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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

F-15B QuietSpike(TradeMark) Aeroservoelastic Flight Test Data Analysis

System identification or mathematical modelling is utilised in the aerospace community for the development of simulation models for robust control law design. These models are often described as linear, time-invariant processes and assumed to be uniform throughout the flight envelope. Nevertheless, it is well known that the underlying process is inherently nonlinear. The reason for utilising a linear approach has been due to the lack of a proper set of tools for the identification of nonlinear systems. Over the past several decades the controls and biomedical communities have made great advances in developing tools for the identification of nonlinear systems. These approaches are robust and readily applicable to aerospace systems. In this paper, we show the application of one such nonlinear system identification technique, structure detection, for the analysis of F-15B QuietSpike(TradeMark) aeroservoelastic flight test data. Structure detection is concerned with the selection of a subset of candidate terms that best describe the observed output. This is a necessary procedure to compute an efficient system description which may afford greater insight into the functionality of the system or a simpler controller design. Structure computation as a tool for black-box modelling may be of critical importance for the development of robust, parsimonious models for the flight-test community. Moreover, this approach may lead to efficient strategies for rapid envelope expansion which may save significant development time and costs. The objectives of this study are to demonstrate via analysis of F-15B QuietSpike(TradeMark) aeroservoelastic flight test data for several flight conditions (Mach number) that (i) linear models are inefficient for modelling aeroservoelastic data, (ii) nonlinear identification provides a parsimonious model description whilst providing a high percent fit for cross-validated data and (iii) the model structure and parameters vary as the flight condition is altered.

Kukreja, Sunil L.↗
NASA NTRS1983

An assessment of the Space Shuttle Orbiter thermal environment using flight data

A unified analysis of the Shuttle Orbiter aerothermodynamic environment and thermal protection system performance is presented using the Space Transportation System development flight data. Comparisons of predicted and measured temperatures and heating rates along the Orbiter lower windward fuselage centerline and lower wing 50 percent and 80 percent semi-spans are discussed. The results of this study indicate lower than predicted heating on windward fuselage surface but higher heating on the nose cap and 50 percent semi-span wing panels.

Williams, S. D.↗
NASA NTRS2018

Airspace Technology Demonstration 2 (ATD-2) Phase 1 Concept of Use (ConUse)

This document presents an operational Concept of Use (ConUse) for the Phase 1 Baseline Integrated Arrival, Departure, and Surface (IADS) prototype system of NASA's Airspace Technology Demonstration 2 (ATD-2) sub-project, which began demonstration in 2017 at Charlotte Douglas International Airport (CLT). NASA is developing the IADS system under the ATD-2 sub-project in coordination with the Federal Aviation Administration (FAA) and aviation industry partners. The primary goal of ATD-2 sub-project is to improve the predictability and the operational efficiency of the air traffic system in metroplex environments, through the enhancement, development, and integration of the nation's most advanced and sophisticated arrival, departure, and surface prediction, scheduling, and management systems. The ATD-2 effort is a five-year research activity through 2020. The initial phase of the ATD-2 sub-project, which is the focus of this document, will demonstrate the Phase 1 Baseline IADS capability at CLT in 2017. The Phase 1 Baseline IADS capabilities of the ATD-2 sub-project consists of: (a) Strategic and tactical surface scheduling to improve efficiency and predictability of airport surface operations, (b) Tactical departure scheduling to enhance merging of departures into overhead traffic streams via accurate predictions of takeoff times and automated coordination between the Airport Traffic Control Tower (ATCT, or Tower) and the Air Route Traffic Control Center (ARTCC, or Center), (c) Improvements in departure surface demand predictions in Time Based Flow Management (TBFM), (d) A prototype Electronic Flight Data (EFD) system provided by the FAA via the Terminal Flight Data Manager (TFDM) early implementation effort, and (e) Improved situational awareness and demand predictions through integration with the Traffic Flow Management System (TFMS), TBFM, and TFDM (3Ts) for electronic data integration and exchange, and an on-screen dashboard displaying pertinent analytics in real-time. The surface scheduling and metering element of the capability is consistent with the Surface CDM Concept of Operations published in 2014 by the FAA Surface Operations Directorate.1 Upon successful demonstration of the Phase 1 Baseline IADS capability, follow-on demonstrations of the matured IADS traffic management capabilities will be conducted in the 2018-2020 timeframe. At the end of each phase of the demonstrations, NASA will transfer the ATD-2 sub-project technology to the FAA and industry partners.

