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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Performance analysis of a fault inferring nonlinear detection system algorithm with integrated avionics flight data

This paper presents the performance analysis results of a fault inferring nonlinear detection system (FINDS) using integrated avionics sensor flight data for the NASA ATOPS B-737 aircraft in a Microwave Landing System (MLS) environment. First, an overview of the FINDS algorithm structure is given. Then, aircraft state estimate time histories and statistics for the flight data sensors are discussed. This is followed by an explanation of modifications made to the detection and decision functions in FINDS to improve false alarm and failure detection performance. Next, the failure detection and false alarm performance of the FINDS algorithm are analyzed by injecting bias failures into fourteen sensor outputs over six repetitive runs of the five minutes of flight data. Results indicate that the detection speed, failure level estimation, and false alarm performance show a marked improvement over the previously reported simulation runs. In agreement with earlier results, detection speed is faster for filter measurement sensors such as MLS than for filter input sensors such as flight control accelerometers. Finally, the progress in modifications of the FINDS algorithm design to accommodate flight computer constraints is discussed.

Caglayan, A. K.↗
NASA NTRS2018

Display of Flight Interval Management Data

A system for providing flight interval management (FIM) instructions to a pilot of an aircraft includes a module coupled to a display device and configured to communicate with a FIM avionics device. The module generates a first output when input data from the FIM avionics device indicates that the aircraft is within 30 nautical miles of another aircraft, and a second input when a lack of valid input data indicates that the module has lost connectivity to the FIM avionics device. The first input is to the display device to present at least an indication of a paired mode of the module with the FIM avionics device, and a commanded speed reported by the FIM avionics device. The second output is to remove any information presented by the display device and present a blank screen, and then present a status message indicating the lost connectivity to the FIM avionics device.

Wilber, George↗
NASA NTRS1977

Solution to the Delta vehicle second stage pogo problem

A discussion of the pogo phenomenon observed on the Delta launch vehicle second stage is presented. The pressure-fed engine and the high frequency of the oscillation (125 Hz) required unique analysis and extensive testing to support analysis detail. In addition, the need to continue a one vehicle per month launch rate required both an immediate interim and a timely long-term solution to the problem. The development and implementation of a program involving analysis, ground test, and flight instrumentation is described. An analytical model was developed and used to investigate both structural and propulsion system modifications. The factors which influenced the final suppression system selection, the analytical predictions for that system, and flight data which validate that system's effectiveness are presented.

Markowitz, M.↗
NASA NTRS2012

Development of an Integrated Data Acquisition System for a Small Flight Probe

In support of the SPRITE concept, an integrated data acquisition system has been developed and fabricated for preliminary testing. The data acquisition system has been designed to condition traditional thermal protection system sensors, store their data to an on-board memory card, and in parallel, telemeter to an external system. In the fall of 2010, this system was integrated into a 14 in. diameter, 45 degree sphere cone probe instrumented with thermal protection system sensors. This system was then tested at the NASA Ames Research Center Aerodynamic Heating Facility's arc jet at approximately 170 W/sq. cm. The first test in December 2010 highlighted hardware design issues that were redesigned and implemented leading to a successful test in February 2011.

Swanson, Gregory T.↗
NASA NTRS2015

SSI-ARC Flight Test 3 Data Review

The "Unmanned Aircraft System (UAS) Integration into the National Airspace System (NAS)" Project conducted flight test program, referred to as Flight Test 3, at Armstrong Flight Research Center from June - August 2015. Four flight test days were dedicated to the NASA Ames-developed Detect and Avoid (DAA) System referred to as Autoresolver. The encounter scenarios, which involved NASA's Ikhana UAS and a manned intruder aircraft, were designed to collect data on DAA system performance in real-world conditions and uncertainties with four different surveillance sensor systems. Resulting flight test data and analysis results will be used to evaluate the DAA system performance (e.g., trajectory prediction accuracy, threat detection) and to add fidelity to simulation models used to inform Minimum Operating Performance Standards (MOPS) for integrating UAS into routine NAS operations.

detect and avoid↗
NASA NTRS1979

AIFTDS stand-alone RMDU flight test report

The remote multiplexer/digitizer unit for the airborne integrated flight test data system was subjected to a flight test environment in order to study its dynamic response and that of its associated instrumentation circuitry during an actual flight test. The shielding schemes and instrumentation used are described and the data obtained are analyzed.

