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Horizontal-tail height, wing height, and dihedral effects on longitudinal and lateral stability characteristics of 76 deg swept arrow wing aircraft model
The Langley Research Center uses radio-controlled, scaled aircraft models to study the spin-entry characteristics of aircraft. Recent spin-entry studies required the use of an electronic proportional-control system for manipulating model control surfaces. In order to meet control system requirements, a special-purpose analog computer was designed to simulate the coupling between roll and pitch controls. A digital encoder was designed to encode the voltage analogs of control-surface position into a special pulse format for transmission to the model. This paper describes the two special developments and their relationship to the functions of the overall control system.
Pressure distribution on x-15 aircraft model
An overview of the Aeroelastic Design Optimization Program (ADOP) at the Douglas Aircraft Company is given. A pilot test program involving the animation of mode shapes with solid rendering as well as wire frame displays, a complete aircraft model of a high-altitude hypersonic aircraft to test ADOP procedures, a flap model, and an aero-mesh modeler for doublet lattice aerodynamics are discussed.
The use of advanced magnetic suspension and balance systems (MSBS) in wind tunnels is examined. The advantages of MSBS are discussed, including accurate dynamic stability and free manipulation of the model aircraft allowing the free-flying model to respond dynamically to aerodynamic forces. Examples of wind tunnel tests employing MSBS are presented, including tests of a hypersonics parasol wing configuration and the simulation of the ejection of the crew-escape module from an aircraft.
The implementation of available wind shear data into general aviation flight training simulators is discussed. Currently, there are 11 simulators with wind shear models installed involving some 9 different aircraft models. Retrofits to other systems that were put out earlier are currently underway, and all the new simulators will have wind shear available for the instructors to use for demonstrations and training. There are three types of computer systems involved, and two different types of instructor stations. Most of the systems with wind shear are the CRT-type displays. The integration of wind shear models in flight simulators is discussed in detail.
A simple technique is presented which forms a cubic grid model of a helicopter from an Aircraft Modeling Code (AMC) input file. The AMC input file defines the helicopter fuselage as a series of polygonal cross sections. The cubic grid model is used as an input to a Finite Difference Time Domain (FDTD) code to obtain predictions of antenna performance on a generic helicopter model. The predictions compare reasonably well with measured data.
In flight control, the design objective and the aircraft dynamics may be different in low and high angle of attack regions. This paper presents a systematic switching Linear Parameter-varying LPV method to determine if it is practical to use for flight control designs over a wide angle of attack region. The approach is based on multiple parameter-dependent Lyapunov functions a family of LPV controllers are designed, and each of them is suitable for a specific parameter subspace. The state of the controller is reset to guarantee the stability requirement of the Lyapunov function when the switching event occurs. Two parameter-dependent switching logics, hysteresis switching and switching with average dwell times are examined. The proposed switching LPV control scheme is applied to an F-16 aircraft model with different design objectives and aircraft dynamics in low and high angle of attack regions. The nonlinear simulating results using both switching logics are compared.
NASA Ames Research Center has an ongoing program in neural network control technology targeted toward real time flight demonstrations using a modified F-15 which permits direct inner loop control of actuators, rapid switching between alternative control designs, and substitutable processors. An important part of this program is the ACTIVE flight project which is examining the feasibility of using neural networks in the design, control, and system identification of new aircraft prototypes. This paper discusses two research applications initiated with this objective in mind: utilization of neural networks for wind tunnel aircraft model identification and rapid learning algorithms for on line reconfiguration and control. The first application involves the identification of aerodynamic flight characteristics from analysis of wind tunnel test data. This identification is important in the early stages of aircraft design because complete specification of control architecture's may not be possible even though concept models at varying scales are available for aerodynamic wind tunnel testing. Testing of this type is often a long and expensive process involving measurement of aircraft lift, drag, and moment of inertia at varying angles of attack and control surface configurations. This information in turn can be used in the design of the flight control systems by applying the derived lookup tables to generate piece wise linearized controllers. Thus, reduced costs in tunnel test times and the rapid transfer of wind tunnel insights into prototype controllers becomes an important factor in more efficient generation and testing of new flight systems. NASA Ames Research Center is successfully applying modular neural networks as one way of anticipating small scale aircraft model performances prior to testing, thus reducing the number of in tunnel test hours and potentially, the number of intermediate scaled models required for estimation of surface flow effects.
A full-scale, tilt-nacelle V/STOL aircraft model was tested in hover at the National Full Scale Aerodynamics Complex (NFAC), NASA Ames Research Center. The model was powered by two TF-34 turbofan engines. It was tested at several ground heights and control deflections. Test technique and test setup were documented. Limited results show that: (1) a small change in control power with ground height was measured, and control power was found to be good over + or - 20 deg of horizontal vane deflection; (2) integrated fuselage undersurface pressures, when compared with the total model loads and measured thrust, defined the effect of the fountain and its related flow field on model forces and moments; and (3) there was no indication of hot gas ingestion during simulated takeoff in calm winds from wheels on deck ground height.
