A novel computer aided engineering method for comparative evaluation of nonlinear structures in the conceptual design phase

Selection of the preferred design concept during design represents a major challenge to design engineers as the required level of information and rigour to achieve an objective evaluation at early stage of design is typically not available. This is particularly evident during evaluation of design concepts of complex load-bearing mechanical structures. The engineering design concepts during concept design phase typically lack detail and more specific performance indicators to enable accurate evaluation. Hence in such cases, a prevailing evaluation approach is based primarily on qualitative scores inferred through personal intuition and historical experience of the design team or individual experts. The principal motivation behind this research is to improve the ability and confidence to select a superior design concept early in the design process. The conventional approach is sensitive to individual expertise and availability of experienced designers. Therefore, in order to make more informed decisions especially in case of complex engineering designs, the concept evaluation methods require more detailed and accurate information. This research is concerned with the development of a novel method for comparative evaluation of engineering design concepts that exhibit nonlinear structural behaviour under load. The approach is based on two key concepts: i) an expansion of the conventional substructuring technique into the nonlinear domain to enable FEA to be more applicable, effective and computationally affordable in early stages of the conceptual design phase; and ii) a restructuring of the traditional process by incorporating the optimisation search to provide orderly rule-guided evolution of design concepts in order to produce objective development metrics which alleviates the dependence on personal intuition and historical experience of the engineering designers. A series of experiments and validation case studies conducted in this research provide conclusive evidence that demonstrates the applicability and the significance of the developed method in terms of reduced time for evaluation and amount of recurrent knowledge generated compared to the more traditional approaches based on the application of FEA in the conceptual design phase. Furthermore, a Confidence Index as a performance measure is developed in this research to describe the quality of the obtained solutions. The derived Confidence Index is a novel contribution to the fields of metaheuristic measurements and engineering concept validation methodology