Geometric dimensionality control of structural components in topology optimization

The present contribution derives a theoretical framework for constructing novel geometrical constraints in the context of density-based topology optimization. Principally, the predefined geometrical dimensionality is enforced locally on the components of the optimized structures. These constraints are defined using the principal values (singular values) from a singular value decomposition of points clouds represented by elemental centroids and the corresponding relative density design variables. The proposed approach is numerically implemented for demonstrating the designing of lattice or membrane-like structures. Several numerical examples confirm the validity of the derived theoretical framework for geometric dimensionality control.

Automated summary

This paper presents a theoretical framework for constructing novel geometrical constraints in density-based topology optimization. The predefined geometrical dimensionality is enforced locally on the components of the optimized structures by using singular value decomposition of point clouds and relative density design variables. Numerical examples demonstrate the validity of the derived theoretical framework for geometric dimensionality control.