QUT ePrints

Robust multidisciplinary design optimisation using CFD and advanced evolutionary algorithms

Lee, Dong Seop , Srinivas, Karkenahalli , Gonzalez, Luis F., Periaux, Jacques , & Obayashi, Shigeru (2010) Robust multidisciplinary design optimisation using CFD and advanced evolutionary algorithms. In Hafez, M.M., Oshima, K., & Kwak, D. (Eds.) Computational Fluid Dynamics Review 2010. World Scientific Publishing Company, Incorporated , Singapore, pp. 469-491.

[img] Accepted Version (PDF 998kB)
Administrators only | Request a copy from author

    View at publisher

    Abstract

    Computation Fluid Dynamics (CFD) has become an important tool in optimization and has seen successful in many real world applications. Most important among these is in the optimisation of aerodynamic surfaces which has become Multi-Objective (MO) and Multidisciplinary (MDO) in nature. Most of these have been carried out for a given set of input parameters such as free stream Mach number and angle of attack. One cannot ignore the fact that in aerospace engineering one frequently deals with situations where the design input parameters and flight/flow conditions have some amount of uncertainty attached to them. When the optimisation is carried out for fixed values of design variables and parameters however, one arrives at an optimised solution that results in good performance at design condition but poor drag or lift to drag ratio at slightly off-design conditions. The challenge is still to develop a robust design that accounts for uncertainty in the design in aerospace applications. In this paper this issue is taken up and an attempt is made to prevent the fluctuation of objective performance by using robust design technique or Uncertainty.

    Impact and interest:

    Citation countsare sourced monthly from Scopus and Web of Science® 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 the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

    ID Code: 39519
    Item Type: Book Chapter
    Additional Information: For more information about this book please refer to the publisher's website (see link) or contact the author. Author contact details : felipe.gonzalez@qut.edu.au
    Additional URLs:
    Keywords: Multidisciplinary Design Optimisation, UAS, Aeronautics, Evolutionary Algorithms, Optimization, CFD
    Subjects: Australian and New Zealand Standard Research Classification > MATHEMATICAL SCIENCES (010000) > NUMERICAL AND COMPUTATIONAL MATHEMATICS (010300) > Optimisation (010303)
    Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > AEROSPACE ENGINEERING (090100)
    Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > AEROSPACE ENGINEERING (090100) > Aerospace Structures (090103)
    Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > AEROSPACE ENGINEERING (090100) > Flight Dynamics (090106)
    Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > AEROSPACE ENGINEERING (090100) > Aerodynamics (excl. Hypersonic Aerodynamics) (090101)
    Divisions: Current > Research Centres > Australian Research Centre for Aerospace Automation
    Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
    Past > Schools > School of Engineering Systems
    Copyright Owner: Copyright 2010 World Scientific Publishing Co. Pte. Ltd.
    Deposited On: 19 Jan 2011 08:37
    Last Modified: 01 Mar 2012 00:32

    Export: EndNote | Dublin Core | BibTeX

    Repository Staff Only: item control page