integrated arrival↗
NASA NTRS2010

Data Acquisition System for Multi-Frequency Radar Flight Operations Preparation

A three-channel data acquisition system was developed for the NASA Multi-Frequency Radar (MFR) system. The system is based on a commercial-off-the-shelf (COTS) industrial PC (personal computer) and two dual-channel 14-bit digital receiver cards. The decimated complex envelope representations of the three radar signals are passed to the host PC via the PCI bus, and then processed in parallel by multiple cores of the PC CPU (central processing unit). The innovation is this parallelization of the radar data processing using multiple cores of a standard COTS multi-core CPU. The data processing portion of the data acquisition software was built using autonomous program modules or threads, which can run simultaneously on different cores. A master program module calculates the optimal number of processing threads, launches them, and continually supplies each with data. The benefit of this new parallel software architecture is that COTS PCs can be used to implement increasingly complex processing algorithms on an increasing number of radar range gates and data rates. As new PCs become available with higher numbers of CPU cores, the software will automatically utilize the additional computational capacity.

Leachman, Jonathan↗
NASA NTRS2005

Analysis of Wallops Flight Test Data Through an Automated COTS System

During the summer of 2004 NASA Langley Research Center flight tested a Synthetic Vision System (SVS) at the Reno/Tahoe International Airport (RNO) and the Wallops Flight Facility (WAL). The SVS included a Runway Incursion Prevention System (RIPS) to improve pilot situational awareness while operating near and on the airport surface. The flight tests consisted of air and ground operations to evaluate and validate the performance of the system. This paper describes the flight test and emphasizes how positioning data was collected, post processed and analyzed through the use of a COTS-derived software system. The system that was developed to analyze the data was constructed within the MATLAB(TM) environment. The software was modified to read the data, perform several if-then scenarios and produce the relevant graphs, figures and tables.

Blackstock, Dexter Lee↗
NASA NTRS2007

F-15B Quiet Spike(TradeMark) Aeroservoelastic Flight-Test Data Analysis

System identification is utilized in the aerospace community for development of simulation models for robust control law design. These models are often described as linear, time-invariant processes and assumed to be uniform throughout the flight envelope. Nevertheless, it is well known that the underlying process is inherently nonlinear. Over the past several decades the controls and biomedical communities have made great advances in developing tools for the identification of nonlin ear systems. In this report, we show the application of one such nonlinear system identification technique, structure detection, for the an alysis of Quiet Spike(TradeMark)(Gulfstream Aerospace Corporation, Savannah, Georgia) aeroservoelastic flight-test data. Structure detectio n is concerned with the selection of a subset of candidate terms that best describe the observed output. Structure computation as a tool fo r black-box modeling may be of critical importance for the development of robust, parsimonious models for the flight-test community. The ob jectives of this study are to demonstrate via analysis of Quiet Spike(TradeMark) aeroservoelastic flight-test data for several flight conditions that: linear models are inefficient for modelling aeroservoelast ic data, nonlinear identification provides a parsimonious model description whilst providing a high percent fit for cross-validated data an d the model structure and parameters vary as the flight condition is altered.

Kukreja, Sunil L.↗
NASA NTRS2010

An Analytical Explanation for the X-43A Flush Air Data Sensing System Pressure Mismatch Between Flight and Theory

Following the successful Mach 7 flight test of the X-43A, unexpectedly low pressures were measured by the aft set of the onboard Flush Air Data Sensing System s pressure ports. These in-flight aft port readings were significantly lower below Mach 3.5 than was predicted by theory. The same lower readings were also seen in the Mach 10 flight of the X-43A and in wind-tunnel data. The pre-flight predictions were developed based on 2-dimensional wedge flow, which fails to predict some of the significant 3-dimensional flow features in this geometry at lower Mach numbers. Using Volterra s solution to the wave equation as a starting point, a three-dimensional finite wedge approximation to flow over the X-43A forebody is presented. The surface pressures from this approximation compare favorably with the measured wind tunnel and flight data at speeds of Mach 2.5 and 3.

Ellsworth, Joel C.↗
NASA NTRS1982

A portable, low-cost flight-data measurement and recording system

The design of and the experience with an inexpensive, hand-portable, onboard data system used to record four parameters in the final portion of the landing approach and touchdown of an airplane are described. The system utilized a high-quality audio tape recorder and amateur photographic equipment with accessory circuitry rather than specialized instrumentation to given satisfactory results.

