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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Integration by parts

This paper describes the unique integration and verification challenges associated with the Space Station Freedom and an approach to solve these problems using Data Management Systems (DMS) Kits. These DMS Kits will help alleviate the complex integration problems inherent in building, assembling and testing the Space Station. Particular emphasis has been placed on utilizing the capabilities and services of the on-board DMS to provide the integration and verification tools, not only for the DMS but for the other on-board distributed systems as well. DMS Kits are provided to system/software developers across the program. These DMS Kits provide a common set of integration and verification tools and hardware. Each system developer can then utilize, through the kits, a simulation of the complete data processing environment which will be available on orbit. The paper describes the evolution of the integration process from the system level to the final integration of multiple launch packages. DMS Kits are used throughout this process, which addresses both the ground and on-orbit aspects of the problem.

Barry, Thomas↗
NASA NTRS2011

A Parametric Testing Environment for Finding the Operational Envelopes of Simulated Guidance Algorithms

The ever-increasing size and complexity of aerospace systems often drive developers to validate using modeling and Monte Carlo simulations confined around expected points of operation in a hyper-dimensional parameter space. This paper describes an alternative that explores large regions of the parameter space with explicit coverage guarantees, searching for n parameter relations that characterize a system's performance envelope.

Parametric testing↗
NASA NTRS1989

A wall interference assessment/correction interface measurement system for the NASA/ARC 12-ft PWT

Development of complex air vehicle configurations is placing increasing demands on wind tunnel testing capabilities. A major area of concern is wall induced interference. Recent developments in wall interference technology provide a means for assessing and correcting for the wall induced interference using information contained in the distribution of flow variables measured at, or near, the wall. The restoration of the NASA-ARC 12-ft pressure wind tunnel (PWT) provides an opportunity to incorporate a measurement system with which wall interference assessment/correction (WIAC) technology can be applied. In this first phase of the development of a WIAC system for the PWT, the design criteria for the placement and the geometry of wall static pressure orifices were determined with a three step approach. First, the operational environment of the PWT was analyzed as to the requirements for the WIAC system. Second, appropriate wall interference theories were evaluated against the requirements determined from the operational environment. Third, the flow about representative models in the PWT was calculated and, specifically, the pressure signatures at the location of the test section wall were obtained. The number of discrete pressure measurements and their locations were determined by curve fitting the pressure distribution through the discrete measurements and evaluating the resulting error.

Source record↗
NASA NTRS1990

Advanced recovery systems wind tunnel test report

Pioneer Aerospace Corporation (PAC) conducted parafoil wind tunnel testing in the NASA-Ames 80 by 120 test sections of the National Full-Scale Aerodynamic Complex, Moffett Field, CA. The investigation was conducted to determine the aerodynamic characteristics of two scale ram air wings in support of air drop testing and full scale development of Advanced Recovery Systems for the Next Generation Space Transportation System. Two models were tested during this investigation. Both the primary test article, a 1/9 geometric scale model with wing area of 1200 square feet and secondary test article, a 1/36 geometric scale model with wing area of 300 square feet, had an aspect ratio of 3. The test results show that both models were statically stable about a model reference point at angles of attack from 2 to 10 degrees. The maximum lift-drag ratio varied between 2.9 and 2.4 for increasing wing loading.

Geiger, R. H.↗
NASA NTRS1989

Automated thermal mapping techniques using chromatic image analysis

Thermal imaging techniques are introduced using a chromatic image analysis system and temperature sensitive coatings. These techniques are used for thermal mapping and surface heat transfer measurements on aerothermodynamic test models in hypersonic wind tunnels. Measurements are made on complex vehicle configurations in a timely manner and at minimal expense. The image analysis system uses separate wavelength filtered images to analyze surface spectral intensity data. The system was initially developed for quantitative surface temperature mapping using two-color thermographic phosphors but was found useful in interpreting phase change paint and liquid crystal data as well.

Buck, Gregory M.↗
NASA NTRS1989

Automated thermal mapping techniques using chromatic image analysis

Thermal imaging techniques are introduced using a chromatic image analysis system and temperature sensitive coatings. These techniques are used for thermal mapping and surface heat transfer measurements on aerothermodynamic test models in hypersonic wind tunnels. Measurements are made on complex vehicle configurations in a timely manner and at minimal expense. The image analysis system uses separate wavelength filtered images to analyze surface spectral intensity data. The system was initially developed for quantitative surface temperature mapping using two-color thermographic phosphors but was found useful in interpreting phase change paint and liquid crystal data as well.

