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At least 595 records · Page 33

Comparisons of AEROX computer program predictions of lift and induced drag with flight test data

The AEROX aerodynamic computer program which provides accurate predictions of induced drag and trim drag for the full angle of attack range and for Mach numbers from 0.4 to 3.0 is described. This capability is demonstrated comparing flight test data and AEROX predictions for 17 different tactical aircraft. Values of minimum (skin friction, pressure, and zero lift wave) drag coefficients and lift coefficient offset due to camber (when required) were input from the flight test data to produce total lift and drag curves. The comparisons of trimmed lift drag polars show excellent agreement between the AEROX predictions and the in flight measurements.

Axelson, J.↗

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↗

Assessment of Next Generation Airframe Noise Prediction Methods with PAA and ASN Flight Test Data

This paper presents an assessment of the airframe noise prediction capability in the research version of the NASA Aircraft Noise Prediction Program (ANOPP) with the objective of validating the accuracy of the current prediction methods, and more importantly, identifying the potential improvements to update the methods. The assessment compares predictions of the individual noise components currently implemented in ANOPP, including the landing gear, the slat, the flap, and the trailing edge noise, with the data from the Propulsion Airframe Aeroacoustics and Aircraft System Noise flight test conducted as part of the Boeing 2020 ecoDemonstrator program on a Boeing 787-10 Etihad Airways aircraft. For each component, prediction errors and discussions are presented for the noise characteristics, covering not only the source features but also the installation effects. It is shown that the predictions by the research level methods in ANOPP capture the major noise features, but improvement potential is identified in two main categories. The first includes minor features that have not been sufficiently modeled in the current methods, the noise due to interactions of the landing gear wake with the flaps and the slat bracket noise, for example. The second is related to changes in modern aircraft designs, which may alter the noise source mechanisms, and thus, calls for major improvements and updates on the current prediction models, examples including the flap side edge noise for modern flap systems and the trailing edge noise for realistic wings with taper and sweep. To illustrate the progress of the method development, previous generations of airframe noise models in ANOPP are also compared with the flight test data.

Yueping Guo↗

Software Tool for Tracking & Mapping the NASA Orion AA-2 Test Flight Ejectable Data Recorders in Real Time

On 2 July 2019, the NASA Ascent Abort 2 flight took place off the Florida coast to test the emergency systems to separate the Orion Crew Module (CM) from the future Space Launch System rocket in the event of a malfunction. During this high-altitude test, instrumentation data was recorded on twelve customized buoyant Ejectable Data Recorders (EDRs) and subsequently jettisoned from the CM in mid-air. Upon release, the EDRs activated their GPS-Iridium beacon systems and began transmitting Short Burst Data (SBD) messages via the Iridium satellite network to relay their individual location and system health information. To locate, track and retrieve each EDR from the ocean surface in real-time, multiple open-source programming tools (Python and Linux shells) were developed for parsing the incoming Iridium binary SBD messages. For this, a Linux laptop was used to receive the Iridium-generated emails containing the SBD messages and autonomously execute the parsing tools. The received SBD data contained location, timestamp and health status information that was translated, saved, and subsequently used for simultaneously generating a continuously updated color-coded tabular display summary and unique KML files used with Google Earth to track their locations. Once their locations were known, dedicated recovery vessels retrieved all EDRs from the ocean. An additional tool was also developed in order to generate 5- and 10-minute geolocation predictions for each EDR by deriving the displacement distance, elapsed time, displacement heading and velocity based on the latest known information available. The recovery vessels were also tracked with the use of a separate commercial GPS beacon system. After jettison, 67% of the EDRs transmitted valid data by the time they were retrieved from the ocean. However, the real-time information presented by the plotting tool allowed for the ready depiction of EDR dispersal patterns and reference drift trajectories, which contributed to the recovery of all twelve EDRs and the AA-2 flight data. Lastly, the available data showed that the distance between the software’s reported drift/predicted locations and the recovery locations did not exceed 38 meters, therefore demonstrating the advantages of this software tool for supporting real-time tracking and recovery efforts of beacon devices.

