Two-scale elastic parameter identification from noisy macroscopic data

Abstract

A two-scale parameter identification procedure to identify microscopic elastic parameters from macroscopic data is introduced and thoroughly analyzed. The macroscopic material behavior of microscopically linear elastic heterogeneous materials is described by means of numerical homogenization. The microscopic material parameters are assumed to be unknown and are identified from noisy macroscopic displacement data. Various examples of microscopically heterogeneous materials—with regularly distributed pores, particles, or layers—are considered, and their parameters are identified from different macroscopic experiments by means of a gradient-based optimization procedure. The reliability of the identified parameters is analyzed by their standard deviations and correlation matrices. It was found that the two-scale parameter identification works well for cellular materials, but has to be designed carefully for layered materials. If the homogenized macroscopic material behavior can be described by less material parameters than the microscopic material behavior, as, e.g., for regularly distributed particles, the identification of all microscopic parameters from macroscopic experiments is not possible.