High-Resolution Thermal Simulation Framework for Extrusion-based Additive Manufacturing of Complex Geometries

TL;DR

This paper introduces a scalable, high-resolution thermal simulation framework for extrusion-based additive manufacturing, enabling real-time predictions and potential closed-loop control for complex geometries.

Contribution

It presents a novel adaptive octree-based simulation framework that efficiently models transient thermal behavior during 3D printing of complex shapes.

Findings

Simulation runs faster than real print time

Scales to high voxel resolutions with complex geometries

Potential for real-time control and optimization

Abstract

Accurate simulation of the printing process is essential for improving print quality, reducing waste, and optimizing the printing parameters of extrusion-based additive manufacturing. Traditional additive manufacturing simulations are very compute-intensive and are not scalable to simulate even moderately sized geometries. In this paper, we propose a general framework for creating a digital twin of the dynamic printing process by performing physics simulations with the intermediate print geometries. Our framework takes a general extrusion-based additive manufacturing G-code, generates an analysis-suitable voxelized geometry representation from the print schedule, and performs physics-based (transient thermal) simulations of the printing process. Our approach leverages adaptive octree meshes for both geometry representation as well as for fast simulations to address real-time predictions. We demonstrate the effectiveness of our method by simulating the printing of complex geometries at high voxel resolutions with both sparse and dense infills. Our results show that this approach scales to high voxel resolutions and can predict the transient heat distribution as the print progresses. Because the simulation runs faster than real print time, the same engine could, in principle, feed thermal predictions back to the machine controller (e.g., to adjust fan speed or extrusion rate). The present study establishes the computational foundations for a real-time digital twin, which can be used for closed control loop control in the future.