CLADDING TECHNOLOGY SHANXI CO., LTDANSYS-Based Numerical Simulation of Temperature Field in TIG Arc Additive Manufacturing
Literature Overview
Published in 2019 in the journal Laser & Optoelectronics Progress, this paper by Liu Dong-shuai, Lv Yan-ming, Zhou Wen-jun, Yang Hua, and Wang Kang from Jiangnan University presents a numerical simulation study of the temperature field during TIG arc additive manufacturing (AM) using ANSYS software. The research is conducted within the framework of the Jiangsu Provincial Key Laboratory of Advanced Food Manufacturing Equipment Technology, suggesting applications in food processing equipment fabrication where corrosion-resistant and high-performance components are required.
Core Technical Content
TIG arc additive manufacturing represents a hybrid approach that combines the precision of arc welding with the layer-by-layer deposition principles of additive manufacturing. Unlike conventional welding, where the objective is to join existing components, TIG AM builds three-dimensional structures by sequentially depositing molten material. The temperature field simulation is critical for understanding the process because:
- Thermal gradients drive solidification microstructure and defect formation
- Residual stresses develop due to non-uniform thermal expansion and contraction
- Layer-to-layer bonding quality depends on the thermal history of each deposited layer
- Distortion and warping are governed by the cumulative thermal effects of multiple layers
ANSYS Simulation Methodology
The paper employs ANSYS, a widely used finite element analysis software, to simulate the temperature field during TIG AM. The simulation methodology typically involves:
- Geometry modeling: Creating a three-dimensional model of the deposition process, including the substrate, deposited layers, and the moving heat source.
- Material property definition: Inputting temperature-dependent thermal properties (conductivity, specific heat, density) and mechanical properties (Young's modulus, thermal expansion coefficient, yield strength).
- Heat source modeling: Implementing a moving heat source that follows the deposition path, with parameters calibrated to match experimental observations.
- Boundary conditions: Defining heat loss mechanisms including convection, radiation, and conduction to the substrate and surrounding environment.
- Meshing and time-stepping: Creating an appropriate mesh density and selecting time steps that capture the rapid thermal transients during deposition.
Temperature Field Characteristics in TIG AM
The simulation results reveal several important characteristics of the temperature field during TIG AM:
| Characteristic | Description | Engineering Significance |
|---|---|---|
| Peak temperature | Typically 1800–2200 °C at the arc center | Determines melting and solidification behavior |
| Thermal gradient | Steep gradients near the deposition zone, gradual decay away from the arc | Influences grain orientation and residual stress |
| Thermal cycle | Rapid heating followed by slower cooling in subsequent layers | Affects microstructure evolution and phase transformations |
| Layer interaction | Each new layer reheats the previous layer, modifying its thermal history | Critical for interlayer bonding and defect prevention |
| Substrate temperature | Gradually increases with each deposited layer | Affects distortion and may require active cooling |
Process Optimization and Defect Prevention
The temperature field simulation enables proactive identification and prevention of common defects in TIG AM:
- Lack of fusion: If the previous layer cools below the solidus temperature before the next layer is deposited, incomplete fusion can occur. The simulation predicts the temperature at the time of the next layer deposition, allowing for optimization of interpass time.
- Cracking: Thermal stresses developed during solidification and cooling can exceed the yield strength of the weld metal, leading to hot cracking or cold cracking. The simulation provides stress distributions that identify critical regions.
- Distortion and warping: Cumulative thermal effects cause the deposited structure to distort from the intended geometry. The simulation predicts the magnitude and direction of distortion, enabling compensation strategies.
- Porosity and gas entrapment: Rapid solidification can trap gases, and thermal gradients can drive gas solubility changes. While not directly simulated in the temperature field analysis, the thermal conditions influence these phenomena.
Process Parameter Optimization
| Parameter | Effect on Temperature Field | Optimization Strategy |
|---|---|---|
| Welding current | Increases peak temperature and heat input | Balance penetration depth with distortion control |
| Travel speed | Affects heat input per unit length | Optimize for complete fusion without excessive heat |
| Wire feed rate | Controls deposition rate and dilution | Match with travel speed for consistent layer thickness |
| Layer thickness | Affects thermal gradient and cooling rate | Thinner layers cool faster but require more passes |
| Interpass temperature | Controls reheating of previous layers | Maintain above solidus for fusion, below for grain control |
Engineering Practice Integration
TIG AM is particularly attractive for manufacturing components where:
- Complex geometries are required that are difficult to machine from solid stock
- Material efficiency is important (additive processes use only the required material)
- Customized or low-volume production is needed
- Corrosion-resistant or high-performance alloys are required
The ANSYS simulation approach provides a virtual prototyping capability that reduces the need for physical trials, which is especially valuable when working with expensive materials such as nickel-based alloys or titanium alloys.
Key Questions and Reflections
The literature raises several important questions for further investigation:
- How accurately does the ANSYS simulation capture the complex thermal-mechanical coupling during multi-layer deposition?
- What are the limitations of the continuum-based finite element approach in predicting microstructure-dependent properties?
- How can the simulation be integrated with process monitoring systems for real-time control?
- What is the optimal balance between simulation accuracy and computational efficiency?
The study also highlights the importance of material property data quality. Temperature-dependent properties for welding consumables and deposited metals must be accurately characterized to ensure reliable simulation results. This is particularly challenging for advanced alloys where property data may be limited or uncertain at high temperatures.
Study Insights and Implications
This literature demonstrates the potential of numerical simulation for TIG AM process development. The ANSYS-based temperature field simulation provides quantitative insights into the thermal behavior during deposition, enabling:
- Predictive process design that minimizes defects and distortion
- Parameter optimization that balances competing requirements
- Virtual qualification that reduces physical trials and development time
For engineers working in additive manufacturing, the key takeaway is that simulation should be an integral part of the process development workflow, complementing experimental trials and physical testing. The simulation results should be validated against experimental measurements to ensure accuracy, and the model should be updated as new material data and process insights become available. The TIG AM process, combined with numerical simulation, offers a powerful approach for manufacturing high-performance components with complex geometries and tailored microstructures.