Moxey, Lucas↗

Analysis of DGPS/INS and MLS/INS final approach navigation errors and control performance data

Flight tests were conducted jointly by NASA Langley Research Center and Honeywell, Inc., on a B-737 research aircraft to record a data base for evaluating the performance of a differential DGPS/inertial navigation system (INS) which used GPS Course/Acquisition code receivers. Estimates from the DGPS/INS and a Microwave Landing System (MLS)/INS, and various aircraft parameter data were recorded in real time aboard the aircraft while flying along the final approach path to landing. This paper presents the mean and standard deviation of the DGPS/INS and MLS/INS navigation position errors computed relative to the laser tracker system and of the difference between the DGPS/INS and MLS/INS velocity estimates. RMS errors are presented for DGPS/INS and MLS/INS guidance errors (localizer and glideslope). The mean navigation position errors and standard deviation of the x position coordinate of the DGPS/INS and MLS/INS systems were found to be of similar magnitude while the standard deviation of the y and z position coordinate errors were significantly larger for DGPS/INS compared to MLS/INS.

Hueschen, Richard M.↗

Flight test data for light aircraft spoiler roll control systems

The results of flight tests to determine the characteristics of spoiler roll control systems on three different light aircraft are summarized. Comparisons are made with wind tunnel data where available. Flight tests indicate that excellent roll characteristics can be achieved with spoilers. Yaw coupling with roll control inputs is virtually eliminated. Roll rates remain high when flaps are deployed at low speed. Very mild nonlinearities in control effectiveness exist, and there was no deadband or lag detected.

Kohlman, D. L.↗

Flight test data for light aircraft spoiler roll control systems

The results of flight tests to determine the characteristics of spoiler roll control systems on three different light aircraft are summarized. Comparisons are made with wind tunnel data where available. Flight tests indicate that excellent roll characteristics can be achieved with spoilers. Yaw coupling with roll control inputs is virtually eliminated. Roll rates remain high when flaps are deployed at low speed. Very mild nonlinearities in control effectiveness exist and there was no deadband or lag detected.

Kohlman, D. L.↗

Step 1: C3 Flight Demo Data Analysis Plan

The Data Analysis Plan (DAP) describes the data analysis that the C3 Work Package (WP) will perform in support of the Access 5 Step 1 C3 flight demonstration objectives as well as the processes that will be used by the Flight IPT to gather and distribute the data collected to satisfy those objectives. In addition to C3 requirements, this document will encompass some Human Systems Interface (HSI) requirements in performing the C3 flight demonstrations. The C3 DAP will be used as the primary interface requirements document between the C3 Work Package and Flight Test organizations (Flight IPT and Non-Access 5 Flight Programs). In addition to providing data requirements for Access 5 flight test (piggyback technology demonstration flights, dedicated C3 technology demonstration flights, and Airspace Operations Demonstration flights), the C3 DAP will be used to request flight data from Non- Access 5 flight programs for C3 related data products

Source record↗

The Impact of Local Meteorological Conditions on Airframe Noise Flight Test Data

Phased microphone array measurements obtained during flight tests conducted in 2016 and 2017 are used to assess the importance of local meteorological measurements on the data. In particular, the effectiveness of atmospheric absorption corrections is evaluated under vastly different temperature and humidity conditions. The results indicate that, even under conditions with high absorption, sources can be visualized up to a frequency that is dependent on background noise levels, wind, and atmospheric turbulence. However, absolute levels were found to be problematic on days with high absorption rates, with the discrepancies most prevalent for aircraft positions further from the center of the array. Restricting the data to those days with favorable meteorological conditions generally resulted in a good collapse of the spectra, with differences less than a couple of decibels.

Lockard, David P.↗

A user's manual for the NASA/JPL synthetic aperture radar and the NASA/JPL L and C band scatterometers

Airborne synthetic aperture radars and scatterometers are operated with the goals of acquiring data to support shuttle imaging radars and support ongoing basic active microwave remote sensing research. The aircraft synthetic aperture radar is an L-band system at the 25-cm wavelength and normally operates on the CV-990 research aircraft. This radar system will be upgraded to operate at both the L-band and C-band. The aircraft scatterometers are two independent radar systems that operate at 6.3-cm and 18.8-cm wavelengths. They are normally flown on the C-130 research aircraft. These radars will be operated on 10 data flights each year to provide data to NASA-approved users. Data flights will be devoted to Shuttle Imaging Radar-B (SIR-B) underflights. Standard data products for the synthetic aperture radars include both optical and digital images. Standard data products for the scatterometers include computer compatible tapes with listings of radar cross sections (sigma-nought) versus angle of incidence. An overview of these radars and their operational procedures is provided by this user's manual.

Thompson, T. W.↗

ASDAR (aircraft to satellite data relay) flight test report

The aircraft to Satellite Data Relay (ASDAR), an airborne data collection system that gathers meteorological data from existing aircraft instrumentation and relays it to ground user via a geo-synchronous meteorological satellite, is described and the results of the first test flight on a commercial Boeing 747 aircraft are presented. The flight test was successful and verified system performance in the anticipated environment.