Buck, Gregory M.↗
NASA NTRS2011

Software Testing and Verification in Climate Model Development

Over the past 30 years most climate models have grown from relatively simple representations of a few atmospheric processes to a complex multi-disciplinary system. Computer infrastructure over that period has gone from punch card mainframes to modem parallel clusters. Model implementations have become complex, brittle, and increasingly difficult to extend and maintain. Existing verification processes for model implementations rely almost exclusively upon some combination of detailed analysis of output from full climate simulations and system-level regression tests. In additional to being quite costly in terms of developer time and computing resources, these testing methodologies are limited in terms of the types of defects that can be detected, isolated and diagnosed. Mitigating these weaknesses of coarse-grained testing with finer-grained "unit" tests has been perceived as cumbersome and counter-productive. In the commercial software sector, recent advances in tools and methodology have led to a renaissance for systematic fine-grained testing. We discuss the availability of analogous tools for scientific software and examine benefits that similar testing methodologies could bring to climate modeling software. We describe the unique challenges faced when testing complex numerical algorithms and suggest techniques to minimize and/or eliminate the difficulties.

Clune, Thomas L.↗
NASA NTRSDate not supplied

Supportability Concepts for Crewed Deep Space Exploration

Supportability—defined as the set of system characteristics that influence the logistics and support required to enable safe and effective operations—will be a much larger driver of mass, risk, and crew time for future human space exploration due to the more challenging mission context. For Mars, systems must operate in a logistically isolated environment for much longer durations than previous missions, which results in a higher probability of system failure and therefore an increased need for maintenance or contingency options. Mars missions also lack access to quick aborts, which increases the consequences of an unrecoverable system failure. Together, this higher likelihood and consequence of failure results in an increase in supportability-related risk. Supportability analysis is an important part of systems development that helps designers better understand the impacts of system and mission decisions on risk, mass, and crew time. The real-world processes that drive maintenance requirements and other supportability-related characteristics are probabilistic, and therefore they require different conceptual approaches and models than are used for more deterministic aspects of space systems. This paper provides an overview of supportability analysis, addresses key concepts, and provides examples of how supportability analysis can be incorporated into system development. Specifically, system supportability involves stochastic processes, and therefore must be evaluated using probabilistic models. These models can be used to perform sensitivity analysis even if system characteristics are not yet fully defined. Failure rates cannot be measured directly, but tests provide valuable data that can help refine those estimates. Human spaceflight architectures are complex, and exhibit coupled behavior that should be examined with integrated systems analysis that includes an assessment of supportability.

Supportability↗
NASA NTRSDate not supplied

Supportability Concepts for Crewed Deep Space Exploration

Supportability—defined as the set of system characteristics that influence the logistics and support required to enable safe and effective operations—will be a much larger driver of mass, risk, and crew time for future human space exploration due to the more challenging mission context. For Mars, systems must operate in a logistically isolated environment for much longer durations than previous missions, which results in a higher probability of system failure and therefore an increased need for maintenance or contingency options. Mars missions also lack access to quick aborts, which increases the consequences of an unrecoverable system failure. Together, this higher likelihood and consequence of failure results in an increase in supportability-related risk. Supportability analysis is an important part of systems development that helps designers better understand the impacts of system and mission decisions on risk, mass, and crew time. The real-world processes that drive maintenance requirements and other supportability-related characteristics are probabilistic, and therefore they require different conceptual approaches and models than are used for more deterministic aspects of space systems. This paper provides an overview of supportability analysis, addresses key concepts, and provides examples of how supportability analysis can be incorporated into system development. Specifically, system supportability involves stochastic processes, and therefore must be evaluated using probabilistic models. These models can be used to perform sensitivity analysis even if system characteristics are not yet fully defined. Failure rates cannot be measured directly, but tests provide valuable data that can help refine those estimates. Human spaceflight architectures are complex, and exhibit coupled behavior that should be examined with integrated systems analysis that includes an assessment of supportability.

Supportability↗
NASA NTRS1989

Characterization of structural connections using free and forced response test data

The accurate prediction of system dynamic response often has been limited by deficiencies in existing capabilities to characterize connections adequately. Connections between structural components often are complex mechanically, and difficult to accurately model analytically. Improved analytical models for connections are needed to improve system dynamic preditions. A procedure for identifying physical connection properties from free and forced response test data is developed, then verified utilizing a system having both a linear and nonlinear connection. Connection properties are computed in terms of physical parameters so that the physical characteristics of the connections can better be understood, in addition to providing improved input for the system model. The identification procedure is applicable to multi-degree of freedom systems, and does not require that the test data be measured directly at the connection locations.

