State-of-the-art in aerodynamic shape optimisation methods

Skinner, S.N. and Zare-Behtash, H. (2018) State-of-the-art in aerodynamic shape optimisation methods. Applied Soft Computing, 62, pp. 933-962. (doi: 10.1016/j.asoc.2017.09.030)

Abstract

Aerodynamic optimisation has become an indispensable component for any aerodynamic design over the past 60 years, with applications to aircraft, cars, trains, bridges, wind turbines, internal pipe flows, and cavities, among others, and is thus relevant in many facets of technology. With advancements in computational power, automated design optimisation procedures have become more competent, however, there is an ambiguity and bias throughout the literature with regards to relative performance of optimisation architectures and employed algorithms. This paper provides a well-balanced critical review of the dominant optimisation approaches that have been integrated with aerodynamic theory for the purpose of shape optimisation. A total of 229 papers, published in more than 120 journals and conference proceedings, have been classified into 6 different optimisation algorithm approaches. The material cited includes some of the most well-established authors and publications in the field of aerodynamic optimisation. This paper aims to eliminate bias toward certain algorithms by analysing the limitations, drawbacks, and the benefits of the most utilised optimisation approaches. This review provides comprehensive but straightforward insight for non-specialists and reference detailing the current state for specialist practitioners.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Skinner, Mr Shaun and Zare-Behtash, Dr Hossein
• Authors: Skinner, S.N., and Zare-Behtash, H.
• College/School: College of Science and Engineering > School of Engineering > Autonomous Systems and Connectivity
• Journal Name: Applied Soft Computing
• Publisher: Elsevier
• ISSN: 1568-4946
• ISSN (Online): 1872-9681
• Published Online: 29 September 2017
• Copyright Holders: Copyright © 2017 The Authors
• First Published: First published in Applied Soft Computing 62: 933-962
• Publisher Policy: Reproduced under a Creative Commons License

Project Code	Award No	Project Name	Principal Investigator	Funder's Name	Funder Ref	Lead Dept
64726	1	National Wind Tunnel Facility	Frank Coton	Engineering and Physical Sciences Research Council (EPSRC)	EP/L024888/1	VPO (ACADEMIC & EDUCATIONAL INNOVATION)