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This paper presented a method for collecting and graphically correlating subjective ratings and objective flight test data. The method enables flight-simulation engineers to enhance the simulator characterization of rotor craft flight in order to achieve maximum transferability of simulator experience.
The FLYRT simulation model of the U.S. Army/McDonnell Douglas AH-64 Apache attack helicopter is validated against flight test data. The approach used for validation involves matching static trim attitudes and control positions and driving the model with measured control time histories to compare dynamic responses such as angular rates and normal acceleration. Flight test data is processed to determine kinematic consistency in the angular degrees of freedom. Modeling problems associated with aerodynamic interaction of the main rotor wake on the horizontal stabilator and engine response timing are identified. Appropriate model updates are made which result in good overall model correlation throughout the flight regime investigated.
Level flight airframe vibration at main rotor excitation frequencies was calculated. A NASTRAN tailboom analysis was compared with test data for evaluation of methods used to determine effective skin in a semimonocoque sheet-stringer structure. The flight vibration correlation involved comparison of level flight vibration for two helicopter configurations: clean wing, at light gross weight and wing stores at heavy gross weight. In the tailboom correlation, deflections and internal loads were compared using static test data and a NASTRAN analysis. An iterative procedure was used to determine the amount of effective skin of buckled panels under compression load.
This paper presents a comparison of analysis and flight test data for a drone aircraft equipped with an active flutter suppression system. Emphasis is placed on the comparison of modal dampings and frequencies as a function of Mach number. Results are presented for both symmetric and antisymmetric motion with flutter suppression off. Only symmetric results are presented for flutter suppression on. Frequency response functions of the vehicle are presented from both flight test data and analysis. The analysis correlation is improved by using an empirical aerodynamic correction factor which is proportional to the ratio of experimental to analytical steady-state lift curve slope. In addition to presenting the mathematical models and a brief description of existing analytical techniques, an alternative analytical technique for obtaining closed-loop results is presented.
Radar data collected during the 1991 NASA flight tests have been selectively analyzed to support research directed at developing both improved as well as new algorithms for detecting hazardous low-altitude windshear. Analysis of aircraft attitude data from several flights indicated that platform stability bandwidths were small compared to the data rate bandwidths which should support an assumption that radar returns can be treated as short time stationary. Various approaches at detection of weather returns in the presence of ground clutter are being investigated. Non-coventional clutter rejection through spectrum mode tracking and classification algorithms is a subject of continuing research. Based upon autoregressive modeling of the radar return time sequence, this approach may offer an alternative to overcome errors in conventional pulse-pair estimates. Adaptive filtering is being evaluated as a means of rejecting clutter with emphasis on low signal-to-clutter ratio situations, particularly in the presence of discrete clutter interference. An analysis of out-of-range clutter returns is included to illustrate effects of ground clutter interference due to range aliasing for aircraft on final approach. Data are presented to indicate how aircraft groundspeed might be corrected from the radar data as well as point to an observed problem of groundspeed estimate bias variation with radar antenna scan angle. A description of how recorded clutter return data are mixed with simulated weather returns is included. This enables the researcher to run controlled experiments to test signal processing algorithms. In the summary research efforts involving improved modelling of radar ground clutter returns and a Bayesian approach at hazard factor estimation are mentioned.
Lockheed C-130 service-flight inspection data is reduced by means of fracture mechanics and statistical analysis into a form from which the probability of time to crack initiation and the distribution of initial flaw sizes for various locations on the aircraft can be determined. Crack sizes are normalized by extrapolating a growing crack backwards from its first recorded size to .03 inches (crack initiation size) yielding the time to crack initiation. In a similar fashion, the crack is grown backwards to a time equal to zero to yield an initial flaw size. In order to perform the discussed computations, crack growth constants were computed for each individual location and were analyzed statistically. Statistical distributions were fitted to times to crack initiation and to initial flaw sizes in order to describe their expected behavior. Weibull and Johnson distributions have been found to fit the data reasonably well but for a better fit convolution integrals of Poisson load distributions and Weibull strength distributions are needed.
The primary acoustic priority of the flight test data base for HSR is the validation of the NASA Aircraft Noise Prediction Program (ANOPP) and other source noise codes. Also, the noise measurements are an important support function for the High Lift Program devoted to HSR. Another concern that will be addressed is a possible noise problem 7-20 miles from take-off during climbout. The attention arises from the higher speeds envisioned for the HSCT compared to conventional aircraft causing levels to increase because of Doppler amplification in conjunction with high source levels due to jet noise. An attempt may be made to measure airframe noise for the F-16XL test which would provide an assessment of this noise component for delta wing aircraft.
In this paper a quasi maximum likelihood method for estimating a low order model of a flexible vehicle has been developed and demonstrated. The quasi maximum likelihood method uses a large number of sensors to estimate the parameters and covariance in a method consistent with the maximum likelihood filter-error method. The cost function has been defined in a frequency domain to improve computational efficiency and to enable estimation of an unstable plant. The method has been demonstrated using flight data from the National Aeronautics and Space Administration X-56A Multi-Utility Technology Testbed flex wing tests, which include unstable flutter modes. The method was able to effectively estimate the frequency and damping of the dynamics of the aircraft and generate a transfer function that is useful for control system evaluations.