Miller, R. J.↗
NASA NTRS1992

Linearized aerodynamic and control law models of the X-29A airplane and comparison with flight data

Flight control system design and analysis for aircraft rely on mathematical models of the vehicle dynamics. In addition to a six degree of freedom nonlinear simulation, the X-29A flight controls group developed a set of programs that calculate linear perturbation models throughout the X-29A flight envelope. The models include the aerodynamics as well as flight control system dynamics and were used for stability, controllability, and handling qualities analysis. These linear models were compared to flight test results to help provide a safe flight envelope expansion. A description is given of the linear models at three flight conditions and two flight control system modes. The models are presented with a level of detail that would allow the reader to reproduce the linear results if desired. Comparison between the response of the linear model and flight measured responses are presented to demonstrate the strengths and weaknesses of the linear models' ability to predict flight dynamics.

Bosworth, John T.↗
NASA NTRS1992

A real time data acquisition system using the MIL-STD-1553B bus

A flight digital data acquisition system that uses the MIL-STD-1553B bus for transmission of data to a host computer for control law processing is described. The instrument, the Remote Interface Unit (RIU), can accommodate up to 16 input channels and eight output channels. The RIU employs a digital signal processor to perform local digital filtering before sending data to the host. The system allows flexible sensor and actuator data organization to facilitate quick control law computations on the host computer. The instrument can also run simple control laws autonomously without host intervention. The RIU and host computer together have replaced a similar larger, ground minicomputer system with favorable results.

Peri, Frank, Jr.↗
NASA NTRS1985

Evaluation of a fault tolerant system for an integrated avionics sensor configuration with TSRV flight data

The performance analysis results of a fault inferring nonlinear detection system (FINDS) using sensor flight data for the NASA ATOPS B-737 aircraft in a Microwave Landing System (MLS) environment is presented. First, a statistical analysis of the flight recorded sensor data was made in order to determine the characteristics of sensor inaccuracies. Next, modifications were made to the detection and decision functions in the FINDS algorithm in order to improve false alarm and failure detection performance under real modelling errors present in the flight data. Finally, the failure detection and false alarm performance of the FINDS algorithm were analyzed by injecting bias failures into fourteen sensor outputs over six repetitive runs of the five minute flight data. In general, the detection speed, failure level estimation, and false alarm performance showed a marked improvement over the previously reported simulation runs. In agreement with earlier results, detection speed was faster for filter measurement sensors soon as MLS than for filter input sensors such as flight control accelerometers.

Caglayan, A. K.↗
NASA NTRS1972

An evaluation of flight data for the Apollo thermal protection system

A study was conducted to correlate Apollo ablation and thermal response flight data using advanced state-of-the-art analytical procedures. The agreement between flight data and predictions is consistently excellent for in-depth temperature distributions, char density profiles, and surface ablation, thus validating the analytical procedures.

Bartlett, E. P.↗
NASA NTRS2011

Space Environments Testbed

The Space Environments Testbed (SET) is a flight controller data system for the Common Carrier Assembly. The SET-1 flight software provides the command, telemetry, and experiment control to ground operators for the SET-1 mission. Modes of operation (see dia gram) include: a) Boot Mode that is initiated at application of power to the processor card, and runs memory diagnostics. It may be entered via ground command or autonomously based upon fault detection. b) Maintenance Mode that allows for limited carrier health monitoring, including power telemetry monitoring on a non-interference basis. c) Safe Mode is a predefined, minimum power safehold configuration with power to experiments removed and carrier functionality minimized. It is used to troubleshoot problems that occur during flight. d) Operations Mode is used for normal experiment carrier operations. It may be entered only via ground command from Safe Mode.

Leucht, David K.↗
NASA NTRS2007

Design of a Mission Data Storage and Retrieval System for NASA Dryden Flight Research Center

The Western Aeronautical Test Range (WATR) at the NASA Dryden Flight Research Center (DFRC) employs the WATR Integrated Next Generation System (WINGS) for the processing and display of aeronautical flight data. This report discusses the post-mission segment of the WINGS architecture. A team designed and implemented a system for the near- and long-term storage and distribution of mission data for flight projects at DFRC, providing the user with intelligent access to data. Discussed are the legacy system, an industry survey, system operational concept, high-level system features, and initial design efforts.

Lux, Jessica↗
NASA NTRS2007

Design of a Mission Data Storage and Retrieval System for NASA Dryden Flight Research Center

The Western Aeronautical Test Range (WATR) at the NASA Dryden Flight Research Center (DFRC) employs the WATR Integrated Next Generation System (WINGS) for the processing and display of aeronautical flight data. This report discusses the post-mission segment of the WINGS architecture. A team designed and implemented a system for the near- and long-term storage and distribution of mission data for flight projects at DFRC, providing the user with intelligent access to data. Discussed are the legacy system, an industry survey, system operational concept, high-level system features, and initial design efforts.

Lux, Jessica↗