Results for “vehicle data quality” — Page 2

NASA NTRSDate not supplied

Augmenting the Space Environment Complex's Thermal Vacuum Capabilities for Artemis 1 Orion Spacecraft Testing

The Space Environments Complex at Glenn Research Center’s Neil A Armstrong Test Facility (formerly Plum Brook Station) recently successfully completed Artemis 1 thermal vacuum testing. The Space Environments Complex boasts the world’s largest thermal vacuum chamber with a 122-foot tall, 100-foot diameter aluminum assembly vacuum chamber. The fifty-year old chamber has been adapted over its history to conduct several unique test campaigns in a variety of test environments. Artemis 1 Orion spacecraft testing is the most complex test campaign the Space Environments Complex has undergone to date, with temperature limits between -250 F to +300F in a high vacuum with significant requirements for quality data and contamination control of a flight vehicle. This presentation covers the improvements and innovations in the cryoshroud and thermal systems, data acquisition, as well as contamination and cleanliness to accommodate the rigors of a flight vehicle during a six-week thermal vacuum test. Additionally, the presentation covers successes and lessons learned from the testing.

Erin Reed↗

NASA NTRSDate not supplied

NASA Armstrong Flight Research Center Dynamics and Controls (530)

AFRC Controls and Dynamics Branch - Research Areas: - Traditional GN&C - Classical and advanced control algorithms - Risk based approaches for safety critical applications - Integration of novel sensors and sensor fusion (FOSS, LIDAR, etc.) - Trajectory optimization and control - Flight/System Dynamics - Equations of Motion and integrated modeling of vehicles and vehicle systems - Unique and novel vehicle dynamics - Methods for extracting relevant vehicle dynamic information from flight data - Human and vehicle interfaces and interactions - Handling Qualities and Pilot-in-the-loop oscillations (PIO) predictions and design metrics - Ride quality research - Autonomy - Novel algorithms, sensors, and sensor fusion - Bounding risk for testing automated systems - Pilot/Operator interactions - Engineering Support and Airworthiness Assessments - Aircraft modifications and experimental configurations

Chris Miller↗

NASA NTRS2015

Quality Control of Wind Data from 50-MHz Doppler Radar Wind Profiler

Upper-level wind profiles obtained from a 50-MHz Doppler Radar Wind Profiler (DRWP) instrument at Kennedy Space Center are incorporated in space launch vehicle design and day-of-launch operations to assess wind effects on the vehicle during ascent. Automated and manual quality control (QC) techniques are implemented to remove spurious data in the upper-level wind profiles caused from atmospheric and non-atmospheric artifacts over the 2010-2012 period of record (POR). By adding the new quality controlled profiles with older profiles from 1997-2009, a robust database will be constructed of upper-level wind characteristics. Statistical analysis will determine the maximum, minimum, and 95th percentile of the wind components from the DRWP profiles over recent POR and compare against the older database. Additionally, this study identifies specific QC flags triggered during the QC process to understand how much data is retained and removed from the profiles.

Vacek, Austin D.↗

NASA NTRS2015

Quality Control of Wind Data from 50-MHz Doppler Radar Wind Profiler

Upper-level wind profiles obtained from a 50-MHz Doppler Radar Wind Profiler (DRWP) instrument at Kennedy Space Center are incorporated in space launch vehicle design and day-of-launch operations to assess wind effects on the vehicle during ascent. Automated and manual quality control (QC) techniques are implemented to remove spurious data in the upper-level wind profiles caused from atmospheric and non-atmospheric artifacts over the 2010-2012 period of record (POR). By adding the new quality controlled profiles with older profiles from 1997-2009, a robust database will be constructed of upper-level wind characteristics. Statistical analysis will determine the maximum, minimum, and 95th percentile of the wind components from the DRWP profiles over recent POR and compare against the older database. Additionally, this study identifies specific QC flags triggered during the QC process to understand how much data is retained and removed from the profiles.

