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Main Authors: Rojas, Carlos J. G., Mollah, Md. Tusher, Gómez-Pérez, C. A., Özkan, Leyla
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2508.20617
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author Rojas, Carlos J. G.
Mollah, Md. Tusher
Gómez-Pérez, C. A.
Özkan, Leyla
author_facet Rojas, Carlos J. G.
Mollah, Md. Tusher
Gómez-Pérez, C. A.
Özkan, Leyla
contents Accurate numerical simulation of material extrusion additive manufacturing requires reliable tracking of evolving material interfaces while preserving mass conservation. Inaccurate mass conservation can lead to significant discrepancies between simulated and deposited strand geometries, undermining the predictive capability of the model. In this work, we investigate the mass conservation performance of the conservative level-set (CLS) method in extrusion-based 3D printing simulations. A systematic parametric study is conducted to quantify the influence of the interface thickness and reinitialization parameters on mass conservation, using the steady-state cross-sectional area of deposited strands as a quantitative metric. Simulated cross-sections are compared against reference values obtained from analytical mass balance relations. The results show that reducing both the interface thickness and the reinitialization parameter improves mass conservation accuracy, although diminishing returns and increased computational cost are observed beyond certain thresholds. In addition, appropriate tuning of the interface thickness can relax mesh refinement requirements while maintaining acceptable accuracy. The proposed parameter selection strategy is validated across a range of printing conditions, materials, and nozzle geometries, including multilayer deposition of viscoplastic fluids. The simulations show reasonable agreement with experimentally validated data from the literature, confirming that careful CLS parameter tuning enables accurate and computationally efficient prediction of strand geometry in extrusion-based 3D printing.
format Preprint
id arxiv_https___arxiv_org_abs_2508_20617
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Mass conservation analysis of extrusion-based 3D printing simulations based on the level-set method
Rojas, Carlos J. G.
Mollah, Md. Tusher
Gómez-Pérez, C. A.
Özkan, Leyla
Computational Engineering, Finance, and Science
Accurate numerical simulation of material extrusion additive manufacturing requires reliable tracking of evolving material interfaces while preserving mass conservation. Inaccurate mass conservation can lead to significant discrepancies between simulated and deposited strand geometries, undermining the predictive capability of the model. In this work, we investigate the mass conservation performance of the conservative level-set (CLS) method in extrusion-based 3D printing simulations. A systematic parametric study is conducted to quantify the influence of the interface thickness and reinitialization parameters on mass conservation, using the steady-state cross-sectional area of deposited strands as a quantitative metric. Simulated cross-sections are compared against reference values obtained from analytical mass balance relations. The results show that reducing both the interface thickness and the reinitialization parameter improves mass conservation accuracy, although diminishing returns and increased computational cost are observed beyond certain thresholds. In addition, appropriate tuning of the interface thickness can relax mesh refinement requirements while maintaining acceptable accuracy. The proposed parameter selection strategy is validated across a range of printing conditions, materials, and nozzle geometries, including multilayer deposition of viscoplastic fluids. The simulations show reasonable agreement with experimentally validated data from the literature, confirming that careful CLS parameter tuning enables accurate and computationally efficient prediction of strand geometry in extrusion-based 3D printing.
title Mass conservation analysis of extrusion-based 3D printing simulations based on the level-set method
topic Computational Engineering, Finance, and Science
url https://arxiv.org/abs/2508.20617