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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Long Duration Exposure Facility (LDEF) low-temperature Heat Pipe Experiment Package (HEPP) flight results

The Low Temperature Heat Pipe Flight Experiment (HEPP) is a fairly complicated thermal control experiment that was designed to evaluate the performance of two different low temperature ethane heat pipes and a n-Heptane Phase Change Material (PCM) canister. A total of 388 days of continuous operation with an axially grooved aluminum fixed conductance heat pipe of axially grooved stainless steel heat pipe diode was demonstrated before the EDS batteries lost power. The inability of the HEPP's radiator to cool below 190 K in flight prevented freezing of the PCM and the opportunity to conduct transport tests with the heat pipes. Post flight tests showed that the heat pipes and the PCM are still functioning. This paper presents a summary of the flight data analysis for the HEPP and its related support systems. Pre and post-flight thermal vacuum tests results are presented for the HEPP thermal control system along with individual heat pipe performance and PCM behavior. Appropriate SIG related systems data will also be included along with a 'lessons learned' summary.

Mcintosh, Roy↗
NASA NTRS1973

Auroral data from Michigan airglow payload launch

Auroral studies are presented of flight data analysis from the Michigan airglow payload. Analysis of the stellar occultation data and results from the twilight flight are reported. Optical emissions from bottled aurora and an electron analyzer for measurement of distributions in energy of electrons along a beam are also presented. A list of related publications is included.

Hays, P. B.↗
NASA NTRSDate not supplied

Assessing Engine Hot Fire Data for Human Spaceflight Applications

Development and certification of liquid engine systems for human spaceflight missions requires exhaustive analysis to meet the NASA’s requirements for engine health, reliability, and performance. The techniques used to assess requirement conformance and test-to-test engine health pose many unique challenges including the unusually large scale of data, complex component and system analysis, and rigorous engineering judgement standards. To address these challenges, NASA Marshall Space Flight Center’s Engine Systems branch has developed and maintained a robust software suite and operational processes that satisfy programmatic requirements levied on engines and the 7 Elements of Flight Rationale. Analysis at a systems level includes subsystem assessment of components such as turbomachinery and combustion devices as well as structural and fluid dynamics and transient and steady-state assessment at a systems level. Some of the most important tools to accomplish this analysis are automated script databases, creation of historical and statistical comparisons, and parameters calculated at the full data rate. These tools greatly simplify the crucial processes of anomaly investigation, limit monitoring, health assessment, and timely communication of key conclusions drawn from hot fire testing and flight data analysis.

Data Assessment↗
NASA NTRSDate not supplied

Assessing Engine Hot Fire Data for Human Spaceflight Applications

Development and certification of liquid engine systems for human spaceflight missions requires exhaustive analysis to meet the NASA’s requirements for engine health, reliability, and performance. The techniques used to assess requirement conformance and test-to-test engine health pose many unique challenges including the unusually large scale of data, complex component and system analysis, and rigorous engineering judgement standards. To address these challenges, NASA Marshall Space Flight Center’s Engine Systems branch has developed and maintained a robust software suite and operational processes that satisfy programmatic requirements levied on engines and the 7 Elements of Flight Rationale. Analysis at a systems level includes subsystem assessment of components such as turbomachinery and combustion devices as well as structural and fluid dynamics and transient and steady-state assessment at a systems level. Some of the most important tools to accomplish this analysis are automated script databases, creation of historical and statistical comparisons, and parameters calculated at the full data rate. These tools greatly simplify the crucial processes of anomaly investigation, limit monitoring, health assessment, and timely communication of key conclusions drawn from hot fire testing and flight data analysis.

Data Assessment↗
NASA NTRSDate not supplied

Assessing Hot Fire Data with WinPlot

Development and certification of liquid engine systems for human spaceflight missions requires exhaustive analysis to meet the NASA’s requirements for engine health, reliability, and performance. The techniques used to assess requirement conformance and test-to-test engine health and performance pose many unique challenges including the unusually large scale of data, complex component and system analysis, and rigorous engineering judgement standards. To address these challenges, NASA Marshall Space Flight Center’s Engine Systems branch has developed and maintained a robust software suite and operational processes that satisfy programmatic requirements levied on engines and the 7 Elements of Flight Rationale. Analysis at a systems level includes subsystem assessment of components such as turbomachinery and combustion devices as well as structural and fluid dynamics and transient and steady-state assessment at a systems level. Some of the most important tools to accomplish this analysis are automated script databases, creation of historical and statistical comparisons, and parameters calculated at the full data rate. These tools greatly simplify the crucial processes of anomaly investigation, limit monitoring, health assessment, and timely communication of key conclusions drawn from hot fire testing and flight data analysis.