Vacek, Austin↗

NASA NTRS2016

Quality Control of Wind Data from 50-MHz Doppler Radar Wind Profiler

Upper-level wind profiles obtained from a 50-MHz Doppler Radar Wind Profiler (DRWP) instrument at Kennedy Space Center are incorporated in space launch vehicle design and day-of-launch operations to assess wind effects on the vehicle during ascent. Automated and manual quality control (QC) techniques are implemented to remove spurious data in the upper-level wind profiles caused from atmospheric and non-atmospheric artifacts over the 2010-2012 period of record (POR). By adding the new quality controlled profiles with older profiles from 1997-2009, a robust database will be constructed of upper-level wind characteristics. Statistical analysis will determine the maximum, minimum, and 95th percentile of the wind components from the DRWP profiles over recent POR and compare against the older database. Additionally, this study identifies specific QC flags triggered during the QC process to understand how much data is retained and removed from the profiles.

Vacek, Austin↗

NASA NTRS2015

Data Applicability of Heritage and New Hardware for Launch Vehicle System Reliability Models

Many launch vehicle systems are designed and developed using heritage and new hardware. In most cases, the heritage hardware undergoes modifications to fit new functional system requirements, impacting the failure rates and, ultimately, the reliability data. New hardware, which lacks historical data, is often compared to like systems when estimating failure rates. Some qualification of applicability for the data source to the current system should be made. Accurately characterizing the reliability data applicability and quality under these circumstances is crucial to developing model estimations that support confident decisions on design changes and trade studies. This presentation will demonstrate a data-source classification method that ranks reliability data according to applicability and quality criteria to a new launch vehicle. This method accounts for similarities/dissimilarities in source and applicability, as well as operating environments like vibrations, acoustic regime, and shock. This classification approach will be followed by uncertainty-importance routines to assess the need for additional data to reduce uncertainty.

Al Hassan Mohammad↗

NASA NTRS2018

Sensor Data Quality and Angular Rate Down-Selection Algorithms on SLS EM-1

The NASA Space Launch System Block 1 launch vehicle is equipped with an Inertial Navigation System (INS) and multiple Rate Gyro Assemblies (RGA) that are used in the Guidance, Navigation, and Control (GN&C) algorithms. The INS provides the inertial position, velocity, and attitude of the vehicle along with both angular rate and specific force measurements. Additionally, multiple sets of co-located rate gyros supply angular rate data. The collection of angular rate data, taken along the launch vehicle, is used to separate out vehicle motion from flexible body dynamics. Since the system architecture uses redundant sensors, the capability was developed to evaluate the health (or validity) of the independent measurements. A suite of Sensor Data Quality (SDQ) algorithms is responsible for assessing the angular rate data from the redundant sensors. When failures are detected, SDQ will take the appropriate action and disqualify or remove faulted sensors from forward processing. Additionally, the SDQ algorithms contain logic for down-selecting the angular rate data used by the GNC software from the set of healthy measurements. This paper explores the trades and analyses that were performed in selecting a set of robust fault-detection algorithms included in the GN&C flight software. These trades included both an assessment of hardware-provided health and status data as well as an evaluation of different algorithms based on time-to-detection, type of failures detected, and probability of detecting false positives. We then provide an overview of the algorithms used for both fault-detection and measurement down selection. We next discuss the role of trajectory design, flexible-body models, and vehicle response to off-nominal conditions in setting the detection thresholds. Lastly, we present lessons learned from software integration and hardware-in-the-loop testing.

Park, Thomas↗

NASA NTRS2012

Jet-Surface Interaction Test: Far-Field Noise Results

Many configurations proposed for the next generation of aircraft rely on the wing or other aircraft surfaces to shield the engine noise from the observers on the ground. However, the ability to predict the shielding effect and any new noise sources that arise from the high-speed jet flow interacting with a hard surface is currently limited. Furthermore, quality experimental data from jets with surfaces nearby suitable for developing and validating noise prediction methods are usually tied to a particular vehicle concept and, therefore, very complicated. The Jet/Surface Interaction Test was intended to supply a high quality set of data covering a wide range of surface geometries and positions and jet flows to researchers developing aircraft noise prediction tools. During phase one, the goal was to measure the noise of a jet near a simple planar surface while varying the surface length and location in order to: (1) validate noise prediction schemes when the surface is acting only as a jet noise shield and when the jet/surface interaction is creating additional noise, and (2) determine regions of interest for more detailed tests in phase two. To meet these phase one objectives, a flat plate was mounted on a two-axis traverse in two distinct configurations: (1) as a shield between the jet and the observer (microphone array) and (2) as a reflecting surface on the opposite side of the jet from the observer.

