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    ARTICLE

    Comparative Study of Machine Learning Modeling for Unsteady Aerodynamics

    Mohammad Alkhedher*

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1901-1920, 2022, DOI:10.32604/cmc.2022.025334

    Abstract Modern fighters are designed to fly at high angle of attacks reaching 90 deg as part of their routine maneuvers. These maneuvers generate complex nonlinear and unsteady aerodynamic loading. In this study, different aerodynamic prediction tools are investigated to achieve a model which is highly accurate, less computational, and provides a stable prediction of associated unsteady aerodynamics that results from high angle of attack maneuvers. These prediction tools include Artificial Neural Networks (ANN) model, Adaptive Neuro Fuzzy Logic Inference System (ANFIS), Fourier model, and Polynomial Classifier Networks (PCN). The main aim of the prediction model is to estimate the pitch… More >

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