Identification Of Aerodynamic Coefficients Research Articles

Efficient prediction method for the water-exit characteristics of unmanned aerial–underwater vehicles

In the design of unmanned aerial–underwater vehicles (UAUVs), the performance during the transition from water to air is a crucial aspect requiring considerable attention. During water exit, UAUVs transition from water to air, crossing two vastly different mediums. Even after emerging from the water, the vehicle is still subjected to the forces exerted by the attached water. These challenges pose significant difficulties in predicting the water-exit performance. This study investigated a UAUV equipped with foldable wings and introduced a novel method for forecasting its water exit and flight characteristics using relay calculations. The method considered the complex force changes when crossing the water–air interface, as well as the force changes caused by wing unfolding and the influence of water attached to the vehicle after exiting the water. Additionally, an efficient aerodynamic coefficient identification method was adopted, and a novel approach for capturing and describing the state of the attached water was introduced. The accuracy and efficiency of the proposed method were demonstrated through comparisons with computational fluid dynamics methods. This method can be applied to the rapid iterative design of new UAUVs and provides a foundation for investigating water-exit motion control.

Dynamic modelling of parafoil system based on aerodynamic coefficients identification

This study focuses on the identification of aerodynamic coefficients through airdrop data based on a known six-degree-of-freedom (6-DOF) model. Since the precise modelling of the parafoil system is a prerequisite for design of guidance, navigation and control systems, the accurate calculation of aerodynamic coefficients is vital. This paper first presents a rigid 6-DOF nonlinear model and simplifies it by linearizing the equations around the equilibrium point, which facilitates the acquisition of aerodynamic parameters next. Then, the recursive weighted least square method is applied to identify roll and yaw coefficients from airdrop test data. At last, simulations in the wind environment are implemented to analyse the dynamics of gliding and turning. The airdrop experiment also verifies the effectiveness of the dynamic model and the accuracy of identification.

Prediction of Aircraft Aerodynamic Coefficient Based on Data-Driven Method

To identify the aerodynamic coefficient of aircraft that cannot be directly measured in actual flight, in this paper, the problem of aerodynamic coefficient identification has been solved with the rigid body three-degree-of-freedom model using aircraft dynamics model based approaches. And based on the data-driven method to predict the aerodynamic coefficients, based on radial basis function neural network (RBFNN) with particle swarm optimization (PSO) has been used to achieve the task. Taking the external disturbance and the noise of flight data into account, a section of flight data of the XXX aircraft is preprocessed. The aerodynamic coefficients are identified based on the pre-processed flight data, and the prediction results of the aerodynamic coefficients of the above methods are analyzed, which proves the effectiveness of using the data-driven method to predict the aerodynamic coefficients.

Robust parameter estimation with outlier-contaminated correlated measurements and applications to aerodynamic coefficient identification

We consider the robust parameter estimation problem for state-space models with correlated measurements in the presence of outliers. Both the scenarios that the statistical information of the nominal noises in state-space models is known or not are explored. A novel Kalman robust smoother is proposed via introducing a specific reweighting approach to estimate the system parameters as well as the states when the nominal noise covariances are known. For the case where the statistic information of the nominal noise is absent, a modified expectation–maximization algorithm is introduced and integrated into the proposed robust smoother for simultaneously estimating the unknown states, system parameters, and the noise covariances. The performance of the proposed methods is illustrated by solving the aerodynamic coefficient identification problem with the real flight data set. The simulation results reveal that the proposed approaches outperform several existing solutions when outliers occur in multiple components of correlated measurements.

Approaches to aircraft flight tests at high angles of attack

Evaluation of aircraft characteristics at high angles of attack is one of the most important tasks when testing highly maneuverable aircraft. The paper presents a new methodology for flight tests of aircraft at high angles of attack based on information and computer technologies. The key points are the flight experiment design, the identification of aerodynamic coefficients at super-critical angles of attack, the use of mathematic models for the phenomena of aerodynamic hysteresis. Practical results in the field of testing aircraft at high and super-critical angles of attack are presented.

