A Formulation for Efficient Adaptive Metamodelling in Engineering Design

  • Thomas Makin

Student thesis: Doctoral ThesisPhD


This thesis presents the research and development of robust metamodelling tools for engineering design. Metamodelling in engineering is typically used for reducing computational cost of highly expensive analyses or simulations. Metamodels have been shown to be effective in these problems where an approximation constructed from a limited set of true data points is used in support of optimisation. The inspiration for this work is drawn from the optimisation of aircraft wing structures, constructed using large numbers of rectangular stiffened panels. When optimising such structures to produce a minimum weight design, it is necessary to evaluate multiple design constraints such as buckling load, damage tolerance and repairability. The total computational cost for this aspect of the analysis can become considerable when a large number of evaluations is required and can creates a bottleneck in the optimisation workflow. In response to this industrial design problem, a specification is proposed for an efficient and adaptive metamodelling formulation. Following an extensive literature review the multilevel Radial Basis Function (mRBF) model is highlighted as a promising candidate for further investigation. The mRBF formulation is discussed in detail, and a comparative study is presented comparing mRBF to more established modelling techniques. mRBF is then put to work on a range of optimisation test problems, including an industrial scale multi-panel wing design scenario. Emphasis is placed on the adaptive acquisition of model data as the optimisation process progresses. Implementation details and software development processes are also presented in detail.The case is made for decoupled modelling workflows, and a RESTful web based mRBF modelling framework. Finally the performance of the proposed modelling scheme is compared to the original specification, and recommendations are made for further investigation.
Date of Award23 Apr 2014
Original languageEnglish
Awarding Institution
  • University of Bath
SponsorsEngineering and Physical Sciences Research Council & Airbus Operations Ltd
SupervisorHyunsun Kim (Supervisor) & Michael Wilson (Supervisor)


  • Metamodelling
  • Engineering design
  • multilevel RBF
  • RESTful web services
  • aerospace composites

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