Determination of transient interfacial heat transfer coefficients in chill mold castings

Santos, Carlos Alexandre dos; Quaresma, José M.V.; Garcia, Amauri

doi:10.1016/s0925-8388(01)00904-5

Cited by 168 publications

(121 citation statements)

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“…Distribution of temperature of the solidifying material is described by the heat conduction equation [1][2][3][4]:…”

Section: Governing Equationsmentioning

confidence: 99%

“…Having the assumed form of function describing this contribution we can transform the equation into the heat conduction equation with the so called substitute thermal capacity. In this way, the considered differential equation defines the heat conduction in the entire homogeneous domain (in solid phase, in twophase zone (mushy zone) and in liquid phase) [1][2][3][4].Process of the alloy solidification is also affected by the process of segregation of the alloy components, for example, the change of concentration corresponds with the change of liquidus and solidus temperatures. Models, the most often used for describing the concentration, are these ones in which the immediate equalization of chemical composition of the alloy in the liquid phase and solid phase is assumed (the lever arm rule) [5][6][7][8] as well as the Scheil model [6,7,9,10].…”

mentioning

confidence: 99%

“…In this way, the considered differential equation defines the heat conduction in the entire homogeneous domain (in solid phase, in twophase zone (mushy zone) and in liquid phase) [1][2][3][4].…”

mentioning

confidence: 99%

mentioning

confidence: 99%

“…In this paper we consider a model in which the distribution of temperature is described by means of the heat conduction equation [2][3][4] with the substitute thermal capacity and with the liquidus and solidus temperatures varying in dependence on the concentration of the alloy component. Whereas for describing the concentration we apply the model based on the lever arm rule.…”

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confidence: 99%

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Inverse problem for the solidification of binary alloy in the casting mould solved by using the bee optimization algorithm

Hetmaniok

2015

Heat Mass Transfer

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of solidification in the temperature interval is based on the heat conduction equation with the included source element in which the latent heat of fusion and the volume contribution of solid phase are taken into account. Having the assumed form of function describing this contribution we can transform the equation into the heat conduction equation with the so called substitute thermal capacity. In this way, the considered differential equation defines the heat conduction in the entire homogeneous domain (in solid phase, in twophase zone (mushy zone) and in liquid phase) [1][2][3][4].Process of the alloy solidification is also affected by the process of segregation of the alloy components, for example, the change of concentration corresponds with the change of liquidus and solidus temperatures. Models, the most often used for describing the concentration, are these ones in which the immediate equalization of chemical composition of the alloy in the liquid phase and solid phase is assumed (the lever arm rule) [5][6][7][8] as well as the Scheil model [6,7,9,10].In this paper we consider a model in which the distribution of temperature is described by means of the heat conduction equation [2][3][4] with the substitute thermal capacity and with the liquidus and solidus temperatures varying in dependence on the concentration of the alloy component. Whereas for describing the concentration we apply the model based on the lever arm rule. And the discussed problem lies in determination of the heat transfer coefficient appearing in the third kind boundary condition defined on the boundary of solidifying alloy. Additionally, the reconstruction of temperature in the region of solidifying alloy should be also obtained. The sought elements will be calculated on the basis of temperature measurements read in selected point of the mould.Since the considered problem consists in reconstruction of some missing part of input information on the basis Abstract In this paper the procedure for solving the inverse problem for the binary alloy solidification in the casting mould is presented. Proposed approach is based on the mathematical model suitable for describing the investigated solidification process, the lever arm model describing the macrosegregation process, the finite element method for solving the direct problem and the artificial bee colony algorithm for minimizing the functional expressing the error of approximate solution. Goal of the discussed inverse problem is the reconstruction of heat transfer coefficient and distribution of temperature in investigated region on the basis of known measurements of temperature.

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“…Distribution of temperature of the solidifying material is described by the heat conduction equation [1][2][3][4]:…”

Section: Governing Equationsmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Inverse problem for the solidification of binary alloy in the casting mould solved by using the bee optimization algorithm

Hetmaniok

2015

Heat Mass Transfer

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Evolution of the Microstructure and Microsegregation in Subrapidly Solidified Mg–6Al–4Zn–1.2Sn Magnesium Alloy

Cui

Luo

et al. 2020

Adv Eng Mater

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The evolution of the microstructure and microsegregation in a new type of Mg–6Al–4Zn–1.2Sn (wt%) cast magnesium alloy solidified at cooling rates from 4.5 × 101 °C s−1 to 2.3 × 103 °C s−1 is investigated. The results indicate that the secondary dendrite arm spacing and the average grain sizes decrease from 14.3 to 2.9 μm and from 187 to 78 μm, respectively, as the cooling rate increases from 4.5 × 101 °C s−1 to 2.3 × 103 °C s−1. The relationship between the secondary dendrite arm spacing (λ2) and cooling rate (R) is fitted as λ2 = 69.7 × R−0.42. When the alloy solidifies in the range of cooling rates, a new quasi‐crystalline I phase is formed due to faster solidification. The microsegregation ratios of Al, Zn, and Sn elements decrease significantly with the increase in cooling rate. Compared with the specimen solidified at 4.5 × 101 °C s−1, the microsegregation ratios of Al, Zn, and Sn of that solidified at a cooling rate of 2.3 × 103 °C s−1 decrease by 37.4%, 45.7%, and 31.6%, respectively.

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Modelling of metal–mold interface resistance in the A356 Aluminium alloy casting process

Mirbagheri

2006

Commun. Numer. Meth. Engng.

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SUMMARYIn this study, a computational model has been developed for determination of metallostatic pressure on the heat transfer coefficient, resistance of metal-mold interface and solidification time for solving of heat transfer equations. The simulation of interface resistance is based on the zero thickness element (ZTE), using the finite element method (FEM). The solid boundary conditions, including contact resistance have been modified by pressure gradient in each ZTE. The pressure gradient has been imposed by an experimental function, which obtained based on experimental data. In order to verify the computational results, an A356 Aluminium alloy has been poured into a permanent mold and temperature of interface was measured by data acquisition system. The comparison between the experimental and the simulation results during solidification process shows a good agreement that confirms the accuracy of the model in order to simulate the effect of interface resistance on the solidification time.

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Determination of transient interfacial heat transfer coefficients in chill mold castings

Cited by 168 publications

References 13 publications

Inverse problem for the solidification of binary alloy in the casting mould solved by using the bee optimization algorithm

Inverse problem for the solidification of binary alloy in the casting mould solved by using the bee optimization algorithm

Evolution of the Microstructure and Microsegregation in Subrapidly Solidified Mg–6Al–4Zn–1.2Sn Magnesium Alloy

Modelling of metal–mold interface resistance in the A356 Aluminium alloy casting process

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