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Article

Optimization of Printing Parameters Based on Computational Fluid Dynamics (CFD) for Uniform Filament Mass Distribution at Corners in 3D Cementitious Material Printing

1
Aerospace Times Feihong Technology Company Limited, Beijing 100029, China
2
Singapore Centre for 3D Printing, Nanyang Technological University, Singapore 639798, Singapore
3
National Superior College for Engineers, Northwestern Polytechnical University, Xi’an 710072, China
*
Authors to whom correspondence should be addressed.
Crystals 2025, 15(8), 725; https://doi.org/10.3390/cryst15080725
Submission received: 8 July 2025 / Revised: 3 August 2025 / Accepted: 4 August 2025 / Published: 15 August 2025

Abstract

Three-dimensional cementitious material printing (3DCMP) enables structures with complex geometry to be fabricated. Printed filament quality is significantly affected by the mass distribution at its corners. Although fruitful results have been obtained, a significant gap exists in systematically investigating the impact of comprehensive parameters on this mass distribution. Therefore, the cross-section ratio Φ (Φ = So/Su) of the filament is proposed as a measurement to evaluate the mass distribution at corners. Then, the impacts of printing process parameters, including the tool path radius R, nozzle aspect ratio φ, and relative nozzle travel speed ζ, on the filament mass distribution are investigated using computational fluid dynamics (CFD). The flow mechanism is elaborated using CFD for cementitious material printing at corners. It was found that the material flow mechanism caused by the combined effects of the printing process parameters affects the filament mass distribution significantly. Some material spills out from the overfilled zone to the underfilled zone during the deposition process. Additionally, printing process windows were identified to ensure acceptable printing quality using a support vector machine (SVM). A new printing window is identified using transfer learning, which can save data resources compared to the SVM method. Finally, the experimental results show the feasibility and effectiveness of the proposed methods in printing process window determination.
Keywords: 3DCMP; filament mass distribution; CFD; machine learning; printing process windows 3DCMP; filament mass distribution; CFD; machine learning; printing process windows

Share and Cite

MDPI and ACS Style

Liu, Z.; Si, L.; Liu, Y.; Li, M.; Wong, T.N. Optimization of Printing Parameters Based on Computational Fluid Dynamics (CFD) for Uniform Filament Mass Distribution at Corners in 3D Cementitious Material Printing. Crystals 2025, 15, 725. https://doi.org/10.3390/cryst15080725

AMA Style

Liu Z, Si L, Liu Y, Li M, Wong TN. Optimization of Printing Parameters Based on Computational Fluid Dynamics (CFD) for Uniform Filament Mass Distribution at Corners in 3D Cementitious Material Printing. Crystals. 2025; 15(8):725. https://doi.org/10.3390/cryst15080725

Chicago/Turabian Style

Liu, Zhixin, Liang Si, Yebao Liu, Mingyang Li, and Teck Neng Wong. 2025. "Optimization of Printing Parameters Based on Computational Fluid Dynamics (CFD) for Uniform Filament Mass Distribution at Corners in 3D Cementitious Material Printing" Crystals 15, no. 8: 725. https://doi.org/10.3390/cryst15080725

APA Style

Liu, Z., Si, L., Liu, Y., Li, M., & Wong, T. N. (2025). Optimization of Printing Parameters Based on Computational Fluid Dynamics (CFD) for Uniform Filament Mass Distribution at Corners in 3D Cementitious Material Printing. Crystals, 15(8), 725. https://doi.org/10.3390/cryst15080725

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