Data-driven material data 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.

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BibTeX RIS

BibTeX

@article{ulloa2026datadriven,
  title = {{Data-driven material data identification in micromorphic continua}},
  author = {Jacinto Ulloa and Laurent Stainier},
  journal = {Journal of the Mechanics and Physics of Solids},
  year = {2026},
  month = sep,
  doi = {10.1016/j.jmps.2026.106742},
  eprint = {2512.15646},
  archivePrefix = {arXiv},
  url = {https://hal.science/hal-05741474v1},
  note = {CC BY-NC-ND 4.0},
}

RIS

TY  - JOUR
TI  - Data-driven material data identification in micromorphic continua
AU  - Jacinto Ulloa
AU  - Laurent Stainier
PY  - 2026
DA  - 2026/09/07
JO  - Journal of the Mechanics and Physics of Solids
DO  - 10.1016/j.jmps.2026.106742
UR  - https://hal.science/hal-05741474v1
AB  - 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.
SN  - 0022-5096
ER  -

Abstract

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