Numerical analysis of molten iron flow and heat transfer in plumbing casting defect detection using split tracking approach
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Issued Date
2025-08-01
Resource Type
ISSN
2214157X
Scopus ID
2-s2.0-105006480073
Journal Title
Case Studies in Thermal Engineering
Volume
72
Rights Holder(s)
SCOPUS
Bibliographic Citation
Case Studies in Thermal Engineering Vol.72 (2025)
Suggested Citation
Namchanthra S., Phirommark P., Phengpom T., Priyadumkol J., Wijitdamkerng W., Chookaew W., Suvanjumrat C., Promtong M. Numerical analysis of molten iron flow and heat transfer in plumbing casting defect detection using split tracking approach. Case Studies in Thermal Engineering Vol.72 (2025). doi:10.1016/j.csite.2025.106287 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/110473
Title
Numerical analysis of molten iron flow and heat transfer in plumbing casting defect detection using split tracking approach
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Abstract
Gravity sand casting, widely utilised in plumbing manufacturing for metal part production, is the focus of this research to enhance its efficiency. Computational Fluid Dynamics (CFD) was employed to address molten flow, solidification, and cooling dynamics to reduce surface and internal defects. FLOW-3D CAST software was utilised with Volume of Fluid (VOF) method to examine flow patterns during the filling and solidification process. Suitable riser locations, quantities, and sprue placements were determined, emphasising their critical role in enhancing quality. The control of crystallisation temperatures and accurate positioning of pouring caps were also highlighted. Insights into refining gravity sand casting are provided, laying the groundwork for future CFD validation studies to confirm defect reduction in air valve production and further improvements in process parameters. Rapid filling within 20 s at 1550 °C influenced a 740-s solidification process. Key solidification phases between 100 and 600 s were crucial for improving casting efficiency and quality. Proper riser and sprue configurations were found to be essential for process efficiency and waste reduction, demonstrating economic benefits for sustainable manufacturing practices. Enhanced accuracy in simulating fluid dynamics during casting was achieved by benchmarking Split Lagrangian tracking schemes against other methods, which is critical for predicting process behaviours.