Multi-additional Sampling Multi-objective Efficient Global Optimization applied to UAVs Airfoil Design Problem

Abstract

In the aircraft design methodology, there are many methods to measuring the UAVs performance, such as, the minimize drag, the lift required or the take-off/landing performance etc. The multi-objective optimization is one of the popular method for UAVs design problem. In addition, in the UAVs design problem is required for high computational cost such as computation of fluid dynamics. The solution to the said problem could be reached through the method of the Efficient Global Optimization algorithm (or abbreviated, the EGO). However, the EGO was, in the first instant, intended for very limited use; namely, it was utilized as a solution for a single-objective optimization problem with just one additional sampling. Then, the EGO method must be required for long computational time for single-additional sampling procedure. The objective of this particular research was to study the EGO with multi-objective multi-additional sampling as a solution to the UAVs airfoil design problem. The Expected Hypervolume Improvement (EHVI) is applied with the EGO process with an intention to find a solution to the multi-objective optimization problem. Furthermore, there was a proposal to use multiple additional sampling methods in the efficiency improvement of the additional sampling process in EGO, and at the same time, keeping the performance of exploration based on EHVI maximization at the same constant There are two main goals in the application of this algorithm to UAVs airfoil design optimization, which include minimizing aerodynamic drag and maximizing UAVs airfoil thickness at the trailing edge. The Reynolds-averaged Navier-Stokes simulation is applied for aerodynamic evaluation. By adopting the airfoil design, the results were the reduction in the aerodynamic drag, as well as 5% improvement of the thickness of the airfoil at the trailing edge when compared with the airfoil initial design.