Materials knowledge system for nonlinear composites

• Published in: Computer methods in applied mechanics and engineering Vol. 346; pp. 180 - 196
• Main Authors: Latypov, Marat I., Toth, Laszlo S., Kalidindi, Surya R.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.04.2019; Elsevier BV; Elsevier
• Subjects: Composite materials; Computer simulation; Constituents; Engineering Sciences; Finite element method; Homogenization theories; Linkages; Materials knowledge systems; Mathematical analysis; Mathematical models; Micromechanics; Microstructure; Multiscale modeling; Reduced-order models; Strain hardening; Micromechanics; Homogenization theories; Reduced-order models; Materials knowledge systems; Multiscale modeling
• ISSN: 0045-7825; 1879-2138
• DOI: 10.1016/j.cma.2018.11.034

In this contribution, we present a new Materials Knowledge System framework for microstructure-sensitive predictions of effective stress–strain responses in composite materials. The model is developed for composites with a wide range of combinations of strain hardening laws and topologies of the constituents. The theoretical foundation of the model is inspired by statistical continuum theories, leveraged by mean-field approximation of self-consistent models, and calibrated to data obtained from micromechanical finite element simulations. The model also relies on newly formulated data-driven linkages between micromechanical responses (phase-average strain rates and effective strength) and microstructure as well as strength contrast of the constituents. The paper describes in detail the theoretical development of the model, its implementation into an efficient computational plasticity framework, calibration of the linkages, and demonstration of the model predictions on two-phase composites with isotropic constituents exhibiting linear and power-law strain hardening laws. It is shown that the model reproduces finite element results reasonably well with significant savings of the computational cost. •A new model for predicting effective stress–strain curves of composites is presented.•The model is based on data-driven microstructure–response linkages.•Strength contrast is additionally incorporated into linkages to capture hardening.•Model shows comparable accuracy with FEM at much lower computational cost.