Efficient buckling constrained topology optimization using reduced order modeling

We present an efficient computational approach to continuum topology optimization with linearized buckling constraints, using Reduced Order Models (ROM). A reanalysis technique is employed to generate basis vectors that subsequently are used to significantly reduce the size of the generalized eigenvalue problems. We demonstrate the efficacy of this approach by optimizing for stiffness with buckling constraints and show results for several test cases. Based on our findings, we conclude that the ROM can potentially save significant computational effort without compromising the quality of the results.

Automated summary

We propose an efficient computational approach for continuum topology optimization with linearized buckling constraints, using Reduced Order Models (ROM). A reanalysis technique is utilized to generate basis vectors, reducing the size of the generalized eigenvalue problems significantly. The approach is demonstrated through stiffness optimization with buckling constraints and shows promising results for various test cases. Based on the findings, we conclude that the ROM has the potential to save significant computational effort without compromising the quality of the results.