Wilner, D. O.↗
NASA NTRS1981

The Development and Use of a Computer-Interactive Data Acquisition and Display System in a Flight Environment

The flight test data requirements at the NASA Dryden Flight Research Center increased in complexity, and more advanced instrumentation became necessary to accomplish mission goals. This paper describes the way in which an airborne computer was used to perform real-time calculations on critical flight test parameters during a flight test on a winglet-equipped KC-135A aircraft. With the computer, an airborne flight test engineer can select any sensor for airborne display in several formats, including engineering units. The computer is able to not only calculate values derived from the sensor outputs but also to interact with the data acquisition system. It can change the data cycle format and data rate, and even insert the derived values into the pulse code modulation (PCM) bit stream for recording.

Computer Systems↗
NASA NTRS1990

Evolution of the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) flight and ground data processing system

The modifications made to both the AVIRIS instrument and the data processing facility since the instrument made its initial flight in the summer of 1987 are described. Historical development of the data system is discussed and attention is given to enhancements to instrument stability and noise performance. AVIRIS data facility objectives include rapid and automated decommutation and archiving of data, the ability to assess the quality of the data and health of the instrument, and the provision of an automated procedure for applying radiometric corrections to the data and providing responsive processing of data requests from investigators. The modifications described have resulted in an overall radiometric stability of better than 10 percent, with stability of only a few percent during a single flight.

Porter, Wallace M.↗
NASA NTRS1992

Onboard System Processes SAR Data

Aircraft Flight Correlator (AFC) computing system, mounted with AIRSAR synthetic-aperture-radar (SAR) system, supplements recording and postflight analysis, processing portion of data in real or nearly real time to provide imagery for rapid evaluation. Facilitates diagnosis of SAR equipment or adjustment of parameters of experiment. Operates in two modes: "quick-look" mode, data processed in 10 minutes into high-resolution image; and "real-time" mode, data processed in real time to reduced resolution. Also used as aid to navigation.

Carande, Richard E.↗
NASA NTRS2014

SpaceCube v2.0 Space Flight Hybrid Reconfigurable Data Processing System

This paper details the design architecture, design methodology, and the advantages of the SpaceCube v2.0 high performance data processing system for space applications. The purpose in building the SpaceCube v2.0 system is to create a superior high performance, reconfigurable, hybrid data processing system that can be used in a multitude of applications including those that require a radiation hardened and reliable solution. The SpaceCube v2.0 system leverages seven years of board design, avionics systems design, and space flight application experiences. This paper shows how SpaceCube v2.0 solves the increasing computing demands of space data processing applications that cannot be attained with a standalone processor approach.The main objective during the design stage is to find a good system balance between power, size, reliability, cost, and data processing capability. These design variables directly impact each other, and it is important to understand how to achieve a suitable balance. This paper will detail how these critical design factors were managed including the construction of an Engineering Model for an experiment on the International Space Station to test out design concepts. We will describe the designs for the processor card, power card, backplane, and a mission unique interface card. The mechanical design for the box will also be detailed since it is critical in meeting the stringent thermal and structural requirements imposed by the processing system. In addition, the mechanical design uses advanced thermal conduction techniques to solve the internal thermal challenges.The SpaceCube v2.0 processing system is based on an extended version of the 3U cPCI standard form factor where each card is 190mm x 100mm in size The typical power draw of the processor card is 8 to 10W and scales with application complexity. The SpaceCube v2.0 data processing card features two Xilinx Virtex-5 QV Field Programmable Gate Arrays (FPGA), eight memory modules, a monitor FPGA with analog monitoring, Ethernet, configurable interconnect to the Xilinx FPGAs including gigabit transceivers, and the necessary voltage regulation. The processor board uses a back-to-back design methodology for common parts that maximizes the board real estate available. This paper will show how to meet the IPC 6012B Class 3A standard with a 22-layer board that has two column grid array devices with 1.0mm pitch. All layout trades such as stack-up options, via selection, and FPGA signal breakout will be discussed with feature size results. The overall board design process will be discussed including parts selection, circuit design, proper signal termination, layout placement and route planning, signal integrity design and verification, and power integrity results. The radiation mitigation techniques will also be detailed including configuration scrubbing options, Xilinx circuit mitigation and FPGA functional monitoring, and memory protection.Finally, this paper will describe how this system is being used to solve the extreme challenges of a robotic satellite servicing mission where typical space-rated processors are not sufficient enough to meet the intensive data processing requirements. The SpaceCube v2.0 is the main payload control computer and is required to control critical subsystems such as autonomous rendezvous and docking using a suite of vision sensors and object avoidance when controlling two robotic arms.

