Integrating Topology Optimization and Lattice Infilling for Lightweight Aircraft Bracket Design via Additive Manufacturing

Integrating topology optimization (TO) with lattice infilling for additive manufacturing provides an effective route to lightweight, high-performance structures for aerospace applications. Reducing structural mass can deliver environmental and economic benefits by lowering fuel consumption and associated emissions. This study evaluates a computational workflow for weight reduction of an aircraft bearing bracket by combining topology optimization with stress guided lattice infilling. First, compliance minimizing TO is performed under additive manufacturing constraints to obtain an efficient global load-path layout. Next, lattice infill is introduced using both Triply Periodic Minimal Surface (TPMS) unit cells (gyroid) and strut-based unit cells (diamond). To avoid manual trial-and-error in selecting unit cell size, and thickness, an implicit modeling approach with Python-driven iteration is used to systematically explore lattice parameters and identify feasible configurations. The proposed method uses the TO-derived stress field to tailor lattice parameters spatially, enabling graded cellular architectures aligned with local load demands. Compared with the baseline bracket, TO alone achieved a 44.42% mass reduction, while the stress-guided lattice designs achieved 70% (gyroid) and 68.6% (diamond) weight savings. Finite element analysis is used to compare the baseline, TO, and lattice-infilled brackets in terms of mass, maximum deflection, and von Mises stress, demonstrating that stress-guided lattice infill can improve structural efficiency beyond TO alone while maintaining AM oriented manufacturability through self-supporting cellular features. A key contribution is an automated, stress-guided ramp mapping for graded lattice-parameter control, which is broadly applicable to other components, loading scenarios, and lattice families.