CLADDING TECHNOLOGY SHANXI CO., LTDAnalytical Model of Quasi-Steady Temperature Field in Hot-Wire TIG Welding
Literature Overview
This 2012 publication from Shanghai Jiao Tong University, authored by Zhao Fuhai, Hua Xueming, Ye Xin, and Wu Yixiong, presents an analytical model for the quasi-steady temperature field in hot-wire TIG welding. Published in the Journal of Shanghai Jiao Tong University, this work addresses a fundamental aspect of welding thermal analysis that has direct implications for process optimization, distortion control, and residual stress prediction. The research is conducted within the Welding Engineering Research Institute, the Shanghai Key Laboratory of Laser Manufacturing and Materials Modification, and the State Key Laboratory of Metal Matrix Composites at Shanghai Jiao Tong University, reflecting the institution's strength in welding science and engineering.
Process Background and Motivation
Hot-wire TIG welding is a variant of conventional TIG welding in which the filler wire is preheated before entering the arc zone. The preheating can be achieved by electrical resistance heating, inductive heating, or gas flame heating. The primary benefits of hot-wire TIG welding include increased deposition rate, reduced arc power requirement, improved weld bead geometry, and reduced heat input to the base material. These advantages make hot-wire TIG welding particularly attractive for cladding applications, where high deposition rates and controlled dilution are essential.
The quasi-steady state assumption is valid when the welding process operates at a constant travel speed for a sufficiently long duration that the thermal field has reached a steady-state condition in the coordinate system moving with the arc. Under this assumption, the temperature distribution can be described by an analytical solution that depends on the welding parameters and material properties.
Analytical Model Development
Governing Equations
The quasi-steady temperature field in hot-wire TIG welding is governed by the heat conduction equation with a moving heat source:
The heat source is modeled as a Gaussian distribution with two components: the arc heat input and the hot wire heat input. The arc heat source is characterized by the arc power, which is a function of the welding current and arc voltage. The hot wire heat source is characterized by the thermal energy carried by the preheated wire, which depends on the wire temperature, wire feed rate, and wire material properties.
Key Model Parameters
| Parameter | Symbol | Typical Value | Description |
|---|---|---|---|
| Arc power | Q_arc | 2-10 kW | Function of current and voltage |
| Wire temperature | T_w | 200-800°C | Preheating temperature |
| Wire feed rate | v_f | 200-600 mm/min | Deposition rate control |
| Travel speed | v_t | 5-30 mm/min | Welding speed |
| Thermal conductivity | k | 20-50 W/m·K | Material property |
| Specific heat | c | 450-700 J/kg·K | Material property |
| Density | rho | 7800-8100 kg/m³ | Material property |
| Heat source radius | r_0 | 1-5 mm | Gaussian distribution parameter |
Temperature Distribution Characteristics
The analytical model predicts several important features of the temperature field:
- The maximum temperature occurs at the intersection of the arc axis and the wire feed point, with values typically in the range of 2000 to 3000 K depending on the process parameters.
- The temperature distribution is asymmetric, with a higher temperature on the leading edge of the weld pool due to the direction of travel.
- The hot wire contributes significantly to the overall heat input, reducing the arc power requirement by 20 to 40 percent compared to cold-wire TIG welding for the same deposition rate.
- The thermal gradient is steeper on the trailing edge of the weld pool, which affects solidification morphology and defect formation.
Process Optimization and Engineering Applications
Heat Input Control
The quasi-steady temperature field model provides a quantitative basis for optimizing the heat input in hot-wire TIG welding. The total heat input is the sum of the arc heat input and the wire heat input, and the model allows the engineer to determine the optimal combination of arc power and wire preheating temperature for a given deposition rate and weld geometry.
For cladding applications, where the dilution ratio must be controlled to maintain the chemical composition of the overlay layer, the model is particularly valuable. By adjusting the arc power and wire temperature independently, the engineer can achieve the desired dilution ratio while maintaining adequate wetting and bond strength.
Distortion and Residual Stress Prediction
The temperature field model serves as the basis for predicting welding distortion and residual stress. The thermal strain field, derived from the temperature distribution, can be used in finite element analysis to predict the deformation pattern and residual stress distribution in the welded component. This information is critical for designing fixtures, planning welding sequences, and implementing post-weld stress relief procedures.
| Application | Model Output | Engineering Use |
|---|---|---|
| Cladding | Dilution ratio prediction | Filler selection, process qualification |
| Pipe welding | Distortion prediction | Fixture design, sequence planning |
| Thick plate welding | Residual stress prediction | Stress relief planning, fatigue assessment |
| Additive manufacturing | Layer temperature prediction | Process optimization, defect prevention |
Comparison with Experimental Data
The study validates the analytical model against experimental temperature measurements obtained using thermocouples and infrared thermography. The comparison shows good agreement between predicted and measured temperatures, with deviations typically within 10 to 15 percent. The larger deviations occur near the arc zone, where the assumptions of the Gaussian heat source model are less accurate, and in regions where phase transformations affect the thermal properties.
Sources of Model Error
| Source | Magnitude | Mitigation |
|---|---|---|
| Heat source geometry | 10-15% | Use double-ellipsoidal model |
| Phase transformation | 5-10% | Incorporate latent heat effects |
| Convection losses | 5-8% | Add surface cooling term |
| Material property variation | 3-5% | Use temperature-dependent properties |
| Wire heat input uncertainty | 5-10% | Measure wire temperature directly |
Study Insights and Practical Implications
The analytical model presented in this study provides a valuable tool for process engineers seeking to optimize hot-wire TIG welding parameters. The key insight is that the quasi-steady assumption, while simplifying the mathematical analysis, captures the essential physics of the welding thermal field and provides sufficiently accurate predictions for practical engineering purposes.
For cladding and weld overlay applications, where hot-wire TIG welding is increasingly used to achieve high deposition rates with controlled dilution, the model offers a quantitative basis for process development. The engineer can use the model to predict the effect of varying arc power, wire temperature, and travel speed on the resulting temperature field, dilution ratio, and weld geometry.
The model also has implications for residual stress management in pressure vessel fabrication. By predicting the temperature field and thermal strain, the engineer can anticipate the residual stress distribution and design welding sequences and post-weld treatments to minimize adverse effects on component performance.
In conclusion, this analytical model represents a significant contribution to the understanding of hot-wire TIG welding thermal behavior, providing engineers with a practical tool for process optimization and quality control in cladding and general welding applications.