J. Davis Hunter↗
NASA NTRS2006

Geolocation and Pointing Accuracy Analysis for the WindSat Sensor

Geolocation and pointing accuracy analyses of the WindSat flight data are presented. The two topics were intertwined in the flight data analysis and will be addressed together. WindSat has no unusual geolocation requirements relative to other sensors, but its beam pointing knowledge accuracy is especially critical to support accurate polarimetric radiometry. Pointing accuracy was improved and verified using geolocation analysis in conjunction with scan bias analysis. nvo methods were needed to properly identify and differentiate between data time tagging and pointing knowledge errors. Matchups comparing coastlines indicated in imagery data with their known geographic locations were used to identify geolocation errors. These coastline matchups showed possible pointing errors with ambiguities as to the true source of the errors. Scan bias analysis of U, the third Stokes parameter, and of vertical and horizontal polarizations provided measurement of pointing offsets resolving ambiguities in the coastline matchup analysis. Several geolocation and pointing bias sources were incfementally eliminated resulting in pointing knowledge and geolocation accuracy that met all design requirements.

Meissner, Thomas↗
NASA NTRS1993

Research requirements for a real-time flight measurements and data analysis system for subsonic transport high-lift research

A multiphased research program to obtain detailed flow characteristics on a multielement high-lift flap system is being conducted on the Transport Systems Research Vehicle (B737-100 aircraft) at NASA Langley Research Center. Upcoming flight tests have required the development of a highly capable and flexible flight measurement and data analysis instrumentation system. This instrumentation system will be more comprehensive than any of the systems used on previous high-lift flight experiment at NASA Langley. The system will provide the researcher near-real-time information for decision making needed to modify a flight test in order to further examine unexpected flow conditions. This paper presents the research requirements and instrumentation design concept for an upcoming flight experiment for the subsonic transport high-lift research program. The flight experiment objectives, the measurement requirements, the data acquisition system, and the onboard data analysis and display capabilities are described.

Whitehead, Julia H.↗
NASA NTRS2000

Aerospike Engine Post-Test Diagnostic System Delivered to Rocketdyne

The NASA Glenn Research Center at Lewis Field, in cooperation with Rocketdyne, has designed, developed, and implemented an automated Post-Test Diagnostic System (PTDS) for the X-33 linear aerospike engine. The PTDS was developed to reduce analysis time and to increase the accuracy and repeatability of rocket engine ground test fire and flight data analysis. This diagnostic system provides a fast, consistent, first-pass data analysis, thereby aiding engineers who are responsible for detecting and diagnosing engine anomalies from sensor data. It uses analytical methods modeled after the analysis strategies used by engineers. Glenn delivered the first version of PTDS in September of 1998 to support testing of the engine s power pack assembly. The system was used to analyze all 17 power pack tests and assisted Rocketdyne engineers in troubleshooting both data acquisition and test article anomalies. The engine version of PTDS, which was delivered in June of 1999, will support all single-engine, dual-engine, and flight firings of the aerospike engine.

Meyer, Claudia M.↗
NASA NTRS2024

BOLT-2 Roughness Side Flight Data Results and Analysis

This report provides an in-depth review of the flight data obtained from Side B, also known as the roughness side, of BOLT-2, which was developed and designed to measure the effectiveness of boundary layer trips at hypersonic conditions. Three discrete-roughness trips were implemented on Side B at specific locations, with the necessary sensor layout, to investigate the flight conditions at which they no longer maintained turbulence behind them. All three trips were the same type that were scaled and sized based on predictions of local boundary layer thicknesses to provide the same level of effectiveness. One trip was on the vehicle centerline, where the boundary layer is relatively thick, while the other two were symmetrically located outboard where the boundary layer is much thinner. The relative difference in boundary layer thickness between these locations was roughly on the order of 3-to-1, thus the centerline trip was geometrically about three times larger than the outboard trips. A first order assessment of the Side B flight results is indicated by these three trips forcing transition onset at the same time during flight. The enclosed flight data shows that the performance of each individual trip was nearly identical, with allowances for minor variations attributed to measurement accuracy.

