Aerodynamic Shape Optimisation of Unmanned Aerial Vehicles using Hierarchical Asynchronous Parallel Evolutionary Algorithms
Lee, Dong-Seop , Gonzalez, Luis F., Srinivas, K. , Auld, Doug , & Wong, Kee Choon (2007) Aerodynamic Shape Optimisation of Unmanned Aerial Vehicles using Hierarchical Asynchronous Parallel Evolutionary Algorithms. International Journal of Computational Intelligence Research, 3(3), pp. 229-250.
One of the challenges in Unmanned (Combat) Aerial Vehicles (UCAV) is the improvement of aerodynamic performance to complete diverse missions, increase endurance and lower fuel consumption. Recent advances in design tools, materials, electronics and actuators have opened the door for implementation of transonic flow control technologies to improve aerodynamic efficiency. This paper explores the application of a robust Multi-Objective Evolutionary Algorithm (MOEA) for the design and optimisation of aerofoil sections and wing planform of UAVs and UCAVs. The methodology is based on a canonical evolution strategy and incorporates the concepts of hierarchical topology, parallel computing and asynchronous evaluation. For the design and optimisation of UCAV wing planform shape, an aero-diamond planform shape with a jagged trailing edge is considered like saw tooth. Results obtained from the combination between the approach and the aerodynamic analysis tools show the improvement of the aerodynamic efficiency, a set of shock-free aerofoils and the supercritical aero-diamond wing. Results also indicate that the method is capable to produce non-dominated solutions.
Impact and interest:
Citation countsare sourced monthly fromand citation databases.
These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.
Citations counts from theindexing service can be viewed at the linked Google Scholar™ search.
Repository Staff Only: item control page