Brown, Clifford A.↗

NASA NTRS2018

Sensor Data Quality and Angular Rate Down-Selection Algorithms on SLS EM-1

The NASA Space Launch System Block 1 launch vehicle is equipped with an Inertial Navigation System (INS) and multiple Rate Gyro Assemblies (RGA) that are used in the Guidance, Navigation, and Control (GN&C) algorithms. The INS provides the inertial position, velocity, and attitude of the vehicle along with both angular rate and specific force measurements. Additionally, multiple sets of co-located rate gyros supply angular rate data. The collection of angular rate data, taken along the launch vehicle, is used to separate out vehicle motion from flexible body dynamics. Since the system architecture uses redundant sensors, the capability was developed to evaluate the health (or validity) of the independent measurements. A suite of Sensor Data Quality (SDQ) algorithms is responsible for assessing the angular rate data from the redundant sensors. When failures are detected, SDQ will take the appropriate action and disqualify or remove faulted sensors from forward processing. Additionally, the SDQ algorithms contain logic for down-selecting the angular rate data used by the GN&C software from the set of healthy measurements. This paper provides an overview of the algorithms used for both fault-detection and measurement down selection.

Park, Thomas↗

NASA NTRS1983

Development of a flight test maneuver autopilot for a highly maneuverable aircraft

This paper details the development of a flight test maneuver autopilot for a highly maneuverable aircraft. This newly developed flight test technique is being applied at the Dryden Flight Research Facility of the NASA Ames Research Center. The flight test maneuver autopilot (FTMAP) is designed to increase the quantity and quality of the data obtained in flight test. The vehicle with which it is being used is the highly maneuverable aircraft technology (HiMAT) vehicle. This paper describes the HiMAT vehicle systems, maneuver requirements, FTMAP development process, and flight results.

Duke, E. L.↗

NASA NTRS1975

University of Virginia acquisition of passenger ride quality data aboard the Total In-Flight Simulator (TIFS)

The subjective response of passengers to vehicle motions was investigated on the Total In-Flight Simulator (TIFS) aircraft. Prerecorded signals were converted into controlled aircraft motion for evaluation by ten subjects on a seven-point rating scale. Eighteen test flights were flown on August and September 1974, the results of which are to be used in validation studies on ground based simulators at NASA/Langley Research Center and to extend passenger response models.

Mcclurken, E. W., Jr.↗

NASA NTRS1980

Propulsion system research and development for electric and hybrid vehicles

An approach to propulsion subsystem technology is presented. Various tests of component reliability are described to aid in the production of better quality vehicles. component characterization work is described to provide engineering data to manufacturers on component performance and on important component propulsion system interactions.

Schwartz, H. J.↗

NASA NTRS1975

X-24B flight test program

The X-24B is an air launched, rocket powered research aircraft. A number of its design features constitute a tradeoff between aerodynamics and heating considerations. A vehicle description is given and test program objectives are discussed along with operational procedures and aspects of energy management. Attention is also given to X-24B handling qualities, approach and landing, wind tunnel data and simulation, and proposed X-24C vehicle requirements.