A full-scale, tilt-nacelle V/STOL aircraft model was tested in hover at the National Full Scale Aerodynamics Complex (NFAC), NASA Ames Research Center. The model was powered by two TF-34 turbofan engines. It was tested at several ground heights and control deflections. Test technique and test setup were documented. Limited results show that (1) a small change in control power with ground height was measured, and control power was found to be good over + or - 20 deg of horizontal vane deflection; (2) integrated fuselage undersurface pressures, when compared with the total model loads and measured thrust, defined the effect of the fountain and its related flow field on model forces and moments; and (3) there was no indication of hot gas ingestion during simulated takeoff in calm winds from wheels on deck ground height.
Estimating aircraft models from test data requires several simplifying assumptions that introduce biases into the parameter estimates. In this paper, these biases are defined and a method for estimating the biases is discussed. Having an estimate of the bias allows the parameters estimated from test to be integrated into a high-order model. The Integrated Adaptive Wing Technology Maturation (IAWTM) wind tunnel model is discussed and the bias is demonstrated for one of the testing configurations. The methodology was able to estimate these biases and apply corrections to high-order aeroelastic models to improve the fit to test data. The consideration of the biases allows more meaningful comparisons and avoids the erroneous differences between pretest predictions and the fitted model.
Estimating aircraft models from test data requires several simplifying assumptions that introduce biases into the parameter estimates. In this paper, these biases are defined and a method for estimating the biases is discussed. Having an estimate of the bias allows the parameters estimated from test to be integrated into a high-order model. The Integrated Adaptive Wing Technology Maturation (IAWTM) wind tunnel model is discussed and the bias is demonstrated for one of the testing configurations. The methodology was able to estimate these biases and apply corrections to high-order aeroelastic models to improve the fit to test data. The consideration of the biases allows more meaningful comparisons and avoids the erroneous differences between pretest predictions and the fitted model.
Results of buffet research that was conducted as part of the joint USAF/NASA F-111 TACT Research Program are presented. The correlation of wind tunnel and flight measurements of buffet excitation showed that there generally was good agreement between measurements of pressure fluctuations on the models and aircraft in regions of separated flow. At shock-wave boundaries of the separated flow, correlations of pressure fluctuations were not so good, due to Reynolds number and static elastic effects. The buffet prediction method, which applies a forcing function that is obtained by real-time integration of pressure time histories with the natural modes, is described. The generalized forces, including the effects of wing and tail, correlations of predicted and measured damping, and correlations of predicted and measured buffet response are presented. All presented data are for a Mach number of 0.8 with wing-sweep angles of 26 and 35 deg for a range of angles-of-attack that include buffet onset to high intensity buffeting. Generally, the buffet predictions were considered to be quite good particularly in light of past buffet-prediction experience.
The problem of using engine thrust differentials to compensate for rudder and aileron failures in aircraft flight control is addressed in this paper in a new framework. A nonlinear aircraft model that incorporates engine di erentials in the dynamic equations is employed and linearized to describe the aircraft s longitudinal and lateral motion. In this model two engine thrusts of an aircraft can be adjusted independently so as to provide the control flexibility for rudder or aileron failure compensation. A direct adaptive compensation scheme for asymptotic regulation is developed to handle uncertain actuator failures in the linearized system. A design condition is specified to characterize the system redundancy needed for failure compensation. The adaptive regulation control scheme is applied to the linearized model of a large transport aircraft in which the longitudinal and lateral motions are coupled as the result of using engine thrust differentials. Simulation results are presented to demonstrate the effectiveness of the adaptive compensation scheme.
Twenty-five large scale aircraft flammability tests were conducted in a Boeing 737 fuselage at the NASA Johnson Space Center (JSC). The objective of this test program was to provide a data base on the propagation of large scale aircraft fires to support the validation of aircraft fire mathematical models. Variables in the test program included cabin volume, amount of fuel, fuel pan area, fire location, airflow rate, and cabin materials. A number of tests were conducted with jet A-1 fuel only, while others were conducted with various Boeing 747 type cabin materials. These included urethane foam seats, passenger service units, stowage bins, and wall and ceiling panels. Two tests were also included using special urethane foam and polyimide foam seats. Tests were conducted with each cabin material individually, with various combinations of these materials, and finally, with all materials in the cabin. The data include information obtained from approximately 160 locations inside the fuselage.
The Rapid Aero Modeling (RAM) approach is a method to efficiently and automatically obtain aerodynamic models during testing, significantly saving time and resources. Motivation for this technology results from demand for experimental efficiency and model fidelity that has increased with growing aircraft complexity and aerodynamic nonlinearities. These issues are typical in the responses presented by a class of vehicles categorized as Urban Air Mobility aircraft where many features from both airplane and rotorcraft are present. For UAM configurations, with typically many more factors than conventional aircraft, traditional test methods can lead to increased costs and missed interactions. RAM guides the test to obtain high-fidelity, statistically rigorous aircraft models, and the approach is applicable to computational, ground, or flight-test experiments. It combines concepts from Design of Experiment theory and Aircraft System Identification theory that allow the user the freedom to choose, in advance of the test, a specific level of fidelity typically, in terms of prediction error. RAM only collects data required to meet the user-specified fidelity and fidelity is only limited by the facility and test article capabilities. An initial wind tunnel test to support development of RAM was conducted to assess potential metrics, algorithms, and procedures. This paper presents results from initial tests for the development of RAM technology and highlights some of the unique features of RAM applied toa conventional configuration during a ground-based, static, wind-tunnel test.
Wind-tunnel wall effect on tilt-wing and fan-in- wing aircraft models