Xilinx FPGA↗
NASA NTRS1982

Modeling methodology for MLS range navigation system errors using flight test data

Flight test data was used to develop a methodology for modeling MLS range navigation system errors. The data used corresponded to the constant velocity and glideslope approach segment of a helicopter landing trajectory. The MLS range measurement was assumed to consist of low frequency and random high frequency components. The random high frequency component was extracted from the MLS range measurements. This was done by appropriate filtering of the range residual generated from a linearization of the range profile for the final approach segment. This range navigation system error was then modeled as an autoregressive moving average (ARMA) process. Maximum likelihood techniques were used to identify the parameters of the ARMA process.

Karmali, M. S.↗
NASA NTRS1982

Thematic mapper flight model preshipment review data package. Volume 3, part C: System data

Failure reports for flight model-1 of the thematic mapper are summarized showing the symptom and cause of failure as well as the corrective action taken. Each report is keyed to the major subsystem against which the failure occurred. Requests for deviation/waiver are listed by number, description, and current status. Copies of engineering proposals are included.

Source record↗
NASA NTRS2019

Airspace Technology Demonstration 2 (ATD-2) Phase 2 Technology Description Document (TDD)

This Technology Description Document (TDD) provides an overview of the technology for the Phase 1 Baseline and Phase 2 Fused demonstrations of the Integrated Arrival, Departure, and Surface (IADS) prototype system of the National Aeronautics and Space Administration’s (NASA) Airspace Technology Demonstration 2 (ATD-2) project, which has been demonstrated since October of 2017 at Charlotte Douglas International Airport (CLT). Development, integration, and field demonstration of relevant technologies of the IADS system directly address recommendations made by the Next Generation Air Transportation System (NextGen) Integration Working Group (NIWG) on Surface and Data Sharing and the Surface Collaborative Decision Making (Surface CDM) concept of operations developed jointly by the Federal Aviation Administration (FAA) and aviation industry partners. NASA has been developing the IADS traffic management system under the ATD-2 project in coordination with the FAA, flight operators, CLT airport operators, and the National Air Traffic Controllers Association (NATCA). The primary goal of ATD-2 is to improve the predictability and 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 project is a 5-year research activity beginning in 2015 and extending through 2020. The Phase 1 Baseline IADS capability resulting from the ATD-2 research has been demonstrated at the CLT airport since the beginning of October 2017. Phase 1 provided data exchange and integration with the initial demonstration of the integrated system of strategic and tactical scheduling, collaborative tactical surface metering, tactical departure scheduling to an en route meter point and overhead stream insertion, initial integration of a TFDM SWIM prototype feed, and an early implementation prototype of a Terminal Flight Data Manager (TFDM) Electronic Flight Data (EFD) system. The strategic surface scheduling element of the capability is consistent with the Surface CDM Concept of Operations published in 2014 by the FAA Surface Operations Directorate.1 The Phase 2 Fused IADS system provided substantial updates to baseline IADS Demonstration capability. Improvements were made to the IADS modeler; tactical surface scheduling, and metering; tactical departure scheduling for overhead stream insertion; Electronic Flight Data (EFD) and the integration with the FAA Advanced Electronic Flight Strip (AEFS); RTC/RMTC, and departure trajectories. New capabilities included a TFDM SWIM prototype feed and delivery of IADS data via the TFDM Terminal Publication (TTP) service of the FAA’s SWIM system; strategic surface scheduling and metering as well as fusion with tactical surface metering; integration and ingestion of data from TTP-connected Mobile App and texting industry for General Aviation (GA) flights; and expansion of airspace deployments to include adjacent Center automation, in particular interface with the Atlanta Center (ZTL) arrival metering TBFM system to evaluate pre-scheduling of flights. Improvements in Data Analysis and System Health (DASH) monitoring and updates were completed as well.

Talebi, Ehsan↗
NASA NTRS1980

Helicopter sling loads

Computer program compares various control-system concepts for improving handling qualities of single-rotor helicopters carrying relatively-large external sling loads. Computer program developed to test these and other ideas helps to circumvent expensive prototype and field testing. Comparisons between (1) computed data and flight data, (2) simulation-system values and flight test data, and (3) pilot evaluations of simulation and actual-flight conditions are very favorable.

Shaughnessy, J. D.↗
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.↗