Adaptive Structural Design of Biomaterials Combining Genetic Algorithm and Topology Optimization

In practical application, biomaterials need to have good performance, and material design method is the key to improve performance. Aiming at this challenge, this paper skillfully combines genetic algorithm with topology optimization technology to promote the adaptive structure design of biomaterials to a new height. In this paper, firstly, the genetic algorithm is used to generate a set of initial biomaterial structure design schemes, and each design scheme is topologically optimized, and the fitness value of each design scheme is calculated, and the better design scheme is selected as the parent, and the selected parent design scheme is crossed and mutated to generate a new design scheme. After combining the characteristics of the parent design scheme, mutation operation introduces a new solution space by randomly changing some characteristics of the child design scheme. Repeating the above operations of topology optimization, fitness evaluation, selection and crossover mutation until the required performance requirements are met. After optimization, the structural quality is reduced, the average maximum stress is reduced from 134.6 MPa to 95.2 MPa, and the maximum and minimum displacements are reduced to 1.07 mm and 0.11 mm, respectively, which shows that the optimization strategy has remarkable effects in reducing the structural quality and improving the structural safety. These results prove that the combination of genetic algorithm and topology optimization is effective and practical in adaptive structural design of biomaterials. The research in this paper not only provides a new methodology for biomaterial design, but also opens up new possibilities for future biomaterial research and application.