Study on the Application Scheme of Aerodynamic Coefficient Identification Based on the Differential Evolution Algorithm

The present paper studies the application schemes of aerodynamic coefficient identification based on the differential evolution (DE) algorithm from free flight data. Two identification schemes utilizing the DE algorithm are proposed, including the whole discrete point (WDP) scheme and the differential interval linear (DIL) scheme. Several comparative tests are conducted to study the performances of the two schemes by using the noisy simulated flight data and the measured radar data. The results show satisfactory performance in estimating the aerodynamic coefficients for the two schemes. The WDP scheme provides more accurate and robust coefficients estimates in exchange of more than two times greater computational effort compared with the DIL scheme.

Identification of Aerodynamic Coefficients of Longitudinal Movement and Error Estimates for Onboard Measurements of Supercritical Angles of Attack

We propose an identification method for the aerodynamic coefficients of the lift force, drag force, and pitch moment in the supercritical range of angles of attack. The investigated models take into account the hysteresis with respect to the angle of attack, which is the main specific feature of aerodynamic coefficients in the specified range. Also, we consider the problem to find and correct errors of onboard measurements in the channels of the angle of attack and the air speed and the computational model for the forces and moments created by engines with a deflected thrust vector. We provide processing examples for the flight test data obtained during maneuvers on supercritical angles of attack; they confirm the efficiency of the proposed methods.

Forced motions design for aerodynamic identification and modeling of a generic missile configuration

This article is focused on the design of forced motions and developing models that can accurately and rapidly predict the aerodynamic stability derivatives of air vehicles over a wide range of air speeds using time-accurate computational fluid dynamic (CFD) simulations. The test case is a generic missile configuration known as the Army–Navy (basic) Finner (ANF) missile. Longitudinal stability coefficients are available from a combination of free-flight and wind tunnel tests for Mach numbers in range of 0.5–4.5. Estimating stability derivatives of this vehicle requires a large number of static and dynamic CFD simulations using a brute-force approach. The present study instead uses a single forced motion to estimate vehicle's stability derivatives over a wide range of speed regimes. The results of this study show that identification of aerodynamic coefficients from time-accurate simulation of the forced motions requires significantly less computational time. A new aerodynamic model is also proposed that captures the aerodynamic coefficients' dependence on the angle of attack, pitch rate, time rate of change of angle of attack, and Mach number including the transonic region. The results presented show that the model predictions agree well with experimental data and those calculated from a brute-force approach. The methods of this work could reduce the computational cost of estimating stability derivatives up to 90%.

Sensitivity Analysis for Global Parameter Identification. Application to Aerodynamic Coefficients

The parameter identification of grey-box nonlinear model structures remains a challenging task. Analytical models, constructed from physical laws, allow a complete description of the system behavior, with however a high complexity of the mathematical structure of the system. This paper presents an identification procedure adapted to nonlinear models and able to cope with the difficulties related to the model structure. This procedure, composed of several steps from model development to its validation, takes into account the identifiability of model parameters. It highlights the importance of performing sensitivity analysis of the output variables w.r.t. unknown parameters - input conditions and/or model parameters - to give insights on the choice of the experimental conditions able to provide sufficient information for the estimation step. These results are illustrated in the case of the identification of aerodynamic coefficients of a space probe based on free flight measurements.

Robust adaptive gliding guidance for hypersonic vehicles

A novel robust adaptive gliding guidance strategy based on multi-constrained analytical optimal guidance and online identification of aerodynamic coefficients for hypersonic vehicles is proposed. The guidance models are constructed in both longitudinal and lateral directions and optimal guidance law, namely required load factor, is designed with minimum energy consumption to satisfy terminal position, altitude and flight-path angle constraints. Considering aerodynamic coefficients are the core factors in the angle-of-attack calculation, it constructs the aerodynamic models in the form of quadratic polynomial function and employs extended Kalman filter to estimate the unknown parameters. Using the optimal guidance law based on current flight states and terminal constraints and the identified outputs to calculate angle-of-attack, then the gliding guidance mission can be achieved adaptively and robustly. Finally, the simulation experiments of high performance of the common aerothermodynamics-shell vehicle (CAV-H) are carried out to validate the guidance performance.

