Adaptive Variable Design Algorithm for Improving Topology Optimization in Additive Manufacturing Guided Design

Abstract

CAD-CAE software companies have introduced numerous tools aimed at facilitating topology optimization through Finite Element Simulation, thereby enhancing accessibility for designers via user-friendly interfaces. However, the imposition of intricate constraint conditions or additional restrictions during calculations may introduce instability into the resultant outcomes. In this paper, an algorithm for updating the design variables called Adaptive Variable Design is proposed to keep the final design space volume of the optimized part consistently under the target value while giving the main algorithm multiple chances to update the optimization parameters and search for a valid design. This algorithm aims to produce results that are more conducive to manufacturability and potentially more straightforward in interpretation. A comparison between several commercial software packages and the proposed algorithm, implemented in MATLAB R2023a, is carried out to prove the robustness of the latter. By simulating identical parts under similar conditions, we seek to generate comparable results and underscore the advantages stemming from the adoption and comprehension of the proposed topology optimization methodology. Our findings reveal that the integrated enhancements within MATLAB pertaining to the topology optimization process yield favourable outcomes with respect to discretization and the manufacturability of the resultant geometries. Furthermore, we assert that the methodology evaluated within MATLAB holds promise for potential integration into commercial packages, thereby enhancing the efficiency of topology optimization processes.

Keywords

• topology optimization
• optimization software
• performance optimization
• manufacturability
• discreteness