CLADDING TECHNOLOGY SHANXI CO., LTDNumerical Simulation of K-TIG Welding Molten Pool Behavior
Literature Overview
This study, published in the Welding Journal (焊接学报, 2026) by He Hongyun, Wang Xinxin, and Chen Dawei from Chongqing University of Technology and the Chongqing Engineering Research Center for Special Welding Materials and Technology, presents a numerical simulation of the molten pool behavior during K-TIG welding. The research is supported by the National Natural Science Foundation of China (510705054), Chongqing Natural Science Foundation (CSTB2024NSCQ-MSX0127), and Chongqing Education Commission Project (KJQN202101135).
Core Technical Content
K-TIG welding operates in a transition regime between conventional TIG and keyhole arc welding, characterized by partial or full keyhole formation depending on the welding parameters. The molten pool in K-TIG welding exhibits complex behavior influenced by electromagnetic forces, surface tension, buoyancy forces, and the dynamic interaction between the arc plasma and the molten metal.
Numerical Model Components
| Model Component | Governing Equations | Key Assumptions |
|---|---|---|
| Heat Transfer | Energy equation with moving heat source (double-ellipsoidal or Gaussian) | Steady-state or transient depending on travel speed |
| Fluid Flow | Navier-Stokes equations with Boussinesq approximation | Incompressible, Newtonian fluid |
| Arc Force | Lorentz force and plasma shear stress boundary conditions | Axisymmetric arc, uniform current density |
| Phase Change | Enthalpy-porosity method or solidification model | Constant properties in solid and liquid phases |
| Surface Tension | Surface tension gradient (Marangoni effect) with temperature coefficient | Surface tension decreases with temperature for most metals |
The numerical simulation typically employs a finite element method (FEM) or finite volume method (FVM) solver, such as COMSOL Multiphysics, ANSYS Fluent, or Abaqus, to solve the coupled heat transfer and fluid flow equations in a three-dimensional domain.
Interpretation of Technical Points
The keyhole formation mechanism in K-TIG welding is governed by the balance between vaporization pressure, surface tension, and hydrostatic pressure. When the arc pressure exceeds the sum of surface tension and hydrostatic pressure at the weld pool center, a keyhole opens, allowing the arc to penetrate deeper into the workpiece. The molten pool shape, depth, and width are direct consequences of this complex interaction.
Typical Simulation Parameters for K-TIG on Carbon Steel
| Parameter | Value | Unit |
|---|---|---|
| Welding Current | 150–300 | A |
| Travel Speed | 100–500 | mm/min |
| Arc Power Density | 10⁸–10⁹ | W/m² |
| Heat Source Radius | 1–5 | mm |
| Heat Input | 5–25 | kJ/mm |
| Surface Tension Coefficient | 1.7–1.9 | N/m (at 1800 K) |
| Marangoni Coefficient | -3×10⁻⁵ to -5×10⁻⁵ | N/(m·K) |
The Marangoni convection, driven by surface tension gradients, plays a dominant role in determining the molten pool shape. A negative surface tension coefficient (surface tension decreases with increasing temperature) promotes a wide, shallow pool, while a positive coefficient leads to a deep, narrow pool. In K-TIG welding, the transition between these regimes is critical for achieving the desired penetration profile.
Process Analysis and Defect Prediction
Numerical simulation enables the prediction of welding defects before actual welding takes place. Common defects predicted by K-TIG simulations include:
- Undercut: Caused by excessive Marangoni convection at the weld pool edges, particularly in horizontal and overhead positions.
- Porosity: Predicted by analyzing gas entrapment mechanisms related to pool turbulence and keyhole collapse.
- Incomplete Fusion: Identified by analyzing the thermal cycle and solidification rate at the fusion boundary.
- Cracking: Related to the thermal stress distribution and solidification cracking susceptibility predicted from the cooling rate and gradient.
Defect Prediction Capability
| Defect Type | Primary Cause in Simulation | Key Parameter Sensitivity |
|---|---|---|
| Undercut | Edge Marangoni flow | Surface tension coefficient, travel speed |
| Porosity | Keyhole instability | Arc pressure, shielding gas composition |
| Incomplete Fusion | Low thermal input at edges | Current, arc length, joint fit-up |
| Hot Cracking | High cooling rate and gradient | Heat input, material composition |
Integration with Engineering Practice
For pressure vessel fabrication, numerical simulation of K-TIG welding provides several practical benefits:
- Procedure Development: Simulation allows rapid evaluation of welding parameter combinations without consuming expensive materials and time.
- Heat Affected Zone (HAZ) Prediction: The thermal cycle prediction enables assessment of microstructural changes and mechanical property variations in the HAZ.
- Residual Stress Analysis: Coupled thermo-mechanical simulation predicts residual stress distributions, which are critical for assessing distortion and stress corrosion cracking susceptibility.
- Weld Sequence Optimization: For complex vessel geometries, simulation guides the selection of welding sequences to minimize distortion and residual stresses.
In the context of ASME VIII Div.2, the predicted residual stresses can be used for stress linearization and the determination of primary membrane, primary bending, and secondary stress components for fitness-for-service assessment.
Key Questions and Reflections
The accuracy of numerical simulations depends heavily on the boundary conditions and material property assumptions. The arc force model, heat source distribution, and surface tension coefficient are particularly sensitive parameters that require calibration against experimental data. Engineers should treat simulation results as a qualitative guide rather than a precise quantitative prediction, especially when extrapolating beyond the validated parameter range.
Another consideration is the computational cost. Three-dimensional transient simulations of K-TIG welding can require significant computational resources, limiting their practical use in routine procedure development. Simplified models or surrogate models may be necessary for real-time or rapid evaluation applications.
Study Insights and Implications
This numerical simulation study provides a valuable tool for understanding the fundamental physics of K-TIG welding molten pool behavior. The insights gained from simulation complement experimental studies by revealing internal phenomena that are difficult to observe directly. For pressure vessel engineers, the ability to predict weld geometry, thermal cycles, and residual stresses through simulation supports more rational procedure development and qualification. The work also highlights the importance of accurately characterizing material properties, particularly surface tension and its temperature dependence, as these parameters critically influence the simulation predictions.