Determination of the thermophysical properties of titanium alloys from liquid bath profiles

Ледер, М. О.; Gorina, A. V.; Kornilova, M. A.; Tarenkova, N. Yu.; Kondrashov, E. N.

doi:10.1134/s0036029515120083

Cited by 4 publications

(3 citation statements)

References 6 publications

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Section: Introductionmentioning

confidence: 99%

“…Because the physical and chemical phenomena and ingot morphology of the vacuum consumable smelting process are difficult to observe, and the cost of industrial testing of titanium alloy production is high, the numerical calculation method has gradually replaced the traditional trial and error method as the main method to study the solidification structure. Numerical calculation can not only directly observe the formation of the solidification structure but also help to understand the formation mechanism of the solidification structure [12][13][14][15][16][17]. Domestic and foreign scholars have carried out a large number of numerical simulation studies on the solidification structure of vacuum consumable melting, including the realization of the vacuum arc remelting simulation process, the treatment of boundary conditions, the selection of a microstructure model, and so on [18][19][20][21][22][23][24].…”

Section: Introductionmentioning

confidence: 99%

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Simulation of Solidification Structure in the Vacuum Arc Remelting Process of Titanium Alloy TC4 Based on 3D CAFE Method

Jing,

Liu,

Geng

et al. 2024

Processes

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Vacuum arc remelting is the main production method of titanium alloy ingots at present. In order to obtain good quality ingots, it is of great significance to study the formation of the solidification structure of ingots via vacuum arc remelting. In order to select and optimize the nucleation parameters for the solidification microstructure simulation of an ingot, a 3D CAFE model for microstructure evolution during vacuum arc remelting was established, taking into account heat transfer, flow, and solute diffusion. The Gaussian distribution continuous nucleation model and extended KGT model were used to describe the grain nucleation and dendrite tip growth rates, respectively. The multi-point mass source and moving boundary method were used to simulate the ingot growth. The results show that there are three typical crystal regions in the solidification structure of vacuum arc remelting titanium alloy ingots, namely the surface fine crystal region, columnar crystal region, and central equiaxed crystal region. The proportion of the columnar crystal region in the solidification structure of an ingot increases gradually with the increase in the undercooling of the maximum bulk nucleation. With an increase in the maximum bulk nucleation density, the equiaxed grain zone gradually increases, and the grain size gradually decreases. The proportion of the columnar crystal region in the solidification structure of an ingot increases gradually with an increase in the undercooling of the maximum bulk nucleation. The maximum volume nucleation variance has no obvious effect on the change in the solidification structure. When the maximum volume nucleation undercooling is 5.5 K, the maximum volume nucleation standard deviation is 4 K, and the maximum volume nucleation density is 5 × 108. The solidification structure simulation results are in good agreement with the experimental results.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Simulation of Solidification Structure in the Vacuum Arc Remelting Process of Titanium Alloy TC4 Based on 3D CAFE Method

Jing,

Liu,

Geng

et al. 2024

Processes

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“…The number of bibliographic references devoted to the application of optimization algorithms to the adjustment of metal casting simulation models is quite reduced. Most of them [22][23][24][25] use the maximum A posteriori (MAP) algorithm, which is a variation of the least-square technique explained in reference [26]. Others perform the adjustment manually [27] or combining the manual adjustment with the MAP algorithm [28][29][30][31][32].…”

Section: Introductionmentioning

confidence: 99%

Performance of Optimization Algorithms in the Model Fitting of the Multi-Scale Numerical Simulation of Ductile Iron Solidification

Anglada

Meléndez

Obregón

et al. 2020

Metals

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The use of optimization algorithms to adjust the numerical models with experimental values has been applied in other fields, but the efforts done in metal casting sector are much more limited. The advances in this area may contribute to get metal casting adjusted models in less time improving the confidence in their predictions and contributing to reduce tests at laboratory scale. This work compares the performance of four algorithms (compass search, NEWUOA, genetic algorithm (GA) and particle swarm optimization (PSO)) in the adjustment of the metal casting simulation models. The case study used in the comparison is the multiscale simulation of the hypereutectic ductile iron (SGI) casting solidification. The model fitting criteria is the value of the tensile strength. Four different situations have been studied: model fitting based in 2, 3, 6 and 10 variables. Compass search and PSO have succeeded in reaching the error target in the four cases studied, while NEWUOA and GA have failed in some cases. In the case of the deterministic algorithms, compass search and NEWUOA, the use of a multiple random initial guess has been clearly beneficious.

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Microstructure, Mechanical and Electrochemical Properties of Ti 7Mo 8Nb Alloy Produced by Casting and Powder Metallurgy for Biomedical Applications

Saood,

El-kashif,

Ibrahim

et al. 2023

Inter Metalcast

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Determination of the thermophysical properties of titanium alloys from liquid bath profiles

Cited by 4 publications

References 6 publications

Simulation of Solidification Structure in the Vacuum Arc Remelting Process of Titanium Alloy TC4 Based on 3D CAFE Method

Simulation of Solidification Structure in the Vacuum Arc Remelting Process of Titanium Alloy TC4 Based on 3D CAFE Method

Performance of Optimization Algorithms in the Model Fitting of the Multi-Scale Numerical Simulation of Ductile Iron Solidification

Microstructure, Mechanical and Electrochemical Properties of Ti 7Mo 8Nb Alloy Produced by Casting and Powder Metallurgy for Biomedical Applications

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