Aerodynamic Coefficient Identification of a Space Vehicle from Multiple Free-Flight Tests

The identification of aerodynamic coefficients, based on free-flight measurements, remains complex and challenging for vehicles such as space probes, unmanned aerial vehicles, or ammunition. In this paper, a detailed procedure for the identification of the drag, pitching moment slope, and pitch damping coefficients of a reentry space vehicle is presented. New models of these aerodynamic coefficients, based on polynomial functions of Mach numbers and incidence angles, are proposed, and an estimation strategy using multiple data series is applied. The free-flight data correspond to three-axis magnetometer and radar measurements for different experimental conditions. The resulting model is tested with new data sets to ascertain the model validity. The results show that the proposed description of the three aerodynamic coefficients and the estimation strategy are relevant.

The Identification of MATHEMATICAL MODEL aerodynamic coefficients of AIRCRAFT LATERAL MOVEMENT

The aim of this work is to develop improved methods of identifying the aerodynamic coefficients based on the synthesis of adaptive system, an adaptive algorithm aiming to identify and study the relations to identify and refine the aerodynamic parameters not maneuver lateral motion of the aircraft. The method combines the advantages of the known methods for the identification of the aerodynamic coefficients, which are presented in the public domain.The main problem lies in the fact that by traditional flight test aerodynamic coefficients are a set of discrete values. Linear model, which then is used does not describe accurately coefficients in flight, especially when changing parameters in a wide range of flight.The basic idea of the method consists in the following: synthesizing adaptive system that eliminates the inconsistency between the calculated values of the phase coordinates by which to identify and value, taken from the record flight tests. Simulation of changes in time of the phase coordinates is based on the results of other flight tests phase coordinates and mathematical model aircraft.After processing the records modified aircraft movement on the proposed algorithm we obtain the value of aerodynamic coefficients as a function of time for small changes in the parameters of flight and as a function of angle, angular velocity and deviation of steering for changing flight parameters in large range.The method of identification of the aerodynamic coefficients can fairly well determine the aerodynamic coefficients from flight test records: after identification increases the degree of real convergence of transient aircraft and its mathematical model. This method will improve the accuracy of identification of the aircraft motion parameters and therefore improve the quality of control.

ОПРЕДЕЛЕНИЕ ВЕТРОВОЙ НАГРУЗКИ НА ТРЕХМЕРНЫЕ КОНСТРУКЦИИ С ПОМОЩЬЮ МОДЕЛИРОВАНИЯ В АЭРОДИНАМИЧЕСКОЙ ТРУБЕ

The authors discuss wind loads applied to a set of two buildings. The wind load is simulated with the help of the wind tunnel. In the Russian Federation, special attention is driven to the aerodynamics of high-rise buildings and structures. According to the Russian norms, identification of aerodynamic coefficients for high-rise buildings, as well as the influence of adjacent buildings and structures, is performed on the basis of models of structures exposed to wind impacts simulated in the wind tunnel. This article deals with the results of the wind tunnel test of buildings. The simulation was carried out with the involvement of a model of two twenty-three storied buildings. The experiment was held in a wind tunnel of the closed type at in the Institute of Mechanics of Moscow State University. Data were compared at the zero speed before and after the experiment. LabView software was used to process the output data. Graphs and tables were developed in the Microsoft Excel package. GoogleSketchUp software was used as a visualization tool. The three-dimensional flow formed in the wind tunnel can't be adequately described by solving the two-dimensional problem. The aerodynamic experiment technique is used to analyze the results for eighteen angles of the wind attack.

Aerodynamic Modeling and Parameter Estimation from QAR Data of an Airplane Approaching a High-altitude Airport

Aerodynamic modeling and parameter estimation from quick accesses recorder (QAR) data is an important technical way to analyze the effects of highland weather conditions upon aerodynamic characteristics of airplane. It is also an essential content of flight accident analysis. The related techniques are developed in the present paper, including the geometric method for angle of attack and sideslip angle estimation, the extended Kalman filter associated with modified Bryson-Frazier smoother (EKF-MBF) method for aerodynamic coefficient identification, the radial basis function (RBF) neural network method for aerodynamic modeling, and the Delta method for stability/control derivative estimation. As an application example, the QAR data of a civil airplane approaching a high-altitude airport are processed and the aerodynamic coefficient and derivative estimates are obtained. The estimation results are reasonable, which shows that the developed techniques are feasible. The causes for the distribution of aerodynamic derivative estimates are analyzed. Accordingly, several measures to improve estimation accuracy are put forward.