Manke, J. A.↗

NASA NTRS2014

Acoustics Research of Propulsion Systems

The liftoff phase induces some of the highest acoustic loading over a broad frequency for a launch vehicle. These external acoustic environments are used in the prediction of the internal vibration responses of the vehicle and components. Thus, predicting these liftoff acoustic environments is critical to the design requirements of any launch vehicle but there are challenges. Present liftoff vehicle acoustic environment prediction methods utilize stationary data from previously conducted hold-down tests; i.e. static firings conducted in the 1960's, to generate 1/3 octave band Sound Pressure Level (SPL) spectra. These data sets are used to predict the liftoff acoustic environments for launch vehicles. To facilitate the accuracy and quality of acoustic loading, predictions at liftoff for future launch vehicles such as the Space Launch System (SLS), non-stationary flight data from the Ares I-X were processed in PC-Signal in two forms which included a simulated hold-down phase and the entire launch phase. In conjunction, the Prediction of Acoustic Vehicle Environments (PAVE) program was developed in MATLAB to allow for efficient predictions of sound pressure levels (SPLs) as a function of station number along the vehicle using semiempirical methods. This consisted, initially, of generating the Dimensionless Spectrum Function (DSF) and Dimensionless Source Location (DSL) curves from the Ares I-X flight data. These are then used in the MATLAB program to generate the 1/3 octave band SPL spectra. Concluding results show major differences in SPLs between the hold-down test data and the processed Ares IX flight data making the Ares I-X flight data more practical for future vehicle acoustic environment predictions.

Gao, Ximing↗

NASA NTRS1982

Signalling characteristics in satellite-aided land mobile communications

The feasibility of land mobile radio communications has been demonstrated by a large number of experiments with NASA's ATS satellites. Significant differences in the propagation characteristics of satellite and terrestrial mobile signal paths were observed in the experiments. Terrestrial paths are best in cities where they can provide frequency reuse and assure communication by bouncing signals around obstructions. Satellites may be best in thinly populated areas because they eliminate the need for many tower mounted relays. The satellite paths do not have the severe Rayleigh fading that limits the range and signal quality of terrestrial paths if the satellite is above approximately ten degrees elevation, a value easily achieved for the United States. The experiments verified that high quality voice communications and other functions, such as data transmission and vehicle position surveillance, are easily accomplished through geostationary satellites with vehicle transmitter power and antenna gain no different than those of terrestrial mobile communications.

Anderson, R. E.↗

NASA NTRS1992

6th AIAA Biennial Flight Test Conference, Hilton Head Island, SC, Aug. 24-26, 1992, Selected Papers

Topics presented include training for avionics evaluation, flight testing in the '90s, methodology for the critical evaluation of flight test data, flight testing of an electric powered vehicle, and the flying qualities of a remotely piloted vehicle. Also presented are airspeed calibration using GPS, the design and conduct of a windshear detection flight experiment, the 757 fly-by-wire demonstrator flight test, and an update of the B-52 flight test program.

American Institute of Aeronautics and Astronautics↗

NASA NTRS2006

Development of a Low-Cost Sub-Scale Aircraft for Flight Research: The FASER Project

An inexpensive unmanned sub-scale aircraft was developed to conduct frequent flight test experiments for research and demonstration of advanced dynamic modeling and control design concepts. This paper describes the aircraft, flight systems, flight operations, and data compatibility including details of some practical problems encountered and the solutions found. The aircraft, named Free-flying Aircraft for Sub-scale Experimental Research, or FASER, was outfitted with high-quality instrumentation to measure aircraft inputs and states, as well as vehicle health parameters. Flight data are stored onboard, but can also be telemetered to a ground station in real time for analysis. Commercial-off-the-shelf hardware and software were used as often as possible. The flight computer is based on the PC104 platform, and runs xPC-Target software. Extensive wind tunnel testing was conducted with the same aircraft used for flight testing, and a six degree-of-freedom simulation with nonlinear aerodynamics was developed to support flight tests. Flight tests to date have been conducted to mature the flight operations, validate the instrumentation, and check the flight data for kinematic consistency. Data compatibility analysis showed that the flight data are accurate and consistent after corrections are made for estimated systematic instrumentation errors.

Owens, Donald B.↗

NASA NTRS1984

Space shuttle flying qualities criteria assessment, phase 3

The crucial flight data measurement and reduction techniques required for the experimental approach are explored. An overview of available flight data is presented, identification of the effective augmented vehicle and pilot models determined, a summary of flight data problems compiled, and further recommendations for the Orbiter Flying Qualities (OFQ) experiment provided.

Myers, T. T.↗