Lawrence, Charles↗
NASA NTRS1989

Characterization of structural connections using free and forced response test data

The accurate prediction of system dynamic response often has been limited by deficiencies in existing capabilities to characterize connections adequately. Connections between structural components often are complex mechanically, and difficult to accurately model analytically. Improved analytical models for connections are needed to improve system dynamic predictions. A procedure for identifying physical connection properties from free and forced response test data is developed, then verified utilizing a system having both a linear and nonlinear connection. Connection properties are computed in terms of physical parameters so that the physical characteristics of the connections can better be understood, in addition to providing improved input for the system model. The identification procedure is applicable to multi-degree of freedom systems, and does not require that the test data be measured directly at the connection locations.

Lawrence, C.↗
NASA NTRS1993

Full-scale wind-tunnel tests of high-lift system modifications on a carrier based fighter aircraft

Modifications to the high-lift system of a full-scale F/A-I8A were tested in the 80- by 120-Foot Wind Tunnel of the National Full-Scale Aerodynamics Complex at the NASA Ames Research Center in Moffett Field, California. The objective was to measure the effect of simple modifications on the aerodynamic performance of the high-lift system. The modifications included the placement of a straight fairing in the shroud cove above the trailing-edge flap and the addition of seals to prevent air leakage through the hinge lines of the leading-edge flap, the trailing-edge shroud, and the wing fold. The test was carried out on an actual F/A-18A with it's flaps deployed in the landing approach configuration. The angle of attack ranged from 0 to 16 degrees and the wind speed was 100 knots. At an angle of attack of 8 degrees, the trimmed lift coefficient was improved by 0.09 with all wing seals in place. This corresponds to a reduction in the approach speed for the F/A-I8A of about 5 knots. The seal along the wing fold hinge, a feature present on many naval aircraft, provided one third of the total increment in trimmed lift. A comparison of the full-scale wind-tunnel results with those obtained from flight test is also presented.

Meyn, Larry A.↗
NASA NTRSDate not supplied

Bootstrapping Multi-Agent Unmanned Aerial Vehicle (UAV) System Integration Using Ground-Based Assets: Lessons Learned

In support of the Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR) project, a fleet of unmanned ground vehicles (UGVs) was developed as a test and evaluation (T\&E) platform to reduce system integration gaps between simulation and live flight hardware. While simulation and hardware-in-the-loop bench testing provide adequate environments for preliminary validation, differences in system deployment architecture, software interfaces, and hardware infrastructure increase the risks to safety, property, and the project. Given ATTRACTOR’s goal of establishing a basis of certification of trust and trustworthiness in multi-agent autonomous systems, bridging these gaps was critical to successful project execution and feasibility assessment. In this paper we present the UGV fleet and its role in speeding up system integration, smoothing the transition from simulation to flight, and providing researchers an easy-to-use hardware test bed. An overview of the hardware and software on-board the vehicles is provided along with supporting infrastructure. The system integration process is documented including results in supporting both the overarching design reference mission (DRM) of ATTRACTOR and individual research efforts conducted since the creation of the fleet. Finally, we discuss the practical lessons learned regarding the testing, deployment, and operation of multi-agent autonomous systems.

Matthew P. Vaughan↗
NASA NTRSDate not supplied

Statistical Approach on Utilizing Ground-based Experiments to Model Break-up Events

Two laboratory-based impact tests have been conducted to develop and extend the capability of NASA satellite breakup models. The first experiment, the Satellite Orbital Debris Characterization Impact Test (SOCIT), was conducted by the U.S. Department of Defense and NASA in 1992. It employed a fully functional U.S. Navy Transit spacecraft, fabricated from materials commonly used in the 1960s. SOCIT fragmentation data formed the basis of the current NASA Standard Satellite Breakup Model (SSBM). A second experiment, DebriSat, was conducted in 2014 by the DebriSat consortium: the NASA Orbital Debris Program Office; the United States Space Force Space Systems Command, formerly the Air Force Space and Missile Systems Center, the Air Force Arnold Engineering Development Complex, and the University of Florida. This impact test was performed on a high-fidelity mock-up satellite assembled from modern components. Data from both experiments are expected to contribute to the next-generation models for on-orbit breakup analyses, long-term environment predictions, and debris risk assessment. This paper uses the direct statistical sampling of the SOCIT and DebriSat data ensembles to model an on-orbit breakup event, rather than the analytic expressions estimated from the samples as with as with the NASA SSBM and its predecessor. This direct method involves drawing fragments (i.e., sampling with replacement) from each fragmentation data-subset containing mass, shape category, material density, characteristic length, mass, and cross-sectional area. As part of the sampling process, the properties of sampled fragment data (e.g., area-to-mass ratios) are numerically checked to ensure they do not contain unrealistic quantities. The process to simulate a breakup cloud composed of fragments from SOCIT and DebriSat datasets is discussed. The methodology for ensuring that conservation of overall mass of the sampled fragment cloud under this sampling approach is highlighted. Finally, the results are compared with simulated clouds generated from SSBM for specific historical breakup events.

