Application of Neural Networks in the Simulation of Dynamic Effects of Canard Aircraft Aerodynamics

Ignatyev, Dmitry; Храбров, А. Н.

doi:10.1615/tsagiscij.2012004704

Cited by 6 publications

(14 citation statements)

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“…The RNN model of unsteady pitch moment coefficient, which has a NARX configuration, is compared with the FFNN model presented in [26]. The RNN has one hidden layer.…”

Section: Modelingmentioning

confidence: 99%

“…To compare only the NN configurations, the regularization technique (GNBR) is selected to be the same as for FFNN in [26].…”

Section: Modelingmentioning

confidence: 99%

“…Surrogate modeling approaches, which use mathematical approximations of the true responses of the system, are a cost-effective tool for unsteady aerodynamics. The most popular surrogate modeling techniques are artificial neural networks [23][24][25][26][27], Radial Basis Function (RBF) interpolation [9,10], and kriging [28]. Neural Networks (NN) have been recently shown to be a formal and effective tool for modeling nonlinear unsteady aerodynamics regardless of the aircraft configurations.…”

Section: Introductionmentioning

confidence: 99%

“…TCR aircraft was studied in the SimSAC project of 6th European Framework Program. Significant experimental and numerical investigations aimed at understanding the flow over such complex configuration and aerodynamic loads acting on the TCR model were carried out previously [5,6,21,26,27,30,31]. In the present paper, results of the intensive experimental campaign, which was undertaken in order to investigate the main static and dynamic properties of the pitch moment coefficient for TCR, are considered.…”

Section: Introductionmentioning

confidence: 99%

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Experimental Study and Neural Network Modeling of Aerodynamic Characteristics of Canard Aircraft at High Angles of Attack

Ignatyev

Храбров

2018

Aerospace

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Flow over an aircraft at high angles of attack is characterized by a combination of separated and vortical flows that interact with each other and with the airframe. As a result, there is a set of phenomena negatively affecting the aircraft's performance, stability and control, namely, degradation of lifting force, nonlinear variation of pitching moment, positive damping, etc. Wind tunnel study of aerodynamic characteristics of a prospective transonic aircraft, which is in a canard configuration, is discussed in the paper. A three-stage experimental campaign was undertaken. In the first stage, a steady aerodynamic experiment was conducted. The influence of a reduced oscillation frequency and angle of attack on unsteady aerodynamic characteristics was studied in the second stage. In the third stage, forced large-amplitude oscillation tests were carried out for the detailed investigation of the unsteady aerodynamics in the extended flight envelope. The experimental results demonstrate the strongly nonlinear behavior of the aerodynamic characteristics because of canard vortex effects on the wing. The obtained data are used to design and test mathematical models of unsteady aerodynamics via different popular approaches, namely the Neural Network (NN) technique and the phenomenological state space modeling technique. Different NN architectures, namely feed-forward and recurrent, are considered and compared. Thorough analysis of the performance of the models revealed that the Recurrent Neural Network (RNN) is a universal approximation tool for modeling of dynamic processes with high generalization abilities.

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“…The RNN model of unsteady pitch moment coefficient, which has a NARX configuration, is compared with the FFNN model presented in [26]. The RNN has one hidden layer.…”

Section: Modelingmentioning

confidence: 99%

“…To compare only the NN configurations, the regularization technique (GNBR) is selected to be the same as for FFNN in [26].…”

Section: Modelingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Experimental Study and Neural Network Modeling of Aerodynamic Characteristics of Canard Aircraft at High Angles of Attack

Ignatyev

Храбров

2018

Aerospace

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“…It seems the most applied method is based on using the neural network [79,80]. The other papers predicted the aerodynamic coefficient of transport aircraft with the use of artificial neural networks [81], simulated the dynamic effects of canard aircraft aerodynamics [82], used genetic algorithm optimized neural networks for predicting the practical measurements [83], determined the global aerodynamic modeling with multivariable spline [84], and applied the fuzzy logic modeling to the aircraft model identification [85] and nonlinear unsteady aerodynamics [86]. Principally all the numerical methods might be applied.…”

Section: Advanced Aerodynamic Modelsmentioning

confidence: 99%

Goal- and Object-Oriented Models of the Aerodynamic Coefficients

Rohács¹

2018

Flight Physics - Models, Techniques and Technologies

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Nowadays, aeronautics discovers new ways of flights near the critical regimes, unconventional aircraft forms, utilizing the micro-electro-mechanical technologies in flow and aircraft control, adaptive and morphing structures, using the structures and controls based on the biological principles, developing highly flexible structures, etc. Before deployment, these new technologies and solutions must be evaluated, tested in wide aerodynamic, flight dynamic simulations that require improved and new type of aerodynamic coefficient models. The chapter overviews the applicable models of the aerodynamic coefficients, introduces some new models and demonstrates how the different models can be applied in different goal-and object-oriented solutions. The following will be shortly explained: (i) how the aerodynamic forces and moments are generating, (ii) how the linear, nonlinear, steady, and nonsteady aerodynamic coefficient structures and forms might be modeled, and (iii) how to harmonize the model with the goal and object of investigations.

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Neural network modeling of unsteady aerodynamic characteristics at high angles of attack

Ignatyev

Храбров

2015

Aerospace Science and Technology

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Application of Neural Networks in the Simulation of Dynamic Effects of Canard Aircraft Aerodynamics

Cited by 6 publications

References 0 publications

Experimental Study and Neural Network Modeling of Aerodynamic Characteristics of Canard Aircraft at High Angles of Attack

Experimental Study and Neural Network Modeling of Aerodynamic Characteristics of Canard Aircraft at High Angles of Attack

Goal- and Object-Oriented Models of the Aerodynamic Coefficients

Neural network modeling of unsteady aerodynamic characteristics at high angles of attack

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