Progress in Multiscale Simulation of Solidification Behavior in Vacuum Arc Remelted Ingot

doi:10.11900/0412.1961.2024.00265

Acta Metall Sin

2025, Vol. 61

Issue (1): 12-28 DOI: 10.11900/0412.1961.2024.00265

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Progress in Multiscale Simulation of Solidification Behavior in Vacuum Arc Remelted Ingot

LI Junjie¹(

), LI Panyue¹, HUANG Liqing¹^,², GUO Jie¹, WU Jingyang¹, FAN Kai², WANG Jincheng¹

1 State Key Laboratory of Solidification Processing, Northwestern Polytechnical University, Xi'an 710072, China
2 Hunan Xiangtou Goldsky Titanium Industry Technology Co. Ltd., Changde 415001, China

Cite this article:

LI Junjie, LI Panyue, HUANG Liqing, GUO Jie, WU Jingyang, FAN Kai, WANG Jincheng. Progress in Multiscale Simulation of Solidification Behavior in Vacuum Arc Remelted Ingot. Acta Metall Sin, 2025, 61(1): 12-28.

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Abstract

Vacuum arc remelting (VAR) is the principal remelting process for producing high-quality Ti-based alloy and Ni-based superalloy ingots with high density, fine chemical homogeneity, and minimal defects. Numerical modeling plays a crucial role in understanding the mechanisms and dynamics of various phenomena occurring at different scales during the VAR process. It also aids in optimizing operational parameters. In this paper, the development of multiscale simulations for VAR ingot solidification over the last two decades is introduced. The following four aspects are addressed: numerical models at various scales, macroscopic transport phenomena, microstructure and defect evolution, and the effects of process control parameters on the VAR ingot quality. Furthermore, the current limitations in this field and proposed future development directions are discussed.

Key words: vacuum arc remelting solidification numerical simulation macrosegregation microstructure

Received: 31 July 2024

ZTFLH:

TG244

Fund: Research Fund of State Key Laboratory of Solidification Processing in NWPU(2020-TS-06)

Corresponding Authors: LI Junjie, professor, Tel: (029)88492374, E-mail: lijunjie@nwpu.edu.cn

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	LI Junjie
	LI Panyue
	HUANG Liqing
	GUO Jie
	WU Jingyang
	FAN Kai
	WANG Jincheng

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https://www.ams.org.cn/EN/10.11900/0412.1961.2024.00265 OR https://www.ams.org.cn/EN/Y2025/V61/I1/12

Fig.1 Interacting physical phenomena and correlation during the solidification of vacuum arc remelting (VAR) molten pool (Dash line indicates the weak correlation)

Fig.2 Typical temperature distributions in the four stages of VAR process^[8] (Inset shows the locally enlarged view)

Fig.3 Typical isothermal lines in the molten pool with buoyancy driven flow (a) or with Lorentz force driven flow (b) (T—temperature, v—liquid velocity)

Fig.4 Flow patterns in VAR molten pool driven by buoyancy (a), self-induced Lorentz force (b), stirring Lorentz force (c) (u—poloidal velocity, u_θ —azimuthal velocity)

Fig.5 Variations of molten pool characters with remelting current determined by the competition between buoyancy and self-induced Lorentz force^[58]
(a) maximum velocity in molten pool (b) pool depth

Fig.6 Generation mechanism of macrosegregation in VAR ingot

Fig.7 Macrosegregation in VAR ingots under various flow patterns
(a, b) simulation results of Ti-5.1%V in the condition of buoyancy driven flow (a) and self-induced Lorentz driven flow (b)^[58] (c—actual composition,

c ¯

—norminal composition) (c, d) schematic representations of the simulated results for Ti-10-2-3 alloy in the condition of buoyancy driven flow (c) and self-induced Lorentz driven flow (d)^[57] (1: Fe enriched, 2: close to average alloy composition, 3: Fe depleted)

Fig.8 Comparisons of the macrosegregation in ingots with various electrode placements for three successive VAR^[11]
(a-i) concentration distributions of all triple remelting ingots for VAR1-A (a), VAR2-A (b), VAR2-D (c), VAR2-R (d), VAR3-A (e), VAR3-D-D (f), VAR3-D-R (g), VAR3-R-D (h), and VAR3-R-R (i) (C_V—mass fraction of vanadium element)
(j) global macrosegregation index (GMI) of each remelting ingot

Fig.9 Comparisons of cellular automation (CA) simulated and experimental results of solidification grain structure in titanium alloy ingot^[29] (a), Ni-based superalloy ingot^[53] (b), and bearing steel ingot^[32] (h—depth of molten pool, R—radius of melting pool. The A1 and A2 regions are the columnar crystal regions corresponding to the simulation results and the experimental results, respectively. The B1 and B2 regions are the central equiaxed crystal regions corresponding to the simulation results and the experimental results, respectively, and the remaining regions are the surface fine grain regions corresponding to the two results) (c)

Fig.10 Multi-scale simulations on the formation mechanism of β fleck in titanium alloys^[28]
(a) macroscale temperature field
(b) grain structure
(c) microsegregation within dendritic structure at nine positions of the ingot labeled in Figs.10a and b (G—temperature gradient,

T ˙ —

cooling rate, C_Cr—mass fraction of Cr)
(d) variation ranges of β transition temperature (T_β) at the nine positions

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