Multiphysics optimization of additive manufacturing of hemp fiber reinforced polylactic acid composite honeycomb structures

Abstract

This paper focuses on optimizing the additive manufacturing of a hemp/PolyLactic Acid composite honeycomb structure using the pellet-based 3D printing as material extrusion process. Based on the Diffusion, Coalescence, Crystallization (DCC) model recently introduced in the literature, this study proposes an optimization of the process parameters to maximize the compression properties of the printed bio-composite honeycomb structure. During 3D printing, the deposition of new strands tends to change the temperature in the previously printed strands. Using the thermal properties of PLA-hemp bio-composite and printing parameters, the Backward Differentiation Formula implicit method was used for solving the numerical simulation of the heat transfer during the printing of successive layers in order to calculate the temperature distribution and history. The heat transfer process was modeled by the transient heat conduction equation and the boundary conditions. At the end of simulations, the temperatures at the interface of the strands were used from probes positioned at each thermal contact and measuring the average temperature of the interface to calculate the DCC parameter. The mechanical performance of bio-composite PLA/hemp honeycomb structure was evaluated discussed using different machine parameters combinations as extrusion temperature, layer height, flow speed and platform temperature. The obtained results showed that minimizing the layer height while maximizing the extrusion temperature, the build platform temperature and the printing flow speed effectively enhances the compression properties of the structure. Experimental measurements of the axial compressive modulus and strength of the honeycomb structure validated these findings and highlighted the improved interlayer adhesion achieved by employing the best process parameters.