Author(s)

Mohamed-Ali Rezgui^1*, Mohamed-Toumi Nasri², Mahfoudh Ayadi²

¹UR-MSSDT (99-UR11-46), Ecole Nationale Supérieure d’Ingénieurs de Tunis, ENSIT, University of Tunis, Tunis, Tunisia.
²Department of Mechanical Engineering, Ecole Nationale d’Ingénieurs de Bizerte, ENIB, University of Cartage, Bizerte, Tunisia.

The purpose of the current work is the development and application of a new identification method of material parameters of elastoplastic damage constitutive model under large strains. A relationship relating the intrinsic and extrinsic parameters of a reference material is built and transformed in equivalence relation. Extrinsic parameters concern the shape of their experimental tensile force/elongation curve, however, intrinsic parameters deal with Swift hardening law coupled with an isotropic damage variable. The relationship is carried out from a statistical characterization of a material reference (standard-steel E24). It based on multiple linear regression of a data set obtained according to a full factor design of numerical simulations of mechanical tensile tests. All materials satisfying this equivalence relation belong to the same equivalence class. This is motivated by observing that gathered materials must behave somewhat like the reference material. The material parameters can be immediately identified by only one task by running the found relationship. The current method facilitates the identification procedure and offers a substantial savings in CPU time. However it just needs only one simulation for the identification of similar behavior instead of the few hundred required when using other methods.

Characterization, Parameter Identification, Tensile Tests, Standard-Steel E24, Elastoplastic Damage Constitutive Law, Equivalence Class

Rezgui, M. , Nasri, M. and Ayadi, M. (2016) Predictive Elastoplastic Damage Constitutive Law: Establishment of Equivalence Relation between Intrinsic and Extrinsic Material Parameters. Materials Sciences and Applications, 7, 730-753. doi: 10.4236/msa.2016.711058.