A posteriori modeling error estimates in the optimization of two-scale elastic composite materials

TL;DR

This paper develops an a posteriori error estimation method for optimizing two-scale elastic composite materials, balancing discretization and modeling errors to produce simple microstructures that nearly match the optimal compliance of complex nested laminates.

Contribution

It introduces a dual weighted residual approach for error estimation in two-scale elasticity optimization, enabling the design of simplified microstructures with near-optimal compliance.

Findings

Adaptive scheme produces microstructures competing with nested laminates.

Simplified microstructures achieve compliance within a few percent of the optimal.

Optimal grid refinement balances discretization and modeling errors.

Abstract

The a posteriori analysis of the discretization error and the modeling error is studied for a compliance cost functional in the context of the optimization of composite elastic materials and a two-scale linearized elasticity model. A mechanically simple, parametrized microscopic supporting structure is chosen and the parameters describing the structure are determined minimizing the compliance objective. An a posteriori error estimate is derived which includes the modeling error caused by the replacement of a nested laminate microstructure by this considerably simpler microstructure. Indeed, nested laminates are known to realize the minimal compliance and provide a benchmark for the quality of the microstructures. To estimate the local difference in the compliance functional the dual weighted residual approach is used. Different numerical experiments show that the resulting adaptive scheme leads to simple parametrized microscopic supporting structures that can compete with the optimal nested laminate construction. The derived a posteriori error indicators allow to verify that the suggested simplified microstructures achieve the optimal value of the compliance up to a few percent. Furthermore, it is shown how discretization error and modeling error can be balanced by choosing an optimal level of grid refinement. Our two scale results with a single scale microstructure can provide guidance towards the design of a producible macroscopic fine scale pattern.