Andrew Vavrin↗
NASA NTRS2023

Statistical Approach on Utilizing Ground-Based Experiments to Model Break-Up Events

Two laboratory-based impact tests have been conducted to develop and extend the capability of NASA satellite breakup models. The first experiment, the Satellite Orbital Debris Characterization Impact Test (SOCIT), was conducted by the U.S. Department of Defense and NASA in 1992. It employed a fully functional U.S. Navy Transit spacecraft, fabricated from materials commonly used in the 1960s. SOCIT fragmentation data formed the basis of the current NASA Standard Satellite Breakup Model (SSBM). A second experiment, DebriSat, was conducted in 2014 by the DebriSat consortium: the NASA Orbital Debris Program Office, the United States Space Force Space Systems Command, formerly the Air Force Space and Missile Systems Center, the Air Force Arnold Engineering Development Complex, and the University of Florida. This impact test was performed on a high-fidelity mock-up satellite assembled from modern components. Data from both experiments are expected to contribute to the next-generation models for on-orbit breakup analyses, long-term environment predictions, and debris risk assessment. This paper uses the direct statistical sampling of the SOCIT and DebriSat data ensembles to model an on-orbit breakup event, rather than the analytic expressions estimated from the samples in the SSBM and its predecessor. This direct method involves drawing fragments (i.e., sampling with replacement) from each fragmentation data-subset containing mass, shape category, material density, characteristic length, mass, and cross-sectional area. As part of the sampling process, the properties of sampled fragment data (e.g., area-to-mass ratios) are numerically checked to ensure they do not contain unrealistic quantities. The process to simulate a breakup cloud composed of fragments from SOCIT and DebriSat datasets is discussed. The methodology for ensuring that conservation of overall mass of the sampled fragment cloud under this sampling approach is highlighted. Finally, the results are compared with simulated clouds generated from SSBM for specific historical breakup events.

Andrew Vavrin↗
NASA NTRS2009

(Quickly) Testing the Tester via Path Coverage

The configuration complexity and code size of an automated testing framework may grow to a point that the tester itself becomes a significant software artifact, prone to poor configuration and implementation errors. Unfortunately, testing the tester by using old versions of the software under test (SUT) may be impractical or impossible: test framework changes may have been motivated by interface changes in the tested system, or fault detection may become too expensive in terms of computing time to justify running until errors are detected on older versions of the software. We propose the use of path coverage measures as a "quick and dirty" method for detecting many faults in complex test frameworks. We also note the possibility of using techniques developed to diversify state-space searches in model checking to diversify test focus, and an associated classification of tester changes into focus-changing and non-focus-changing modifications.

evaluation of test systems↗
NASA NTRS2011

Embedded Acoustic Sensor Array for Engine Fan Noise Source Diagnostic Test: Feasibility of Noise Telemetry via Wireless Smart Sensors

Aircraft engines have evolved into a highly complex system to meet ever-increasing demands. The evolution of engine technologies has primarily been driven by fuel efficiency, reliability, as well as engine noise concerns. One of the sources of engine noise is pressure fluctuations that are induced on the stator vanes. These local pressure fluctuations, once produced, propagate and coalesce with the pressure waves originating elsewhere on the stator to form a spinning pressure pattern. Depending on the duct geometry, air flow, and frequency of fluctuations, these spinning pressure patterns are self-sustaining and result in noise which eventually radiate to the far-field from engine. To investigate the nature of vane pressure fluctuations and the resulting engine noise, unsteady pressure signatures from an array of embedded acoustic sensors are recorded as a part of vane noise source diagnostics. Output time signatures from these sensors are routed to a control and data processing station adding complexity to the system and cable loss to the measured signal. "Smart" wireless sensors have data processing capability at the sensor locations which further increases the potential of wireless sensors. Smart sensors can process measured data locally and transmit only the important information through wireless communication. The aim of this wireless noise telemetry task was to demonstrate a single acoustic sensor wireless link for unsteady pressure measurement, and thus, establish the feasibility of distributed smart sensors scheme for aircraft engine vane surface unsteady pressure data transmission and characterization.

Zaman, Afroz↗