Yer Etkisi Altındaki Delta Kanat Üzerinde Oluşan Taşıma Katsayısının Yapay Sinir Ağı Kullanılarak Tahmin Edilmesi

Abstract

The estimation of the lift coefficient, CL of a non-slender delta wing under the ground effect, is performed by employing an artificial neural network (ANN). The purpose of the study is to estimate the lift coefficient, CL acting on the delta wing for the ground distance h/c=0.4 by utilizing the actual lift coefficient, CL for the ground distances h/c=1, 0.7, 0.55, 0.25 and 0.1. In this ANN model, the angle of attack, α and ground distance, h/c were used as input parameters and lift coefficients, CL as the output parameter. While mean absolute percentage error (MAPE) and root mean squared error (RMSE) were found as 1.60% and 0.0114 in the testing stage, they were calculated as 1.77% and 0.01 in the training stage. Hence, this investigation shows that the lift coefficient, CL of the delta wing in ground effect can be correctly estimated by developing an ANN model.