Flight Data↗
NASA NTRSDate not supplied

Assessment of Artemis-1 Pogo Flight Instrumentation System

As the space industry continues to strive for more efficient launch vehicles, it must relyon increasingly accurate predictive models. Verification of models typically requires physical testing. Flight data measurements offer the most real and therefore the most accurate data for model correlation. As NASA prepares for the inaugural launch of Space Launch System(SLS), Artemis-1, they must rely heavily on predictive system models to ensure flight safety.NASA has implemented a Development Flight Instrumentation (DFI) system in hopes of recovering useful flight data to aid in model correlation. Historically, some of the most important flight measurements are those that monitor the potentially destructive dynamic interaction of the structural and propellant modes – a phenomenon known as pogo. Pogo is a dynamic instability that can occur on a launch vehicle during any phase of ascent. During this investigation an end-to-end assessment of the Artemis-I Pogo-related DFI was performed to identify any obstacles inherent in the current instrumentation system which may prevent successful measurement of the data necessary to validate the current predictive fluid-structural models. Input drive signals were approximated and applied to a state-space system model to derive predicted pressure and acceleration responses. These predicted responses were then fed through a simulation of the data acquisition process in order to recover predicted measurements. Finally, a mock Flight Data Analysis (FDA) was performed to assess the ability of these measurements to meet the Flight Test Objectives(FTO).

Adam Johnson↗
NASA NTRSDate not supplied

Assessment of Artemis-1 Pogo Flight Instrumentation System

As the space industry continues to strive for more efficient launch vehicles, it must rely on increasingly accurate predictive models. Verification of models typically requires physical testing. Flight data measurements offer the most real and therefore the most accurate data for model correlation. As NASA prepares for the inaugural launch of Space Launch System (SLS), Artemis-1, they must rely heavily on predictive system models to ensure flight safety. NASA has implemented a Development Flight Instrumentation (DFI) system in hopes of recovering useful flight data to aid in model correlation. Historically, some of the most important flight measurements are those that monitor the potentially destructive dynamic interaction of the structural and propellant modes – a phenomenon known as pogo. Pogo is a dynamic instability that can occur on a launch vehicle during any phase of ascent. During this investigation an end-to-end assessment of the Artemis-I Pogo-related DFI was performed to identify any obstacles inherent in the current instrumentation system which may prevent successful measurement of the data necessary to validate the current predictive models of the Main Propulsion System (MPS). Input drive signals were approximated and applied to a system-level SLS state-space model to derive predicted pressure and acceleration responses. These predicted responses were then fed through a simulation of the data acquisition process in order to recover predicted measurements. Finally, a mock Flight Data Analysis (FDA) was performed to assess the ability of these measurements to meet the Flight Test Objectives (FTO).

Adam Johnson↗
NASA NTRS1981

Preliminary analysis of STS-1 entry flight data

A preliminary analysis of data acquired during the first shuttle orbiter reentry is presented. Heating levels were higher than predicted. Variations in measured versus predicted lift to drag ratio and trim are discussed, as are plots showing time histories of control surface and jet activity. The confidence felt in the stability and control derivatives is only fair. Confidence in the derivatives extracted for Mach numbers below 3.5 is especially weak, because these derivatives were affected by sideslip data contaminated by wind and turbulence, nonindependent rudder motions, and buffet. The sources of the data used are described. Recommendations are presented for changes to the Aerodynamic Data Book, and for planning future flights.

