1. Introduction

Submerged arc welding (SAW) is a very complex process that includes physical and chemical reactions. Moreover, it is very difficult to investigate the whole SAW process using numerical simulations [1–4]. However, the molten zone and heat-affected zone (HAZ) could be estimated using the finite element method (FEM) and considering just the conduction heat transfer.

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and eproduction in any medium, provided the original work is properly cited. © 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Wen et al. [1] modeled multi-wire SAW of thick-wall line pipe and calculated the thermal distributions under various welding conditions. Sharma et al. [2] predicted the temperature distributions and angular distortions in single-pass butt joints using three-dimensional simulations. Mahapatra et al. [3] suggested and validated a volumetric heat source model of twinwire SAW by using different electrode diameters and polarities. Kiran et al. [4] simulated a three-dimensional heat transfer of a V-groove tandem SAW process for various welding conditions using FEM. However, these studies with FEM only considered the heat conduction transfer in the welding process, which is insufficient to explain the curve weld bead such as fingertip penetration.

could be expected as a flux-wall guided (FWG) metal transfer using CFD simulation. They modeled FWG metal transfer with a moving cylinder and randomly directed droplet impingement. Therefore, it is possible to simulate how porosity can be trapped in the V-groove joint with a FWG metal transfer. For better productivity, the multi-electrode SAW process is proposed. Kiran et al. [17] developed physical and regression equations to predict the arc interaction and arc size as a function of the welding conditions for tandem submerged arc welding process. They modeled arc center displacements for tandem SAW under different welding conditions with a spring model. It was found that the arc center displacement of high current shifted less while that of low current shifted wider. Cho et al. [18] applied the arc interaction effect to simulate the molten pool behavior for tandem SAW process. They compared the various molten pool flow patterns where the combinations of the welding signals were different. Moreover, they found that the direction of droplet impingement was very important to expect the welding penetration. Kiran et al. [19] analyzed the temperature histories of tandem SAW CFD simulations within the same heat input. They compared cooling times from 800 to 500C and volume fractions for different welding conditions and they found that molten pool behavior played an important role to decide the volume fraction and micro hardness. Cho et al. [20] analyzed the flux consumption rate for tandem SAW process where the heat inputs were the same except the combination of welding signals (current and voltage). They found that the arc interaction, droplet impingement direction and metal transfer mode (spray & FWG) affected the overall flux consumption rates. Kiran et al. [21] modeled three wire SAW molten pool simulation which considered arc center displacement and droplet impingement with a physical approach and then analyzed molten pool flow patterns. This chapter briefly introduces the contents how to model and analyze the molten pool behaviors from numerical

Modeling and Analysis of Molten Pool Behavior for Submerged Arc Welding Process with Single and Multi-Wire…

http://dx.doi.org/10.5772/intechopen.76725

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simulations for single and multi-wire SAW process.

2.1. CFD modeling for single electrode

cated flux wall protects the flux cavity.

transfer, as shown in Figure 2.

2. Modeling of molten pool behavior for SAW process

Figure 1 shows a schematic diagram of SAW to allow the following characteristics to be understood [15]: (a) the flux and molten slag cover the overall weld bead and, (b) the fabri-

Although it is very difficult to observe the metal transfer of SAW, some previous studies succeeded in capturing the motion of a droplet in SAW. Franz [22] and Van Adrichem [23] observed the metal transfer through a ceramic tube using a X-ray cinematography and found that drops travel in free flight to the weld pool, or they may project sideways to collide with the molten flux wall. This metal transfer in SAW is the so-called flux-wall guided (FWG)

During the SAW process, a small portion of the flux is melted and consumed. Chandel [24] found that the flux consumption relies upon three sources: (a) conduction from the molten metal, (b) radiation from arc and (c) resistance heating of the slag. However, their individual

