An integrated framework for body-fitted topology optimization considering buckling load factor, stiffness, and von mises stress

Conventional density-based topology optimization methods often face challenges when addressing structural buckling failure, especially in effectively controlling buckling load factors and local von Mises stresses. This study introduces a new body-fitted topology optimization (BFTO) method capable of generating high-quality structural designs under multiple mechanical constraints, including compliance, buckling load factors, material usage, and von Mises stress. Unlike fixed-grid methods, the proposed approach employs body-fitted meshing, which captures evolving material boundaries and enhances numerical accuracy during optimization. The integration of linear material interpolation, sensitivity filtering, density projection, and Kreisselmeier–Steinhauser (KS) function-based aggregation enables efficient handling of multi-constraint formulations. Through a series of benchmark examples, we demonstrate the effectiveness of the proposed method to deliver smooth, efficient, and manufacturable designs across a wide range of constraints and boundary conditions. Parametric investigations reveal the influence of filter radius, mesh density ratio, and projection parameters on both structural performance and algorithmic convergence. Overall, the proposed BFTO framework offers a flexible and robust solution for advanced structural optimization problems, with potential applications in lightweight design and additive manufacturing.