Bi-directional evolutionary structural optimization with buckling constraints

Abstract Buckling is a critical phenomenon in structural members under compression, which could cause catastrophic failure of structure. To increase the buckling resistance design, novel topology optimization approach based on bi-directional evolutionary (BESO) method proposed this study with consideration constraints. The BESO benefits from using only two discrete statuses (solid and void) for design variables, thereby alleviating numerical issues associated pseudo modes. Kreisselmeier-Steinhauser aggregation function introduced to aggregate multiple constraints into differentiable one. An augmented Lagrangian multiplier developed integrate objective ensure computational stability. Besides, modified variable update scheme control rate after target volume fraction reached. Four examples are investigated demonstrate effectiveness buckling-constrained method. results show that algorithm can significantly improve stability slight compliance.