A biologically inspired methodology for multi-disciplinary topology optimization

Abstract

This thesis introduces a biologically inspired topology optimization method with the incorporation of fractones. The proposed method was adapted from a current optimization method which employs a cellular division model for the generation of topological maps. Once topologies are generated, they are evaluated for a set of performance functions and optimized through a genetic algorithm. The proposition of this thesis was that the incorporation of fractones into the existing mapping system may improve the overall efficiency and performance of the optimization algorithm. Fractones are small extracellular structures believed to regulate the cellular division process through the capture and transport of growth factors. In this model the distribution and diffusion of growth factors served as additional control parameters in the creation and optimization of topologies. Both the fractone modified and original methods of the mapping system were applied to an aeroelastic flapping membrane wing optimization problem in which the supporting lattice structures of the wings were optimized for power requirement, lift, and thrust performances. The performances of the original and fractone models were compared and analyses of the generated venation patters were made.