Objective
The development of optimization techniques based on approximation concepts became a separate problem in structural optimization. The mid-range approximations based on least-squares surface fitting will be used. The search through a combinations of individual regression components in empirical model building is computationally prohibitive. A Genetic Algorithm (GA) will be developed and used to create an approximation function structure of the highest possible quality. The problem of assigning the location of the plan points in each plan of numerical experiments will also be addressed. Classic; plans developed in the design of experiments are difficult to apply because the current plan also includes points examine during previous iterations. Therefore, the optimum location of additional points in a current plan must be found to produce model of the highest quality his problem is also to be solved d by GA. Training content (objective, benefit and expected impact)
This is a unique opportunity to train in Bradford's Structural Engineering Research Group and gain niche expertise. I hope subsequently to set up a research centre in my native Castilla-Leon specialised in structural optimization and giving both training and professional services. Links with industry / industrial relevance (22)
Wider usage and acceptance of advanced structural optimization methodologies will grow with the development and distribution of easy-to-use and well-documented software packages.
Funding Scheme
RGI - Research grants (individual fellowships)Coordinator
BD7 1DP West Yorkshire - Bradford
United Kingdom