Numerical Simulation of Macrosegregation in Water-Cooled Heavy Flat Ingot During Solidification

Meng, Qingyong; Wang, Fuming; Li, Changrong; Li, Menglong; Zhang, Jing; Cui, Guanjun

doi:10.1007/s11837-014-1003-2

Cited by 7 publications

(6 citation statements)

References 33 publications

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“…It has long been understood that an increase in ingot size favors macrosegregation formation. It has been demonstrated numerically that a special cooling procedure [22] or an increase in cooling rate [14] could alleviate macrosegregation. However, the effect of the cooling rate was studied with a fixed solid phase.…”

Section: Effect Of Mold Cooling Intensitymentioning

confidence: 99%

“…However, segregation in the upper part of the ingot was different, a fact that again can be attributed to the coarser mesh used for the simulation. Another numerical study with fixed solid phase carried out for a 3.3 ton steel ingot demonstrated that macrosegregation can be alleviated by increasing the cooling intensity of the ingot [14]. To date, the fixed solid phase approach remains attractive for numerical studies of solidification of large-scale industrial ingots, as it greatly reduces modeling complexity.…”

Section: Introductionmentioning

confidence: 99%

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Numerical Simulation of Macrosegregation Formation in a 2.45 ton Steel Ingot Using a Three-Phase Equiaxed Solidification Model

Wang

Delannoy

et al. 2021

Metals

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In the present work macrosegregation during solidification of a 2.45 ton steel ingot is simulated with a pure equiaxed model, which was tested previously via modeling of a benchmark experiment. While the columnar structure is not taken into account, a packed layer formed over inner walls of the mold at an early stage of solidification reproduces to some extent phenomena generally related to zones of columnar dendrites. Furthermore, it is demonstrated that interaction of free-floating equiaxed grains with ascending convective flow in the bulk liquid results in flow instabilities. This defines the irregular form of the negative segregation zone, the formation of which at the ingot bottom corresponds to experimental observation. Vertical channels reported in experimental measurements are reproduced in simulations. It is confirmed that intensification of ingot cooling may decrease segregation in the ingot.

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Section: Effect Of Mold Cooling Intensitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Numerical Simulation of Macrosegregation Formation in a 2.45 ton Steel Ingot Using a Three-Phase Equiaxed Solidification Model

Wang

Delannoy

et al. 2021

Metals

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“…Li et al 24 studied electroslag remelting of a die steel ingot using mathematical modeling. Meng et al 25 calculated the macrosegregation in a water-cooled flat ingot. Zhang et al 26 simulated the solidification of Fe-Ni-based ingot under a vacuum condition.…”

Section: 23mentioning

confidence: 99%

Optimization of Metallurgical Reactors Using Mathematical and Physical Modeling

Zhang

2014

JOM

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Because of the tremendous cost of pilot-plantscale metal industrial trials, previous attempts to develop new metallurgical processes have generally relied on scaling up small bench-scale experiments. Because of the lack of true understanding of the rate constants, mixing phenomena, and geometric effects that control the success of the real process, many previous pilot-plant operations have been unsuccessful. Water modeling and mathematical modeling instead have become the main approaches to optimize the metallurgical reactors. To achieve success, the model must accurately predict the phenomena of true interest, including the following: -Multiphase and turbulent fluid flow within each vessel in the process, incorporating the effects of gas stirring and including transient variations, which are the main source of variability in the product -Mixing phenomena in each vessel, including solidification, heating, and remelting of a metal layer around alloy particle additions, which directly controls the success of alloying, and is important to other reactions as well -Heat-transfer phenomena, including temperature drops between each vessel -Evolution of composition during each vessel, including the thermodynamics and kinetics of the reactions between the molten metal and interfaces with the top slag and bubble surfaces, coupled with fluid flow and mixing phenomena -Effects of the true three-dimensional features of the vessel shape (including location of inlet and outlet launder), gas injection location and flow rates, and other operating conditions on the above phenomenaExtensive past work has employed physical water models to successfully investigate fluid flow phenomena in metallurgical processes such as the steel refining and casting process 1-5 and the aluminum remelting process.6-10 The first water modeling for the fluid flow in a continuous casting mold study was carried out by Afanas'Eva et al.11 for a straight bore nozzle system. Physical water models can model single-phase fluid flow because of the simulation of kinematic viscosity of steel and water. However, it is hard to use water modeling to simulate the solidification of molten metals.With the tremendous increases in the power of computer hardware and modeling software, computational modeling offers a better design tool for creating new processes. Numerical simulation has the potential to quantify the phenomena taking place in a commercial-scale process before it is constructed. Mathematical models can yield added insight into flow phenomena. Computational models based on finite-volume or finite-element solution of the Navier-Stokes equations can include phenomena such as heat transfer, multiphase flow, and solidification in steel casting without the inaccuracies inherent in a water model. Extensive research focused on the design of the metallurgical reactors using mathematical modeling such as for molten steel system 2,12-22 and molten aluminum system. 6,23THE CURRENT JOM TOPICThe current JOM topic addresses the optimization of metallurgical reactors, suc...

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“…The equilibrium partition coefficient varies from 0 to 1 for most solutes in steel [2,5], thereby indicating that a solute may be rejected from the solid phase to the liquid phase, which enriches the liquid phase during solidification. The solutes may concentrate in the residual liquid pool due to convection, which results in center segregation at the end of the solidification process of casting steel blank [6][7][8][9]. When the partition coefficient is low, segregation is serious.…”

Section: Introductionmentioning

confidence: 99%

Phase Transition of Peritectic Steel Q345 and Its Effect on the Equilibrium Partition Coefficients of Solutes

Chen

Long

Cao

et al. 2017

Metals

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Abstract:The solidification path of peritectic steel Q345 was calculated and compared with in-situ observations to investigate the effect of phase transition on the equilibrium partition coefficient. Subsequently, a thermodynamic model for calculating the equilibrium partition coefficient was established and thermodynamic calculations were performed under different phase configurations. Results indicate that L (liquid phase) + δ, L + δ + γ, and L + δ phases coexist in sequence during the solidification of peritectic steel Q345. The phase constitution of the mushy zone evidently affects the evolution of the equilibrium partition coefficient of solutes. The temperature dependence of the equilibrium partition coefficient was quantified through the regression analyses of C, Si, Mn, P, and S solutes under different phase configurations. The average equilibrium partition coefficients of Mn, Si, P, C, and S are 0.696, 0.615, 0.273, 0.2, and 0.033, respectively, thereby indicating the strongest segregation tendency for S and the weakest for Mn.

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Numerical Simulation of Macrosegregation in Water-Cooled Heavy Flat Ingot During Solidification

Cited by 7 publications

References 33 publications

Numerical Simulation of Macrosegregation Formation in a 2.45 ton Steel Ingot Using a Three-Phase Equiaxed Solidification Model

Numerical Simulation of Macrosegregation Formation in a 2.45 ton Steel Ingot Using a Three-Phase Equiaxed Solidification Model

Optimization of Metallurgical Reactors Using Mathematical and Physical Modeling

Phase Transition of Peritectic Steel Q345 and Its Effect on the Equilibrium Partition Coefficients of Solutes

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