Identification Method of Constitutive Material Parameters for Additively Manufactured Structures Using an Inverse Optimization Strategy

Abstract

Abstract The parameters of a constitutive model of a fused deposition modeling (FDM) additively manufactured part were calculated with a novel computational tool of inverse optimization. The finite element (FE) model was used to calibrate the printed part’s properties, incorporates a composite shell section of linear elastic orthotopic material under plane stress, various design configurations following a Taguchi L18 orthogonal array, were modelled in Abaqus CAE 2021 following the classical laminate theory (CLT). The material studied was PLA. The plastic mechanical behavior was taken into account with various stress-based failure criteria normally used in fiber-reinforced composite materials. Initially an investigation based on experiments of 3D printed FDM specimens determined stress-strain curves for various types of geometry and loading. Then, inverse optimization was performed with the interior point (IP) method, which calculates material parameters of the constitutive model of the parts. It was shown that the experimental response of 3D printed FDM processed parts can be estimated accurately numerically with material parameters calculated with the new inverse optimization tool proposed.