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    Efficient analytical moments for the robustness analysis in design optimisation

    Rajan, A.; Ooi, Melanie; Kuang, Y.C.; Demidenko, S.

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    Efficient_analytical_moments_for_the_robustness_analysis_in_design_optimisation.pdf (325.3Kb)
    Date
    2016-10-17
    Citation:
    Rajan, A., Ooi, M. P-L., Kuang, Y. C., & Demidenko, S. (2016). Efficient Analytical Moments for the Robustness Analysis in Design Optimisation. IET Journal of Engineering, 1(1), pp.17. doi: 10.1049/joe.2016.0264
    Permanent link to Research Bank record:
    https://hdl.handle.net/10652/3784
    Abstract
    System uncertainties play a vital role in the robustness (or sensitivity) analysis of system designs. In an iterative procedure such as design optimisation, the robustness analysis that is simultaneously accurate and computationally efficient is essential. Accordingly, the current state-of-the-art techniques such as univariate dimension reduction method (DRM) and performance moment integration (PMI) approach have been developed. They are commonly used to express the sensitivity while utilising the statistical moments of a performance function in an advanced design optimisation paradigm known as the reliability-based robust design optimisation (RBRDO). However, the accuracy and computational efficiency scalability for increasing the problem dimension (i.e. the number of input variables) have not been tested. This study examines the scalability of the above-mentioned pioneering techniques. Additionally, it also introduces a novel analytical method that symbolically calculates the sensitivity of the performance function prior to the iterative optimisation procedure. As a result, it shows a better computational cost scalability when tested on performance functions with increased dimensionality. Most importantly, when applied to real-world RBRDO problems such as the vehicle side impact crashworthiness, the proposed technique is three times faster than the mainstream method while yielding a high quality and safe vehicle design
    Keywords:
    systems design, univariate dimension reduction method (DRM), reliability-based robust design optimisation (RBRDO)., vehicle design
    ANZSRC Field of Research:
    120404 Engineering Systems Design
    Copyright Holder:
    Institution of Engineering and Technology (IET)
    Copyright Notice:
    This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/
    Available Online at:
    http://digital-library.theiet.org/content/journals/10.1049/joe.2016.0264
    Rights:
    This digital work is protected by copyright. It may be consulted by you, provided you comply with the provisions of the Act and the following conditions of use: Any use you make of these documents or images must be for research or private study purposes only, and you may not make them available to any other person. You will recognise the author's and publishers rights and give due acknowledgement where appropriate.
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