A parameter-estimation algorithm was used to extract the longitudinal aerodynamic derivatives from flight data for the XC-142A airplane in a cruise condition. The flight data were the response to a tail-plane doublet input. Results of this study showed that a set of derivatives were determined which yielded a calculated aircraft response in close agreement with the measured response. This calculated response was in much closer agreement with the flight data than the response obtained by using derivatives which were calculated from empirical methods. There were large differences between some of the important derivatives extracted from flight data and those calculated from empirical methods. The reasons for these differences were not identified.
The paper describes preflight and inflight performance checkout of the three isothermalizer heat pipes onboard the OAO-C spacecraft. The three pipes are: an axially grooved pipe, a pedestal artery pipe, and a self-priming spiral artery pipe. All pipes are 1/2-inch diameter tube rolled into a 48-inch diameter hoop. They are constructed of aluminum and use ammonia as working fluid. Periodic inflight performance checks have been made since launch in August 1972. No degradation in performance of any of the pipes has been detected. The flight data are in excellent agreement with ground test data.
The application of a maximum likelihood estimator to flight data is discussed and procedures to facilitate routine analysis of a large amount of flight data are proposed. Flight data were used to demonstrate the proposed procedures. Modeling considerations are discussed for the system to be identified, including linear aerodynamics, instrumentation, and data time shifts, and aerodynamic biases for the specific types of maneuvers to be analyzed. Data editing to eliminate common data acquisition problems, and a method of identifying other problems are considered. The need for careful selection of the maneuver or portions of the maneuver to be analyzed is pointed out. Uncertaintly levels (analogous to Cramer-Rao bounds) are discussed as a way of recognizing significant new information.
Today's modern flight simulation research produces vast amounts of time sensitive data. The meaning of this data can be difficult to assess while in its raw format. Therefore, a method of breaking the data down and presenting it to the user in a graphical format is necessary. Simulation Graphics (SimGraph) is intended as a data visualization software package that will incorporate simulation data into a variety of animated graphical displays for easy interpretation by the simulation researcher. This document is intended as an end user's guide.
The NASA Engineering and Safety Center (NESC) has performed independent model development to support cross-model verification for the Space Launch System (SLS) Program since 2012 which culminated, for Artemis I, in a postflight reconciliation analysis of the Artemis I ascent trajectory (validation). This post-flight analysis was completed by both the NESC and the SLS Program. Upon successful completion of the Artemis I mission, multiple preflight simulations of the nominal ascent trajectory were updated with Day of Launch (DOL) conditions and simulated results were compared to reconstructed flight data derived from telemetry measurements. Dispersed trajectories were also produced using a combination of DOL conditions and preflight uncertainties, which ideally should bound the Artemis I flight data. Finally, multibody dynamics were simulated for some of the separation events to support clearance analyses. This paper focuses on validating and understanding the accuracy of the models by comparing simulated results against the Artemis I flight data. In addition, discrepancies uncovered between simulations led to opportunities to investigate areas for potential model improvement to refine preflight simulations for future Artemis missions. Included in this paper is background on the flight performance simulation tools, the postflight analysis approach, and a comparison of simulation results against the Artemis I flight data. Simulated results were found to generally be in close agreement with each other and the Artemis I flight data.
This dataset includes externalities: weather, number of arrival flights, and day of the week. Weather data are collected from the National Weather Service’s NY-Central Park Area record, and flight arrival data are collected from the Bureau of Transportation Statistics.
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.
Lunar Orbiter flight vibration measurements compared with flight acceptance test data
A number of recent program results and current issues were addressed: the data collection phase of the highly successful Joint Airport Weather Study (JAWS) Project and the NASA-B5f7B Gust Gradient Program, the use of these data for flight crew training through educational programs (e.g., films) and with manned flight training simulators, methods for post-accident determination of wind conditions from flight data recorders, the microburst wind shear phenomenon which was positively measured and described the ring vortex as a possible generating mechanism, the optimum flight procedure for use during an unexpected wind shear encounter, evaluation of the low-level wind shear alert system (LLWSAS), and assessment of the demonstrated and viable application of Doppler radar as an operational wind shear warning and detection system.
Blade-Vortex-Interaction (BVI) produces annoying high-intensity impulsive noise. NASA Ames collected several sets of BVI noise data during in-flight and wind tunnel tests. The goal of this work is to extract the essential features of the BVI signals from the in-flight data and examine the feasibility of extracting those features from BVI noise recorded inside a large wind tunnel. BVI noise generating mechanisms and BVI radiation patterns an are considered and a simple mathematical-physical model is presented. It allows the construction of simple synthetic BVI events that are comparable to free flight data. The boundary effects of the wind tunnel floor and ceiling are identified and more complex synthetic BVI events are constructed to account for features observed in the wind tunnel data. It is demonstrated that improved recording of BVI events can be attained by changing the geometry of the rotor hub, floor, ceiling and microphone. The Euclidean distance measure is used to align BVI events from each blade and improved BVI signals are obtained by time-domain averaging the aligned data. The differences between BVI events for individual blades are then apparent. Removal of wind tunnel background noise by optimal Wiener-filtering is shown to be effective provided representative noise-only data have been recorded. Elimination of wind tunnel reflections by cepstral and optimal filtering deconvolution is examined. It is seen that the cepstral method is not applicable but that a pragmatic optimal filtering approach gives encouraging results. Recommendations for further work include: altering measurement geometry, real-time data observation and evaluation, examining reflection signals (particularly those from the ceiling) and performing further analysis of expected BVI signals for flight conditions of interest so that microphone placement can be optimized for each condition.