Developing Geometry Based Criterion Function Method for Predicting Porosity in LM6 Castings
DOI:
https://doi.org/10.24425/afe.2025.153802Abstract
One of the major issues in the metal casting process that affects productivity and energy efficiency is porosity, especially when it comes to castings that are not made in accordance with Original Equipment Manufacturers (OEMs) specifications. Predictive method is crucial to solving this problem. Criterion function is a noteworthy empirical model that has been extensively studied in the literature. By taking into account important factors like cooling rate, thermal gradient and molten metal velocity during solidification, it provides predictive insights into the location and presence of porosity. It is essential to develop a criterion function that considers the impact of geometric variation on the occurrence of shrinkage porosity. In this paper, a geometry-based model has been proposed for LM6 castings using a standard shape with three T-joints for the prediction of shrinkage porosity. The findings suggest that the presence of joints significantly influences the formation of porosity and it was also observed that an increase in the length ratio leads to a higher occurrence of shrinkage porosity. This information is vital for designers as it guides them to maintain the length ratio within a defined range to prevent shrinkage porosity in T-junction castings.References
[1] Ramesh, S., Gautam, S.K., Roy, H., Lohar, A.K., Samanta, S.K,, Anand, A., Mukherjee, D. & Kumar, S. (2024). Structure property correlation of gravity die-cast and rheocast Al–Mg–Sc–Zr in situ Nano-TiB2 composite. International Journal of Metalcasting. 18(4), 3095-103. https://doi.org/10.1007/s40962-023-01223-2.
[2] Khandelwal, H., Gautam, S.K., Ayar, V.S., Upadhyaya, R. & Kumar, A. (2024). Surface modified reinforcements on the structure properties of A356/SiC stir cast composite. Silicon. 26, 6269-6276. https://doi.org/10.1007/s12633-024-03160-z.
[3] Gautam, S.K., Roy, H., Chandrakanth, B., Lohar, A.K. & Samanta, S.K. (2024). Effect of processing parameters of rheocast on mechanical properties of Al–10.5 Si–1.7 Cu alloy. International Journal of Metalcasting. 18(1), 390-402. https://doi.org/10.1007/s40962-023-01028-3.
[4] Samuel, A.M., Doty, H.W., Valtierra, S. & Samuel, F.H. (2017). Porosity formation in Al–Si sand mold castings. International Journal of Metalcasting. 11, 812-822. https://doi.org/10.1007/s40962-016-0129-0.
[5] Tiedje, N.S., Taylor, J.A. & Easton, M.A. (2012). Feeding and distribution of porosity in cast Al-Si alloys as function of alloy composition and modification. Metallurgical and Materials Transactions A. 43, 4846-4858. https://doi.org/10.1007/s11661-012-1308-0.
[6] Mohammed, V.M., Arkanti, K. & Ferhathullah, H. (2016). Optimization of sand mould type and melting parameters to reduce porosity in Al-Si alloy castings. Leonardo Electronic Journal of Practices and Technologies. 28, 93-106. ISSN 1583-1078.
[7] Zhao, P., Dong, Z., Zhang, J., Zhang, Y., Cao, M., Zhu, Z., Zhou, H. & Fu, J. (2020). Optimization of injection‐molding process parameters for weight control: converting optimization problem to classification problem. Advances in Polymer Technology. 1, 7654249, 1-9. https://doi.org/10.1155/2020/7654249.
[8] Cao, L., Liao, D., Sun, F., Chen, T., Teng, Z. & Tang, Y. (2018). Prediction of gas entrapment defects during zinc alloy high-pressure die casting based on gas-liquid multiphase flow model. The International Journal of Advanced Manufacturing Technology. 94, 807-815. https://doi.org/10.1007/s00170-017-0926-5.
[9] Shafyei, A., Anijdan, S.M. & Bahrami, A. (2006). Prediction of porosity percent in Al–Si casting alloys using ANN. Materials Science and Engineering: A. 431(1-2), 206-210. https://doi.org/10.1016/j.msea.2006.05.150.
[10] Rathod, H., Dhulia, J.K. & Maniar, N.P. (2017). Prediction of shrinkage porosity defect in sand casting process of LM25. InIOP Conference Series: Materials Science and Engineering. 225(1), 012237. DOI:10.1088/1757-899X/225/1/012237
[11] Gautam, S.K., Roy, H., Lohar, A.K. & Samanta, S.K. (2023). Studies on mold filling behavior of Al–10.5 Si–1.7 Cu Al alloy during rheo pressure die casting system. International Journal of Metalcasting. 17(4), 2868-2877. https://doi.org/10.1007/s40962-023-00958-2.
