Modeling of deposition morphology and characteristic dimensions in material extrusion additive manufacturing

Abstract

Developing prediction models for deposition strand morphology is critical in Material Extrusion Additive Manufacturing (MEAM) to optimize processes and guide innovative deposition strategies, while advancing our understanding of the flow mechanics during the deposition process.This study aimed to develop an accurate, rapid, and calibration-free model for predicting deposition strand morphology, height, and width. The relationship between the flow field constraints downstream of the nozzle and the deposition morphology was analyzed. By solving the flow front boundary in the region covered by the nozzle, a model for predicting the deposition height and width under constrained conditions was developed. Moreover, a quantitative method for predicting morphological features was offered. The established model is validated through fused deposition modeling (FDM) single-layer single-path experiments, demonstrating superior accuracy. An in-depth analysis of the model errors resulting from the assumptions in the model has been carried out.This work provided deeper insights by modeling the flow front boundary, which helps to understand the distribution of pressure flow and drag flow during the deposition process. The established model has better application potential due to its advantage of not requiring prior calibration of the machine.