MAP123-EP: A mechanistic-based data-driven approach for numerical elastoplastic analysis

摘要: Abstract In this paper, a mechanistic-based data-driven approach, MAP123-EP, is proposed for numerical analysis of elastoplastic materials. method, stress-update driven by set one-dimensional stress–strain data generated or physical experiments under uniaxial loading. Numerical results indicate that combined with the classical strain-driven scheme, method can predict mechanical response isotropic materials (characterized J2 plasticity model isotropic/kinematic hardening and associated Drucker–Prager model) accurately without resorting to typical ingredients model-based plasticity, such as decomposing total strain into elastic plastic parts, well identifying explicit functional expressions yielding surface curve. This approach has potential opening up new avenue problems where complex material behaviors cannot be described in function/functional forms. The applicability limitation are also discussed.