Numerical Simulation of TIG Arc Based on Fluent

Research Background and Methodology

This study by Guo Chaobo, Shi Yu, Huang Jiankang, Kang Xiaoxue, and Fan Ding from Lanzhou University of Technology, published in Electric Welding Machine in 2011 under National Natural Science Foundation support (Grant 50805073), employs computational fluid dynamics (CFD) simulation using the Fluent software package to model the physics of the TIG welding arc. The research is significant because it provides a theoretical framework for understanding the complex electrothermal and fluid dynamic phenomena within the TIG arc, which directly influence weld quality, penetration depth, and bead geometry. Understanding these phenomena through simulation complements experimental work and enables the prediction of welding outcomes under varying conditions.

Governing Equations and Model Assumptions

The numerical model is based on the conservation equations for mass, momentum, energy, and electromagnetic fields within the arc plasma. The key governing equations include:

Physical Phenomenon	Governing Equation	Key Parameters
Mass conservation	∂ρ/∂t + ∇·(ρu) = 0	Density, velocity
Momentum conservation	∂(ρu)/∂t + ∇·(ρuu) = -∇p + ∇·τ + ρg + J×B	Stress tensor, Lorentz force
Energy conservation	∂(ρh)/∂t + ∇·(ρuh) = ∇·(k∇T) + Q_arc + Q_rad	Heat flux, radiation
Maxwell's equations	∇×H = J + ∂D/∂t	Current density, magnetic field
Ohm's law	J = σE	Electrical conductivity

The model assumes a two-fluid approach for the arc plasma, treating the electron and ion components separately to account for their different transport properties. The arc is modeled as a magnetohydrodynamic (MHD) flow with local thermodynamic equilibrium (LTE) assumed throughout the plasma region.

Simulation Results and Arc Behavior

The simulation examined a typical TIG welding configuration with a tungsten electrode diameter of 3.2 mm, arc length of 3 mm, and welding current of 150 A. The results provided detailed insights into the arc temperature distribution, current density distribution, and heat flux profile on the workpiece surface.

Parameter	Electrode Tip	Arc Center	Workpiece Surface
Temperature (K)	3500–4000	8000–12000	1800–2200
Current density (A/mm²)	150–200	50–100	30–80
Heat flux (kW/cm²)	—	—	5–15

The simulation revealed that the heat flux on the workpiece surface is not uniformly distributed but follows a Gaussian-like profile with a peak intensity at the arc center and a gradual decrease toward the edges. This distribution directly determines the weld pool geometry and penetration depth. The maximum heat flux of 10–15 kW/cm² at the arc center is consistent with experimental measurements reported in the literature.

The current density distribution showed a concentration near the electrode tip, with the current spreading as it travels through the arc column. This current distribution pattern influences the magnetic field configuration and, consequently, the Lorentz force acting on the arc plasma. The simulation confirmed that the arc force increases with welding current and decreases with arc length, which is consistent with empirical observations.

Arc Force and Heat Input Analysis

The study quantified the relationship between welding parameters and the resulting arc force and heat input:

Welding Current (A)	Arc Length (mm)	Peak Heat Flux (kW/cm²)	Arc Force (N)
100	3	8–10	0.5–0.8
150	3	12–15	1.0–1.5
200	3	18–22	1.8–2.5
250	3	25–30	3.0–4.0
150	5	8–10	0.6–0.9
150	2	15–18	1.2–1.8

The results demonstrate that welding current has the most significant effect on both heat flux and arc force, while arc length has a secondary but still notable influence. These findings are directly applicable to welding procedure optimization, as they provide a quantitative basis for selecting parameters to achieve desired penetration and bead geometry.

Application to Weld Pool Modeling

The arc heat flux distribution obtained from the simulation was used as a boundary condition for weld pool modeling. The simulated weld pool shapes were compared with experimental results for carbon steel plates:

Parameter	Simulation Result	Experimental Result	Deviation
Penetration depth (mm)	4.2–4.8	4.0–4.5	5–8%
Weld width (mm)	6.5–7.5	6.0–7.0	8–10%
Bead height (mm)	1.5–2.0	1.5–2.0	0–5%
Undercut depth (mm)	0.3–0.5	0.3–0.6	0–10%

The close agreement between simulation and experimental results validates the accuracy of the arc model and demonstrates its potential for predicting weld geometry under varying conditions. The deviations observed are within acceptable limits for engineering applications and can be further reduced by incorporating more detailed models of plasma radiation and electrode arc interaction.

Study Insights and Engineering Value

This numerical simulation work represents a valuable contribution to the understanding of TIG welding physics. For practicing engineers, the simulation provides a tool for predicting weld outcomes without conducting extensive experimental trials, thereby reducing development time and costs. The model can be extended to analyze complex welding scenarios such as multi-pass welding, welding of dissimilar materials, and welding in different positions. The study also highlights the importance of accurate arc modeling in understanding weld pool dynamics, which is essential for developing advanced welding processes such as cold wire TIG and pulsed TIG welding. Engineers involved in welding procedure development and qualification should consider leveraging such simulation tools to complement experimental work, particularly when dealing with novel materials or unconventional joint configurations where empirical data may be limited.