Data-driven material identification in micromorphic continua

Abstract

We introduce a data-driven framework for identifying material behavior from full-field kinematics and external force measurements in generalized (micromorphic) continua. The aim is to determine whether such input data can reveal generalized stress--strain states and their constitutive response without prescribing closure relations or relying on RVE-based homogenization. To this end, the approach infers the associated generalized stresses from full-field boundary value problems and constructs representative material datasets via clustering in a non-classical phase space. We show that the proposed method reliably extracts non-symmetric and higher-order local stress states, providing material data suitable for either model calibration or model-free data-driven simulations of generalized continua. These capabilities are demonstrated in linear and nonlinear validation simulations with synthetic data, and in an application to mechanical metamaterials, suggesting a practical route for material characterization of microstructured solids.

Revised version, accepted for publication in the Journal of the Mechanics and Physics of Solids