A Bidirectional Evolutionary Structural Topology-Optimization (BESO) for 3D-Printed FRPs

Abstract

This thesis explores structural topology optimization methods in the context of 3D-printed fibre-reinforced polymers (FRPs). While topology optimization has gained significant attention across various engineering industries, its application to anisotropic materials, such as FRPs, is still in its early stages and requires more exploration. This thesis develops a novel approach that considers the anisotropy of the material and optimizes the material orientation alongside the topology optimization. The proposed method incorporates material direction optimization in conjunction with topology optimization to achieve minimum compliance. The material optimization analytically obtains optimal orientation angles to attain maximum internal energy values. The topology optimization, on the other hand, optimizes the material distribution to get maximum stiffness under prespecified constraints. By concurrently optimizing the material distribution and its orientation, the proposed approach harnesses the potential of controlling the fibre orientation in 3D-printed FRPs and produces designs with enhanced stiffness and reduced weight. The results of the thesis demonstrate the effectiveness of the proposed approach through numerical simulations and experimental testing. The optimized designs produced by the proposed approach exhibit improved performance compared to conventional isotropic topology optimization or hybrid methods.