Source record↗
NASA NTRS2022

PAAV Concept Document

The Pathfinding for Airspace with Autonomous Vehicles (PAAV) Concept Document, version 1.0, lays out the key challenges and potential solutions for the use of uncrewed aircraft (UA) technology for future regional air cargo operations. The challenges and solutions described in this document were informed by communications with the UA industry community (e.g., RTCA, the Federal Aviation Administration, and regional air cargo business operators), as well as the PAAV team’s research activities during the last two years including four tabletop exercises, a human-in-the-loop simulation study, a numerical simulation study, a functional allocation study, and flight data analysis (Appendix A). This document first describes the expected operational context of PAAV (Section 2), such as the flight mission, baseline UAS components, nominal operations, m:N operations (i.e., "m" remote pilots per "N" aircraft), and off-nominal operations. This context sets the scope for the PAAV concept development work. PAAV concept development assumes that UA operations will be increasingly autonomous. Thus, near- and far-term assumptions are defined (Section 3). PAAV identified seven key challenges for UA operations (Section 4): - Flight route planning - Separation and flow management - Traffic pattern integration - Contingency management - Taxi, takeoff, and landing - m:N operations - Communications operations The following 13 potential solutions to these challenges are then described (Section 5): - Scalable communications architecture - Data link - Designated UAS corridors - Crew planning for m:N operations - Flight route optimization - Traffic load-level control - Trajectory solutions with data link - Automated hazard avoidance for m:N operations - Traffic pattern integration (TPI) tool - Standard lost command and control (C2) link (LC2L) procedures - Automated hazard avoidance under LC2L - Auto-taxi, auto-takeoff, and auto-land - Ground control station (GCS) user interface for m:N operations The document attempts to link each of these solutions to one or more of the challenge areas. Novel solutions involving numerous automation technologies are needed to mitigate traffic and airspace management challenges, especially for realizing m:N operations and ensuring safety under LC2L conditions. The purpose of this document is to help understand alternatives and tradeoffs among potential solutions and provide a foundation for a cohesive PAAV concept that will be described and refined in subsequent concept versions.

Unmanned aircraft, uncrewed aircraft, regional air↗
NASA NTRS1994

BATSE Data Analysis

The four primary tasks of the Burst and Transient Source Experiment (BATSE) were completed. The Detector Response Matrices were maintained and some improvements implemented. The spectral analysis tasks based on the 4 channel lad data were accomplished. The BLOT team effort was completed and the SN1987A balloon flight data analysis paper was submitted.

Pendleton, Geoffrey N.↗
NASA NTRS2005

BEAM Technology Flight Demonstration

As technologies advance, their growing complexity makes them harder to maintain. Detection methods for isolating and identifying impending problems are needed to balance this complexity. Through comparison of signal pairs from onboard sensors, the Beacon-based Exception Analysis For Multimissions (BEAM) algorithm can identify and help classify deviations in system operation from a data-trained statistical model. The goal of this task is to mature BEAM and validate its performance on a flying test bed. A series of F-18 flight demonstrations with BEAM monitoring engine parameters in real time was used to demonstrate in-the-field readiness. Captured F-18 and simulated F-18 engine data were used in model creation and training. The algorithm was then ported to the embedded system with a data buffering, file writing, and data-time-stamp monitoring shell to reduce the impact of embedded system faults on BEAM'S ability to correctly identify engine faults. Embedded system testing identified hardware related restrictions and contributed to iterative improvements in the code's runtime performance. The system was flown with forced engine flameouts and other pilot induced faults to simulate operation out of the norm. Successful detection of these faults, confirmed through post-flight data analysis, helped BEAM achieve TRL6.

Wang, David↗
NASA NTRS1984

Estimated low-speed aerodynamic parameters of an advanced fighter from flight and wind tunnel data

A procedure for determination of aerodynamic model structure and estimation of aerodynamic parameters is applied to data from a modern fighter operating within an angle of attack range of 5 to 60 deg. The paper briefly describes the airplane, flight and wind tunnel data available, postulated models for airplane aerodynamic coefficients and flight data analysis. The results presented contain only a small number of selected longitudinal and lateral parameters. These parameters were obtained from various maneuvers and subsets of joined data from several flights. The estimated parameters are in good agreement with the wind tunnel measurements. The resulting aerodynamic model equations seem to be satisfactory for the prediction of airplane motion.

Klein, V.↗
NASA NTRS1978

Shuttle Entry Air Data System

The SEADS system (Shuttle Entry Air Data System) is being developed to provide research quality hypersonic (M greater than 3.5) air data. SEADS will accomplish this through the instrumentation of the orbiter's baseline nose cap. The SEADS development program consists of (1) the design and testing program required to define a reinforced carbon-carbon (RCC) nose cap penetration concept which will not degrade nose cap performance, (2) the definition of analytical techniques and design criteria for array definition and flight data analysis, (3) the verification of these analytical techniques and array criteria through a comprehensive wind-tunnel test program, (4) the demonstration of the system concept through detailed testing, and (5) the analyses and tests required to flight-certify the SEADS system.

Siemers, P. M., III↗