A hybrid original approach for prediction of the aerodynamic coefficients of an ATR-42 scaled wing model

作     者：Abdallah Ben Mosbah Ruxandra Mihaela Botez Thien My Dao 

作者机构：Department of Automated Production EngineeringEcole de Technologie SuperieureUniversity of QuebecLaboratory of Applied Research in Active ControlsAvionics and AeroServoElasticity LARCASEMontrealQuebec H3C-1K3Canada Department of Mechanical EngineeringEcole de Technologie SuperieureUniversity of QuebecMontrealQuebec H3C-1K3Canada 

出 版 物：《Chinese Journal of Aeronautics》 (中国航空学报（英文版）)

年 卷 期：2016年第29卷第1期

页      面：41-52页

核心收录：

学科分类：080103[工学-流体力学] 08[工学] 080104[工学-工程力学] 0801[工学-力学（可授工学、理学学位）] 

基　　金：funded by the Natural Sciences and Engineering Research Council of Canada(NSERC)in the frame of the Canada Research Chair for Aircraft Modeling and Simulation Technologies 

主　　题：Aerodynamic coefficients Estimation Extended great deluge Metaheuristic Model identification Optimization Support vector machines Wind tunnel tests 

摘      要：A new approach for the prediction of lift, drag, and moment coefficients is presented. This approach is based on the support vector machines （SVMs） methodology and an optimization meta-heuristic algorithm called extended great deluge （EGD）. The novelty of this approach is the hybridization between the SVM and the EGD algorithm. The EGD is used to optimize the SVM parameters. The training and validation of this new identification approach is realized using the aerodynamic coefficients of an ATR-42 wing model. The aerodynamic coefficients data are obtained with the XFoil software and experimental tests using the Price-Paidoussis wind tunnel. The predicted results with our approach are compared with those from the XFoil software and experimental results for different flight cases of angles of attack and Mach numbers. The main pur- pose of this methodology is to rapidly Predict aircraft aerodynamic coefficients.