To overcome these disadvantages, computational fluid dynamics (CFD) is widely used to investigate molten pool flows and final weld beads because it makes it possible to approach the welding process more realistically [5]. Considering the importance of weld pool convection in the welding process, numerous researchers have attempted to analyze the heat transfer and fluid flow. Kim et al. [6] calculated the convective heat transfer and resultant temperature distributions for a filet gas metal arc welding (GMAW) process. Kim et al. [7] obtained the thermal data and analyzed the molten pool flows for various driving forces in stationary gas tungsten arc welding (GTAW). However, these studies assumed that the welding process was in a quasi-steady-state. Thus it was very difficult to approximate the droplet impingent and arc variation with alternating current (AC). Therefore, it is necessary to apply a transient analysis to the welding simulation because it can detect the free surface variation during the simulation time. One transient analysis method is the volume of fluid (VOF) method, which can track the molten pool surface; therefore, the variable models from arc plasma could be implemented in the simulations. Cho et al. [8] calculated the electromagnetic force (EMF) with mapping coordinates in V-groove GTAW and GMAW, and then applied it to the numerical simulation to obtain the dynamic molten pool behavior and final weld bead using the commercial software, Flow-3D. With the advantage of VOF transient simulation, Cho et al. [9] could calculate unstable molten pool flow patterns such as humping and overflow in V-groove positional GMAW. Cho et al. [10] obtained the heat flux distribution of the arc plasma in gas hollow tungsten arc welding (GHTAW) using the Abel inversion method and applied it to the VOF model to predict the molten zone area. Additionally, a more complex welding process can also be calculated by VOF. Cho and Na [11] conducted a laser welding simulation that included the multiple reflection and keyhole formation. Moreover, Cho and Na [12] conducted the threedimensional laser-GMA hybrid welding, which adopted the laser welding and GMAW. Han et al. [13] compared the driving forces for the weld pool dynamics in GTAW and laser welding. The VOF method could also be applied to describe the alloying element distributions and pore generation in the laser-GMA hybrid welding process [14].

The modeling and the molten pool flow analysis of SAW process are mostly conducted by Cho et al. [15–21]. Cho et al. [15] conducted molten pool analysis of SAW for single electrode for high-current (I > 500 A) condition with spray metal transfer droplet impingement. They considered electrode angle and wave form and modeled to analyze the molten pool behavior for single electrode direct current (DC) and alternative current (AC) welding signals. It was found that the penetration of weld bead is closely related with electrode angle and waveform of welding signal. Cho et al. [16] also found that droplet impingement of low-current (I < 500) could be expected as a flux-wall guided (FWG) metal transfer using CFD simulation. They modeled FWG metal transfer with a moving cylinder and randomly directed droplet impingement. Therefore, it is possible to simulate how porosity can be trapped in the V-groove joint with a FWG metal transfer. For better productivity, the multi-electrode SAW process is proposed. Kiran et al. [17] developed physical and regression equations to predict the arc interaction and arc size as a function of the welding conditions for tandem submerged arc welding process. They modeled arc center displacements for tandem SAW under different welding conditions with a spring model. It was found that the arc center displacement of high current shifted less while that of low current shifted wider. Cho et al. [18] applied the arc interaction effect to simulate the molten pool behavior for tandem SAW process. They compared the various molten pool flow patterns where the combinations of the welding signals were different. Moreover, they found that the direction of droplet impingement was very important to expect the welding penetration. Kiran et al. [19] analyzed the temperature histories of tandem SAW CFD simulations within the same heat input. They compared cooling times from 800 to 500C and volume fractions for different welding conditions and they found that molten pool behavior played an important role to decide the volume fraction and micro hardness. Cho et al. [20] analyzed the flux consumption rate for tandem SAW process where the heat inputs were the same except the combination of welding signals (current and voltage). They found that the arc interaction, droplet impingement direction and metal transfer mode (spray & FWG) affected the overall flux consumption rates. Kiran et al. [21] modeled three wire SAW molten pool simulation which considered arc center displacement and droplet impingement with a physical approach and then analyzed molten pool flow patterns. This chapter briefly introduces the contents how to model and analyze the molten pool behaviors from numerical simulations for single and multi-wire SAW process.
