A genetic algorithm-based structural topology optimisation. (4th November 2022) - Gavali, S.L.; Reddy, Y.P.; Vijayakumar, K.N.
In recent times advancements in 3D printing technology, primarily pertaining to biocompatible materials, have paved the way for customisable biomedical implants. However, the costs of these implants are very high mostly due to expensive materials like Ti64 and associated printing technologies. One method to mitigate this cost challenge is by optimising the material content in the implant structure while keeping its robustness intact. Various methods of structural topology optimisation have been explored by researchers in this field to overcome this challenge. In this paper, a novel genetic algorithm (GA)-based topology optimisation procedure is compared with methods like structural, lattice topology optimisation and Ad joint method. Comparisons are made with respect to mass reduction with minimum deformation. The procedure is implementing a MATLAB code to obtain structurally optimised topologies for various canonical structures. For experimental validation of optimisation procedure, a cantilever beam structure made of Ti64 material was printed as a test coupon and compared with MATLAB simulation. The obtained optimised topologies were found to be in agreement with topologies obtained using different optimisation techniques with similar boundary conditions.