TIG Arc Combustion Simulation Based on Fluent

Literature Overview

The paper by Peng Xiaofei, Ma Guohong, Zhang Yuguang, Ping Qiwen, and Ye Jia, published in Heat Processing Technology in 2016 (Vol. 45, No. 1, pp. 176-179), presents a computational fluid dynamics (CFD) simulation of TIG welding arc combustion using FLUENT software. Funded by the National Natural Science Foundation (61165008) and the Ministry of Education Returnee Fund (13006199), this research was conducted at Nanchang University in collaboration with the Electron Lens Center at the University of Kentucky. The study establishes a two-dimensional axisymmetric model of the TIG arc based on the Navier-Stokes equations, energy conservation equations, and Maxwell's equations, with custom user-defined functions (UDFs) and user-defined scalars (UDS) implementing the physics.

Model Formulation

The governing equations for the TIG arc plasma simulation include:

The use of UDFs to dynamically connect argon gas physical properties to temperature, add momentum source terms, and define the current density distribution at the tungsten electrode boundary represents a sophisticated implementation approach. This methodology allows the simulation to capture the strongly coupled, nonlinear behavior of the arc plasma without requiring modifications to the FLUENT source code.

Key Simulation Results

The simulation reveals several important characteristics of the TIG arc:

1. Bell-shaped temperature field: The arc temperature distribution follows the expected bell-shaped profile, with maximum temperature at the arc center and decreasing toward the boundaries.
2. Axial pressure maximum: The arc pressure is highest along the central axis, which drives the plasma flow outward and downward toward the workpiece.
3. Temperature-dependent argon properties: The physical properties of argon (conductivity, viscosity, thermal diffusivity) vary significantly with temperature, creating strong nonlinear coupling between the flow field and thermal field.
4. Axial current density decrease: The axial component of current density decreases along the arc length, indicating current spreading as the arc widens.
5. Gaussian radial current density: The radial current density distribution follows a Gaussian profile, consistent with experimental measurements.

Comparison with Dual-Temperature Model

When compared with the dual-temperature model presented in Topic 1 of this literature set, the single-temperature approach used in this Fluent-based simulation represents a simplification. The single-temperature model assumes local thermodynamic equilibrium (LTE) throughout the arc, which is valid in the arc core but breaks down at the boundaries. The results of this simulation should be interpreted with awareness of this limitation, particularly when predicting heat transfer at the anode surface.

UDF Implementation Details

The implementation of physics through UDFs is a critical aspect of this work. The key UDFs include:

• Property UDF: Defines argon gas properties as functions of local temperature, enabling the simulation to capture the strong temperature dependence of plasma transport coefficients.
• Momentum source UDF: Adds the Lorentz force (J × B) and other body forces to the momentum equation, coupling the electromagnetic field to the fluid dynamics.
• Boundary condition UDF: Specifies the current density distribution at the tungsten electrode surface, which determines the arc initiation and current density profile.

The UDS approach for implementing the current continuity equation is an elegant solution to the challenge of solving the electromagnetic equations within the FLUENT framework. By treating the electric potential as a scalar field, the current density can be calculated from the gradient of this potential, and the continuity equation ensures charge conservation.

Engineering Applications and Limitations

For pipe welding engineering applications, the CFD simulation of the TIG arc provides valuable insights into:

• Arc force prediction: Understanding the electromagnetic and plasma dynamic forces acting on the weld pool, which affects bead geometry and penetration
• Heat flux distribution: Determining the spatial distribution of heat input at the workpiece surface, which is essential for predicting weld pool geometry and HAZ extent
• Arc stability analysis: Identifying conditions that lead to arc oscillation or instability, which can cause weld defects

However, several limitations constrain the direct application of these simulation results to production welding:

1. Axisymmetric assumption: Real pipe welds are not axisymmetric due to joint geometry, gravity effects, and shielding gas flow patterns.
2. Static analysis: The model captures a steady-state arc, while production welding involves a moving arc with dynamic pool behavior.
3. No workpiece interaction: The model does not include the workpiece surface physics, which is essential for predicting weld penetration and bead geometry.
4. No electrode physics: The tungsten electrode is treated as a boundary condition rather than a dynamic component, which limits predictions of electrode wear and arc drift.

Methodological Reflections

The Fluent-based approach to arc simulation represents a pragmatic engineering solution that leverages commercial CFD software while implementing custom physics through UDFs and UDS. This approach has several advantages:

• Reduced development time compared to writing a dedicated solver
• Access to FLUENT's advanced numerical algorithms and meshing capabilities
• Easier validation against experimental data through post-processing
• Greater accessibility to engineers without specialized computational physics training

The disadvantage is that the implementation is constrained by FLUENT's architecture, and certain physics (such as the full MHD equations with Hall effect) may be difficult or impossible to implement accurately.

Integration with Process Optimization

For practical welding process optimization, the simulation results can be used to:

• Generate lookup tables of heat flux distributions for different current levels, electrode diameters, and arc lengths
• Predict the effect of parameter changes on weld geometry without extensive experimental testing
• Develop surrogate models for real-time process control in automated welding systems
• Optimize shielding gas flow patterns to improve arc stability and protect the weld pool

The simulation-based approach is particularly valuable for pipe welding applications where experimental testing is expensive and time-consuming, such as nuclear-grade stainless steel piping or aerospace titanium components.

Summary

This study demonstrates the effective use of commercial CFD software with custom user-defined functions to simulate TIG welding arc combustion. The results confirm the expected bell-shaped temperature profile, axial pressure maximum, and Gaussian radial current density distribution, validating the model against established physical understanding. For engineering practice, this simulation approach provides a powerful tool for understanding arc behavior and optimizing welding parameters, particularly when combined with experimental validation. The axisymmetric steady-state limitation and the single-temperature assumption should be acknowledged when applying results to complex pipe welding scenarios, but the overall methodology represents a practical and accessible approach to arc physics simulation that can significantly enhance process development and quality improvement in pipe and fitting welding operations.