School: Data Science and Engineering

The Consortium for Enabling Technologies & Innovation (ETI) was established in 2019 to address emerging technologies within the context of nuclear nonproliferation. ETI creates a research and education environment to support cross-cutting technologies across three core disciplines: 1) computer and engineering science research specifically in a form of machine learning and high performance computing (HPC), 2) advanced manufacturing, and 3) nuclear detection technologies. For outreach and development, ETI hosted the first of three summer schools from August 24-28, 2020 with the theme of “Data Science and Engineering”. The school was hosted in an on-line format and had over 200 participants. The recorded content is available on-line as a resource for students. The summer school had four modules: 1) Fundamentals of data Applications, 2) Computational Machine Learning, 3) Bayesian Modeling and Inference, and 4) Data Science for Safeguards. Modules contained both lectures as well as student exercises. Poll Everywhere was utilized in some modules as an on-line method to engage large groups of students. Upcoming ETI Summer Schools include Novel Instrumentation in 2021 and Advanced Manufacturing in 2022.

Biegalski, Steven R.↗
DOE OSTI2022

Residual Dose and Environmental Monitoring for the Fermilab Main Injector Tunnel Using the Data Acquisition Logging Engine (Dale)

The Recycler and the Main Injector are part of the Fermilab Accelerator complex used to deliver proton beam to the different experiments. It is very important to control and minimize losses in both machines during operation, to reduce personnel dose from residual activation and to preserve component lifetime. To minimize losses, we need to identify the loss points and adjust the components accordingly. The Data Acquisition Loss Engine (DALE) platform has been developed within the Main Injector department and upgraded throughout the years. DALE is used to survey the entire enclosure for residual dose rates and environmental readings when unrestricted access to the enclosure is possible. Currently DALE has two radiation meters, which are aligned along each machine, so loss points can be identified for both at the same time. DALE attaches to the enclosure carts and is continuously in motion monitoring dose rates and other environmental readings. In this paper we will describe how DALE is used to provide radiation maps of the residual dose rates in the enclosure. We will also compare the loss points with the Beam Loss monitor data.

43 PARTICLE ACCELERATORS↗
NASA NTRS2000

Martian Surface Boundary Layer Characterization: Enabling Environmental Data for Science, Engineering and Human Exploration

For human or large robotic exploration of Mars, engineering devices such as power sources will be utilized that interact closely with the Martian environment. Heat sources for power production, for example, will use the low ambient temperature for efficient heat rejection. The Martian ambient, however, is highly variable, and will have a first order influence on the efficiency and operation of all large-scale equipment. Diurnal changes in temperature, for example, can vary the theoretical efficiency of power production by 15% and affect the choice of equipment, working fluids, and operating parameters. As part of the Mars Exploration program, missions must acquire the environmental data needed for design, operation and maintenance of engineering equipment including the transportation devices. The information should focus on the variability of the environment, and on the differences among locations including latitudes, altitudes, and seasons. This paper outlines some of the WHY's, WHAT's and WHERE's of the needed data, as well as some examples of how this data will be used. Environmental data for engineering design should be considered a priority in Mars Exploration planning. The Mars Thermal Environment Radiator Characterization (MTERC), and Dust Accumulation and Removal Technology (DART) experiments planned for early Mars landers are examples of information needed for even small robotic missions. Large missions will require proportionately more accurate data that encompass larger samples of the Martian surface conditions. In achieving this goal, the Mars Exploration program will also acquire primary data needed for understanding Martian weather, surface evolution, and ground-atmosphere interrelationships.

England, C.↗
DOE OSTI2022

Preventing Reverse Engineering of Critical Industrial Data with DIOD

Business analytics augmented by artificial intelligence and machine learning (AI/ML) have revolutionized the role of data in the modern world. In recent years, businesses have incorporated data into their decision-making process for better prediction, risk-assessment, content creation, etc. While such businesses often seek to leverage the full use of their data through third-party AI/ML services, they are often hampered by the risks of data leaks, reverse-engineering, stolen technology, etc. that often have disastrous consequences for businesses and their stakeholders alike. Thus, there arises a need for data masking prior to its transmission that obfuscates proprietary information while preserving the information relevant for AI/ML applications. In order to meet the needs of industrial data which are significantly different from those of data warehouses, previous work proposed an efficient time and space-scalable data masking paradigm known as the deceptive infusion of data (DIOD) methodology. The present work expands upon this work by leveraging existing reverse-engineering capabilities to facilitate the decomposition of industrial data into its proprietary and AI/ML-relevant parts, referred to as fundamental and inference metadata respectively. Both sets of metadata are further obfuscated in accordance with the DIOD methodology to create the DIOD rendition of the industrial data, which is rendered immune to reverse-engineering by discarding proprietary information and only preserving AI/ML-relevant information. Additionally, constraints of the original DIOD manuscript are relaxed using mutual information by configuring the methodology to the target AI/ML application to unlock the full potential of the DIOD methodology. As an example, data from a nuclear reactor is transformed into that from a nonlinear spring-mass system with different levels of data masking as required by the generic system and the target application.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1987

High frequency data acquisition system for space shuttle main engine testing

The high frequency data acquisition system developed for the Space Shuttle Main Engine (SSME) single engine test facility at the National Space Technology Laboratories is discussed. The real time system will provide engineering data for a complete set of SSME instrumentation (approx. 100 measurements) within 4 hours following engine cutoff, a decrease of over 48 hours from the previous analog tape based system.

Lewallen, Pat↗
NASA NTRS1991

Software Engineering Laboratory (SEL) data and information policy

The policies and overall procedures that are used in distributing and in making available products of the Software Engineering Laboratory (SEL) are discussed. The products include project data and measures, project source code, reports, and software tools.

Mcgarry, Frank↗
NASA NTRS1976

Emissions data by category of engines

Exhaust gas pollutant emissions data under test stand conditions were obtained for the following: (1) full-rich baseline test (7-mode cycle), (2) lean-out tests for each power mode, and (3) different spark settings. The test data were also used to create a theoretical 5-mode cycle baseline. The emissions data in the framework of the theoretical 5-mode cycle were emphasized. There is no significant difference in the test results produced by data exhibited on the 7-mode cycle or 5-mode cycle. The 5-mode cycle was slightly more conservative for the carbon monoxide pollutant than the 7-mode cycle. The data were evaluated to determine which mode(s) had the greatest influence on improving general aviation piston engine emissions. Improvements that were achieved as a result of making lean-out adjustments to the fuel metering device were: (1) taxi mode only, (2) taxi and approach modes combined, and (3) leaning-out of the climb mode to best power.

Barriage, J.↗
NASA NTRS2003

Software for Preprocessing Data From Rocket-Engine Tests

Three computer programs have been written to preprocess digitized outputs of sensors during rocket-engine tests at Stennis Space Center (SSC). The programs apply exclusively to the SSC E test-stand complex and utilize the SSC file format. The programs are the following: (1) Engineering Units Generator (EUGEN) converts sensor-output-measurement data to engineering units. The inputs to EUGEN are raw binary test-data files, which include the voltage data, a list identifying the data channels, and time codes. EUGEN effects conversion by use of a file that contains calibration coefficients for each channel. (2) QUICKLOOK enables immediate viewing of a few selected channels of data, in contradistinction to viewing only after post-test processing (which can take 30 minutes to several hours depending on the number of channels and other test parameters) of data from all channels. QUICKLOOK converts the selected data into a form in which they can be plotted in engineering units by use of Winplot. (3) EUPLOT provides a quick means for looking at data files generated by EUGEN without the necessity of relying on the PVWAVE based plotting software.

Cheng, Chiu-Fu↗