Identification of aerodynamic coefficients of a kinetic energy projectile from flight data

A technique to identify the aerodynamic coefficients of a kinetic energy (KE) projectile using flight data is proposed. Generally speaking, the flight of a projectile is governed by a six-degree-of-freedom model in which eight aerodynamic coefficients also play a part. We will firstly show that only three of the aerodynamic coefficients have an influence on the measurable quantities (velocity, roll rate). We thus propose a reduced model to represent the projectile flight and then an identification technique based on the optimization of a functional that calls into play aerodynamic measurements and coefficients. The minimization of the functional leads to a non-linear system which, after its resolution, supplies the aerodynamic coefficients of the KE projectile and a recalculated flight that better corresponds to the measured flight data.

Identification of aerodynamic coefficients using computational neural networks

Precise, smooth aerodynamic models are required for implementing adaptive, nonlinear control strategies. Accurate representations of aerodynamic coefficients can be generated for the complete flight envelope by combining computational neural network models with an Estimation-Before-Modeling paradigm for on-line training information. A novel method of incorporating first-partial-derivative information is employed to estimate the weights in individual feedforward neural networks for each aerodynamic coefficient. The method is demonstrated by generating a model of the normal force coefficient of a twin-jet transport aircraft from simulated flight data, and promising results are obtained.

Computer-aided Characteristic Analysis and Model Design of Flight

In this paper, a practical program package of computer-aided characteristic analysis of airacraft and mathematical model design of flight simulator is introduced. This CAD package consists of five parts: flight test data error precorrection, data compatibility check, aerodynamic coefficient identification, characteristic analysis of aircraft and mathematical model design of flight simulator. In order to get high accuracy, the modified gain extended Kalman filter and smoother algorithm, separated bias identification and state estimation algorithm and shifted orthogonal series algorithm are respectively used for data compatibility check, U-D covariance factorization being used for improving numerical stability and computational efficiency. In the identification program of aerodynamic coefficient, linear maximum likelihood method is suitable to the flight regime of low angle of attack, and for the flight regime of high angle of attack, nonlinear maximum likelihood method or shifted orthogonal series method should be used. The results show that with this package the performance stability and control characteristics of aircraft and the mathematical model of flight simulator can be determined satisfactorily.

Adaptation of a strapdown formulation for processing inertial platform data

An estimator propagation formulation which ultilizes dynamic data (attitude and sensed acceleration information) from a gimballed inertial platform has been developed to aid in the Shuttle post-flight trajectory reconstruction process and aerodynamic coefficient determination studies. Unlike the classical inertial algorithms, this formulation yields a six degree-of-freedom fully coupled state and attitude estimate. Furthermore, this inertial version is shown to be independent of initial unknown platform misalignments. Results obtained using actual Inertial Measurement Unit (IMU) data and Aerodynamic Coefficient Identification Package (ACIP) strap down data from Shuttle flights are presented.

Aeroelastic Simulation of Bridges

The paper summarizes trends presently being followed in the windtunnel simulation of bridges. Topics treated are scale factors, section, partialand full‐bridge models, testing under laminar and turbulent flow, and the measurement techniques attendant upon the identification of aerodynamic coefficients of various kinds, including those related to aeroelastic effects. Attention is focused on the section model. The primary purpose as well as secondary purposes of the section model are examined. Section model testing under turbulence and the appropriateness of the test turbulence are also reviewed.

Instrument Modeling for Aerodynamic Coefficient Identification from Flight Test Data

A large number of estimation methods can be used to compute aerodynamic coefficients of ballistically flown spinning vehicles. These estimation schemes often ignore possible phase shifts between measured data and the math model of the motion. Some of these problems occur because onboard instrumentation such as rate gyros or accelerometers behave like spring mass systems. If the vehicle motion is near the resonance frequency of the instrument, the output of the instrument is shifted in phase from the actual motion and probably the model representation of the motion. In order to demonstrate this problem, the aerodynamic coefficients of a spinning vehicle are computed from actual flight test data using a standard least-squares estimation scheme. Comparisons of observed and computed measurements of the vehicle motion are presented and the problem just described is shown to exist for these data. A modeling scheme is derived to compensate for the instrumentation induced changes in the data. The results obtained using the instrumentation modeling scheme are shown to be much better than those obtained using a standard scheme.