Multi-Objective and Multidisciplinary Design and Optimisation of Blended Wing Body UAV via Advanced Evolutionary Algorithms

Abstract

Improvement of wing aerodynamic efficiency is one of the common challenges in Unmanned (Combat) Aerial Vehicles (UCAV) to provide a short distance take-off, long endurance that leads to lower fuel consumption. In addition, the stealth function is one of the essential requirements to complete diverse missions and the survivability of UAVs. This paper explores the application of a robust Evolutionary Algorithm (EA) for aerofoil sections and wing planform design and optimisation for the improvement of aerodynamic performance and the reduction of Radar Cross Section (RCS). The method is based on a canonical evolution strategy and incorporates the concepts of hierarchical topology, parallel computing and asynchronous evaluation. Results obtained from the optimisation show that utilising the designing transonic wing aerofoil sections and planform in combination with Evolutionary techniques improve the aerodynamic efficiency and this produced a set of shock-free aerofoils and achieved the supercritical aero-diamond wings. Results also indicate that the method is efficient and produces optimal and non-dominated solutions.