Numerical Simulation of Temperature Field in TIG Arc Additive Manufacturing Using ANSYS

Literature Overview

The study by Liu Dongshuai, Lv Yanming, Zhou Wenjun, Yang Hua, and Wang Kang, published in Laser & Optoelectronics Progress (2019), presents a finite element analysis of the temperature field during TIG arc additive manufacturing (WAAM) using the commercial software ANSYS. The work originates from the Jiangsu Provincial Key Laboratory of Advanced Manufacturing Equipment for Food Industry at Jiangnan University. This research is significant because it bridges the gap between conventional welding thermal analysis and the more complex multi-layer, multi-pass thermal history inherent to additive manufacturing processes.

Core Technical Content

Thermal Modeling Approach

The researchers employed a 3D transient thermal finite element model to simulate the temperature distribution during TIG arc additive manufacturing. The key modeling assumptions and parameters typically include:

The Goldak double-ellipsoidal heat source model is particularly relevant for additive manufacturing because it accounts for the different thermal penetration in the direction of travel (rear) versus the forward direction. The rear keyhole region in high-power TIG processes can create significant thermal asymmetry that directly affects residual stress and dilution in subsequently deposited layers.

Temperature Field Evolution

A critical insight from this work is that the peak temperature in each new layer is significantly lower than in the first deposited layer due to the thermal mass of previously deposited material. This progressive cooling effect has direct implications for:

• Dilution control: Lower peak temperatures reduce the dilution ratio from the substrate into the overlay layer, which is advantageous when depositing nickel-based alloys (e.g., Inconel 625) onto carbon steel substrates.
• Microstructural evolution: The cooling rate increases with each successive layer, potentially leading to finer grain structures in upper layers compared to the first pass.
• Residual stress accumulation: The thermal gradient between the hot deposited bead and the cooler previously deposited layers generates compressive residual stresses in the weld centerline and tensile stresses near the edges.

Engineering Practice Implications

From a cladding and overlay perspective, the temperature field simulation provides valuable input for:

1. Process parameter optimization: Determining the optimal travel speed and arc power combination to maintain a target peak temperature window (typically 1200–1500 °C for stainless steel overlay).
2. Interpass temperature control: The simulation can predict when interpass cooling is necessary to avoid excessive thermal input that could cause grain coarsening or intergranular sensitization in austenitic stainless steel overlays.
3. WPS development: The thermal analysis supports the development of welding procedure specifications for additive manufacturing applications where the thermal history differs substantially from conventional single-pass cladding.

Key Technical Points and Reflections

The most valuable aspect of this research for practicing engineers is the demonstration that ANSYS-based thermal modeling can accurately predict the complex thermal history in multi-layer deposition. However, several limitations must be acknowledged:

• The model typically assumes a stationary or quasi-stationary heat source, which may not capture the dynamic effects of wire feeding and arc stability.
• Phase transformation effects (such as austenite-to-ferrite transformation in duplex or 300-series stainless steels) are often simplified or omitted.
• The convective and radiative heat loss coefficients are empirical and may introduce significant uncertainty in peak temperature predictions.

For practical application in bimetal pressure vessel fabrication, where weld overlay cladding is performed on large components, the temperature field data from ANSYS simulations can be used to:

• Design preheating strategies to minimize thermal cracking susceptibility in the base metal.
• Predict the heat-affected zone width and depth for post-weld inspection planning.
• Optimize the sequence of cladding passes to minimize distortion in thin-walled vessels.

Integration with Quality Control

The temperature field simulation results should be correlated with non-destructive testing outcomes. For instance, regions predicted to experience rapid cooling (high thermal gradient) are more susceptible to:

• Micro-cracking in the weld metal, detectable by MT or PT.
• Undercut defects at the bead boundaries, detectable by visual inspection or UT.
• Lack of fusion at the interface between passes, detectable by RT or PAUT.

The FMEA approach can be applied by cross-referencing the predicted thermal gradients with known defect mechanisms, creating a risk matrix that prioritizes inspection efforts in high-risk zones.

Study Insights

This work demonstrates that finite element thermal analysis is a powerful tool for understanding and optimizing the TIG arc additive manufacturing process. The temperature field data provides the foundation for predicting microstructure, residual stress, and mechanical properties in the deposited material. For engineers working in the cladding and bimetal product industry, the key takeaway is that thermal simulation should be an integral part of process development, particularly when transitioning from conventional overlay welding to additive manufacturing techniques. The ability to predict thermal history before physical trials reduces the number of expensive test coupons and accelerates the qualification process for critical applications such as pressure vessel repair and overlay.