Multi-objective Optimization of Biomedical Scaffold Geometries for Mechanical and Porous Performance Enhancement
نویسندگان
1 Department of Mechanical Engineering, Birjand University of Technology, Birjand, Iran
2 Department of Mechanical Engineering, University of Birjand, Birjand, Iran
3 Department of Mechanical Engineering, University of Birjand, Birjand, Iran
4 Department of Mechanical Engineering, Birjand University of Technology, Birjand, Iran
doi
10.5829/ije.2026.39.01a.14چکیده
Scaffold geometry plays a crucial role in determining its mechanical strength, as changes in shape can significantly impact its properties. Additionally, porosity, which varies with geometry, weakens the scaffold's mechanical performance. This study investigates the influence of scaffold geometry on mechanical properties and porosity in biomedical applications. Seven distinct geometries were designed using identical materials and fabricated through 3D printing. The scaffolds underwent compressive strength testing and finite element simulations to evaluate their load-bearing capacity and porosity. Among the designs, hexagonal and circular geometries demonstrated superior mechanical performance and controlled porosity. A total of 81 hexagonal and 27 circular scaffold samples were analyzed using Abaqus software. Initially, Response Surface Methodology (RSM) was employed to model the relationship between pressure and porosity, identifying the optimal design space with high predictive accuracy (R² > 96%). Then, a multi-objective optimization process using the Multi-Objective Particle Swarm Optimization (MOPSO) algorithm was implemented. The results revealed a Pareto front for each geometry, enabling the selection of scaffolds with specific load-bearing capacities and maximum porosity levels. Validation tests showed a mean error of 3.4% for circular geometries and 3.53% for hexagonal geometries, demonstrating the reliability of the simulation and optimization methods. This comprehensive approach integrates experimental, simulation, and optimization techniques, offering a robust framework for designing high-performance scaffolds tailored to biomedical needs.