Regression analysis was employed to investigate the complex relationship between the aerodynamic characteristics of NACA 5-digit airfoils and key predictors, including angle of attack (alpha), Reynolds number, optimal lift coefficient (X1), maximum camber (X2), airfoil thickness at the maximum camber (S or X3), and maximum thickness position (Max Thickness or X4). The objective was to develop robust predictive models for critical aerodynamic responses, namely lift coefficient (CL), drag coefficient (CD), profile drag coefficient (CDp), minimum pressure coefficient (Cpmin), and pitching moment coefficient (Cm).
By leveraging regression analysis, we aimed to uncover the nuanced dependencies and intricate patterns within the data, allowing for the creation of empirical models that capture the influence of the selected predictors on the aerodynamic performance of the airfoils. Understanding these relationships is crucial for optimizing airfoil design, enhancing aerodynamic efficiency, and gaining insights into the complex interplay of factors affecting the lift, drag, pressure distribution, and pitching moment characteristics of the airfoils across a wide range of operating conditions. The resulting regression models provide a valuable tool for predicting and optimizing the aerodynamic behavior of NACA 5-digit airfoils, contributing to advancements in aerodynamic design and performance analysis in various applications, such as aviation and wind energy.
In summary, the table provides a comparative overview of the performance of different regression models in predicting Inputs vs CDp Response. Models are assessed based on various metrics, with lower RMSE, MSE, and MAE values and higher R-squared values suggests that these models have been evaluated on a separate test dataset indicating better predictive performance. The "Tested" status metrics, with lower RMSE, MSE, and MAE values and higher R-squared values indicating better predictive performance. The "Tested" status suggests that these models have been evaluated on a separate test dataset.Author: Andrew Clinton
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