[12] Khandelwal, H., Gautam, S.K. & Ravi, B. (2024). Numerical simulation and experimental validation of fluidity of AlSi12CuNiMg alloy using multi spiral channel with varying thickness. International Journal of Metalcasting. 19, 1202-1211. https://doi.org/10.1007/s40962-024-01383-9.
[13] Chudasama, B.J. (2013). Solidification analysis and optimization using pro-cast. International Journal of Research in Modern Engineering and Emerging Technology. 1(4), 9-19. ISSN: 2320-6586.
[14] Ayar, M.S., Ayar, V.S. & George, P.M. (2020). Simulation and experimental validation for defect reduction in geometry varied aluminium plates casted using sand casting. Materials Today: Proceedings. 27(4), 1422-1430. https://doi.org/10.1016/j.matpr.2020.02.788.
[15] Hirata, N. & Anzai, K. (2017). Numerical simulation of shrinkage formation behavior with consideration of solidification progress during mold filling using stabilized particle method. Materials Transactions. 58(6), 932-939. https://doi.org/10.2320/matertrans.F-M2017811.
[16] Bekele, B.T., Bhaskaran, J., Tolcha, S.D. & Gelaw, M. (2022). Simulation and experimental analysis of re-design the faulty position of the riser to minimize shrinkage porosity defect in sand cast sprocket gear. Materials Today: Proceedings. 1(59), 598-604. https://doi.org/10.1016/j.matpr.2021.12.090.
[17] Choudhari, C.M., Narkhede, B.E. & Mahajan, S.K. (2014). Casting design and simulation of cover plate using AutoCAST-X software for defect minimization with experimental validation. Procedia Materials Science. 6, 786-797. https://doi.org/10.1016/j.mspro.2014.07.095.
[18] Kimio, K. & Pehlke, R.D. (1985). Mathematical modeling of porosity formation in solidification. Metallurgical Transactions. B16, 359-366. https://doi.org/10.1007/BF02679728.
[19] Chen, Yin-Heng, & Yong-Taek Im, (1990). Analysis of solidification in sand and permanent mold castings and shrinkage prediction. International Journal of Machine Tools and Manufacture. 30(2), 175-189. https://doi.org/10.1016/0890-6955(90)90128-6.
[20] Sabau, A.S. & Viswanathan, S. (2002). Microporosity prediction in aluminum alloy castings. Metallurgical and Materials Transactions. B33 (2), 243-255. https://doi.org/10.1007/s11663-002-0009-2.
[21] Pequet, Ch., Rappaz, M. & Gremaud, M. (2002). Modeling of microporosity, macroporosity, and pipe-shrinkage formation during the solidification of alloys using a mushy-zone refinement method: applications to aluminum alloys. Metallurgical and Materials Transactions. A33(7), 2095-2106. https://doi.org/10.1007/s11661-002-0041-5.
[22] Dawei, S. & Garimella, S.V. (2006). Numerical and experimental investigation of solidification shrinkage. Numerical Heat Transfer, Part A: Applications. 52(2), 145-162. https://doi.org/10.1080/10407780601115079.
[23] De Obaldia, E. Escobar, & Felicelli, S.D. (2007). Quantitative prediction of microporosity in aluminum alloys. Journal of Materials Processing Technology. 191(1-3), 265-269. https://doi.org/10.1016/j.jmatprotec.2007.03.072.
[24] Reis, A., Houbaert, Y., Zhian Xu, Van Tol, R., Santos, A.D., Duarte, J.F. & Magalhaes, A.B. (2013). Modeling of shrinkage defects during solidification of long and short freezing materials. Journal of Materials Processing Technology. 202(1-3), 428-434. https://doi.org/10.1016/j.jmatprotec.2007.10.030.
[25] Mazloum, K., & Sata, A. (2024). Development of geometry-driven quantitative prediction for shrinkage porosity in T-junction of steel sand castings. Turkish Journal of Engineering. 8(4), 640-646. https://doi.org/10.31127/tuje.1454237.
[26] Sata, A. & Dharaiya, V. (2022). Geometry-driven criterion function for predicting shrinkage porosity in stainless steel castings with T-junction. Journal of Advanced Manufacturing Systems. 21(03), 625-38. https://doi.org/10.1142/S0219686722500226.
[27] Sata, A., Maheta, N., Dave, A. & Khandelwal, H. (2025). Geometry based and simulation supported porosity prediction in ductile iron casting. Engineering Research Express. 7, 015411, 1-12. DOI:10.1088/2631-8695/ada71e.
[28] Kamalesh, S., Pavan, R., Durgesh, J., Karupppasamy, S. Ravi, B. (2008). 3D junctions in castings: simulation-based DFM analysis and guidelines. In INAE International Conference on Advances in Manufacturing Technology (ICAMT 2008), 6-8 February 2008.
