Abstract
The study of the interfacial heat transfer coefficient (IHTC) is one of the major concerns during solidification of casting. In order to find out the IHTC at the metal–mold interface, a one dimensional transient heat conduction model is numerically investigated during horizontal directional solidification of Sn–5wt%Pb alloy. The forward model is solved using explicit finite difference method to obtain the exact temperatures for the known boundary conditions. The estimation of the unknown IHTC is attempted using Particle Swarm Optimization (PSO) as an inverse approach along with Bayesian framework. In order to prove the robustness of the proposed methodology, the estimation is accomplished for the simulated measurements. The simulated measurements are then added with noise to replicate the experimental data. The present approach not only minimizes the difference between simulated and measured temperatures but also takes in to account “a priori” information about the unknown parameters.
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References
Davey K (1993) An analytical solution for the unidirectional solidification problem. Appl Math Model 17(12):658–663
Stefanescu DM (2015) Science and engineering of casting solidification. Springer, Berlin
Jonathan WW, Woodbury K (2008) Accounting for sensor errors in estimation of surface heat flux by an inverse method. In: Proceedings of the ASME summer heat transfer conference, HT
Beck JV, Blackwell B, Clair C (1985) Inverse heat conduction, ill-posed problems. Wiley, London
Ho K, Pehlke RD (1985) Metal-mold interfacial heat transfer. Metall Mater Trans B 16(3):585–594
Nishida Y, Droste W, Engler S (1986) The air-gap formation process at the casting-mold interface and the heat transfer mechanism through the gap. Metall Mater Trans B 17(4):833–844
Santos CA, Siqueira CA, Garcia A, Quaresma JM, Spim JA (2004) Metal–mold heat transfer coefficients during horizontal and vertical unsteady-state solidification of Al–Cu and Sn–Pb alloys. Inv Prob Sci Eng 12(3):279–296
Vasileiou AN, Vosniakos GC, Pantelis DI (2015) Determination of local heat transfer coefficients in precision castings by genetic optimisation aided by numerical simulation. In: Proceedings of the Institution of Mechanical Engineers, Part C: J Mech Eng Sci, vol 229, issue 4, pp 735–750
Vasileiou AN, Vosniakos GC, Pantelis DI (2017) On the feasibility of determining the heat transfer coefficient in casting simulations by genetic algorithms. Procedia Manuf (11):509–516, ISSN 2351-9789
Yu Y, Luo X (2017) Identification of heat transfer coefficients of steel billet in continuous casting by weight least square and improved difference evolution method. Appl Therm Eng 114:36–43
Silva JN, Moutinho DJ, Moreira AL, Ferreira IL, Rocha OL (2011) Determination of heat transfer coefficients at metal–mold interface during horizontal unsteady-state directional solidification of Sn–Pb alloys. Mat Chem Phys 130(1):179–185
Ranjbar AA, Ghaderi A, Dousti P, Famouri M (2011) A transient two-dimensional inverse estimation of the metal-mold heat transfer coefficient during squeeze casting of AL-4.5 wt% CU. Int J Eng-Trans A Basics 23(3 and 4):273
Kennedy J, Eberhart RC (1995) Particle swarm optimization. In: Proceedings of IEEE international conference on neural network, pp 1942–1948
Vakili S, Gadala MS (2009) Effectiveness and efficiency of particle swarm optimization technique in inverse heat conduction analysis. Num Heat Trans Part B: Fundamentals 56:119–141
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Vishweshwara, P.S., Gnanasekaran, N., Arun, M. (2019). Inverse Estimation of Interfacial Heat Transfer Coefficient During the Solidification of Sn-5wt%Pb Alloy Using Evolutionary Algorithm. In: Lakshminarayanan, A., Idapalapati, S., Vasudevan, M. (eds) Advances in Materials and Metallurgy. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-13-1780-4_23
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DOI: https://doi.org/10.1007/978-981-13-1780-4_23
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