A generative design framework for porous structures: implementation to bone scaffolds using FDM method

Abstract

This paper aims to develop a computational generative design framework to create porous structures with an implementation on scaffolds for bone tissue engineering applications. The objective is to develop porous scaffolds that meet target stiffness, pore size, and porosity criteria ensuring mechanical compatibility while supporting biocompatibility. The framework employs a generative design algorithm using quasi-random sampling, genetic optimization, and path generation for scaffold modeling. Four designs are fabricated using Fused Deposition Modelling (FDM) method with Polylactic Acid (PLA) material, and their mechanical behavior is validated through compression tests. The generative design algorithm successfully generates scaffolds that fulfill porosity and stiffness requirements and the scaffold structures exhibit a porosity exceeding 70% with a compression modulus comparable to that of a trabecular bone. The experimental results show the influence of design parameters, such as strut connectivity and segment number, on the stiffness and porosity of the scaffold models. Although the current implementation focuses on highly porous structures, the algorithm can be adapted to accommodate different levels of porosity and stiffness.