Domino, E. J.↗

Identification of aircraft stability and control derivatives in the presence of turbulence

A maximum likelihood estimator for a linear system with state and observation noise is developed to determine stability and control derivatives from flight data obtained in the presence of turbulence. The formulation for the longitudinal short-period mode is presented briefly, including a special case that greatly simplifies the problem if the measurement noise on one signal is negligible. The effectiveness and accuracy of the technique are assessed by applying it first to simulated flight data, in which the true parameter values and state noise are known, then to actual flight data obtained in turbulence. The results are compared with data obtained in smooth air and with wind-tunnel data. The complete maximum likelihood estimator, which accounts for both state and observation noise, is shown to give the most accurate estimate of the stability and control derivatives from flight data obtained in turbulence. It is superior to the techniques that ignores state noise and to the simplified method that neglects the measurement noise on the angle-of-attack signal.

Iliff, K. W.↗

Parasitic current collection by PASP Plus solar arrays

Solar cells at potentials positive with respect to a surrounding plasma collect electrons. Current is collected by the exposed high voltage surfaces: the interconnects and the sides of the solar cells. This current is a drain on the array power that can be significant for high-power arrays. In addition, this current influences the current balance that determines the floating potential of the spacecraft. One of the objectives of the Air Force (PL/GPS) PASP Plus (Photovoltaic Array Space Power Plus Diagnostics) experiment is an improved understanding fo parasitic current collection. We have done computer modeling of parasitic current collection and have examined current collection flight data from the first year of operations. Prior to the flight we did computer modeling to improve our understanding of the physical processes that control parasitic current collection. At high potentials, the current rapidly rises due to a phenomenon called snapover. Under snapover conditions, the equilibrium potential distribution across the dielectric surface is such that part of the area is at potentials greater than the first crossover of the secondary yield curve. Therefore, each incident electron generates more than one secondary electron. The net effect is that the high potential area and the collecting area increase. We did two-dimensional calculations for the various geometries to be flown. The calculations span the space of anticipated plasma conditions, applied potential, and material parameters. We used the calculations and early flight data to develop an analytic formula for the dependence of the current on the primary problem variables. The analytic formula was incorporated into the EPSAT computer code. EPSAT allows us to easily extend the results to other conditions. PASP Plus is the principal experiment integrated onto the Advanced Photovoltaic and Electronics Experiments (APEX) satellite bus. The experiment is testing twelve different solar array designs. Parasitic current collection is being measured for eight of the designs under various operational and environment conditions. We examined the current collected as a function of the various parameters for the six non-concentrator designs. The results are similar to those obtained in previous experiments and predicted by the calculations. We are using the flight data to validate the analytic formula developed. The formula can be used to quantify the parasitic current collected. Anticipating the parasitic current value allows the spacecraft designer to include this interaction when developing the design.

Davis, Victoria Ann↗

Effects of simulated forward flight on jet noise, shock noise and internal noise

Inflight simulation experiments are conducted in an anechoic free-jet facility to examine the flight effects on various combinations of jet noise, shock noise and internal noise. The jet mixing noise component reduces with forward velocity at all angles and frequencies. When jet mixing noise is contaminated with internal noise, forward motion provides a noise reduction in the rear arc and a noise increase in the forward arc, with little change at 90 deg. The results are similar for shock-containing jets. It is found that the existing anomalies between full-scale flight data and model-scale flight simulation data could well be due to the contamination of the flight data by internal noise.

Ahuja, K. K.↗

Artemis I Flight Instrumentation Data Quality Assessment and Processing

This paper is in support of the SciTech 2024 Space Launch System Aerosciences Special Sessions being organized by Brent Pomeroy and Jeremy Pinier. On November 16th, 2022, NASA launched an inaugural test flight of the Space Launch System (SLS) carrying the Orion capsule around the moon. The vehicle was instrumented with thousands of Developmental Flight Instrumentation (DFI) sensors, which monitored aerodynamic, acoustic, structural, and thermal environments. These data are used to validate experimental and numerical tools used to predict conditions the vehicle experiences during ascent. Prior to launch, a set of tests were performed to quantify the expected quality of the DFI flight data. These included testing of individual components, such as data acquisition units, at the Systems Integration Laboratory (SIL) and testing of integrated vehicle components at the Vehicle Assembly Building (VAB). This paper summarizes these tests. Some aspects of post processing of data are also discussed.

Developmental Flight Instrumentation↗