Triply periodic minimal surfaces (TPMS) demonstrate remarkable potential in lightweight design, thermal management, and tissue scaffold due to their unique physical advantages. However, existing approaches often rely on empirical rules and lack physics-informed, intelligent guidance. Furthermore, the generation efficiency of TPMS products remains a significant challenge. This study presents an efficient framework that integrates data-driven design, structural optimization, and advanced lattice technologies to develop high-performance, lightweight products for additive manufacturing (AM). To explore the intricate relationship between TPMS geometry and physical properties, a two-stage optimization scheme is proposed that combines data-driven coarse optimization with gradient-based fine optimization, achieving material savings of 5% to 20% compared with other state-of-the-art methods. Furthermore, a multi-scale strategy is introduced to accelerate the design and manufacturing of conformal products by leveraging the interaction of field variables across different resolutions. The effectiveness of the framework is verified through several case studies. The final products are fabricated via AM technology and experimentally tested, confirming significant improvements in overall performance. These results highlight the contributions of the proposed framework in computational efficiency and lightweight high-performance structural design.
 

TPMS lattices; Additive manufacturing; Implicit design; Structural optimization