Zhuojin Pipe Fitting Co., LtdDynamic Temperature Field Simulation of Dissimilar Material Overlay Welding Using ANSYS Finite Element Analysis
Literature Overview
This paper by Dong Xiaoqiang and Duan Hongyan from Shenyang University of Technology addresses a significant gap in welding simulation literature: the numerical modeling of temperature fields during overlay welding on dissimilar materials. Published in the Journal of Shenyang University of Technology in 2008 (Volume 30, Issue 5, pages 551-554), the study develops a finite element model using ANSYS software to simulate the transient temperature distribution during overlay welding of dissimilar material combinations. The authors note that most existing numerical simulations focus on same-material welding, leaving a knowledge gap for the more complex and practically important case of dissimilar material overlay welding.
Theoretical Framework and Modeling Approach
The thermal analysis of overlay welding is governed by the transient heat conduction equation with a moving heat source:
The governing equation is expressed as:
rho Cp (dT/dt) = k * (d2T/dx2 + d2T/dy2 + d2T/dz2) + Q(x, y, z, t)
Where rho is density, Cp is specific heat capacity, k is thermal conductivity, T is temperature, and Q is the heat source function. For dissimilar material overlay welding, the challenge lies in the fact that material properties (rho, Cp, k) vary spatially depending on whether the point is in the base material or the overlay material.
The authors developed a three-dimensional finite element model with the following key features:
| Modeling Aspect | Implementation Detail |
|---|---|
| Geometry | 3D model of base plate with overlay weld bead |
| Mesh generation | Adaptive mesh refinement in the weld region using ANSYS mesh adaptation |
| Heat source model | Double-ellipsoidal heat source (Goldak model) for GTAW; cylindrical heat source for SAW |
| Material properties | Temperature-dependent properties for both base and overlay materials |
| Boundary conditions | Convective and radiative heat loss from exposed surfaces |
| Time stepping | Dynamic time stepping with adaptive time increments near the weld pool |
The use of ANSYS APDL (ANSYS Parametric Design Language) allowed the authors to automate the application of the moving heat source and the mesh adaptation process. This programmatic approach significantly reduced the computational time compared to manual step-by-step model updates.
Key Results and Temperature Field Characteristics
The simulation results reveal several important characteristics of the temperature field during dissimilar material overlay welding:
- Asymmetric temperature distribution: Due to the different thermal properties of the base and overlay materials, the temperature field is asymmetric about the weld centerline. The side with the higher thermal conductivity material shows a wider but lower peak temperature, while the lower conductivity side shows a narrower but higher peak temperature.
- Peak temperature: The maximum temperature in the weld pool reaches 2200 to 2500 degrees Celsius for GTAW processes, with the peak shifted toward the base material side due to its typically higher thermal conductivity.
- Heat-affected zone extent: The HAZ in the base material extends 3 to 5 millimeters from the fusion boundary, while the HAZ in the overlay material is typically 1 to 2 millimeters due to the higher melting point of many overlay alloys.
- Cooling rate variation: The cooling rate varies significantly across the weld cross-section. The highest cooling rates (100 to 200 degrees Celsius per second) occur near the fusion boundary in the base material, while the overlay metal cools at 30 to 80 degrees Celsius per second.
The comparison between simulation results and experimental thermocouple measurements shows good agreement, with temperature deviations within 50 degrees Celsius at most measurement points. This validates the numerical model for engineering applications.
Engineering Significance and Process Optimization
The ability to simulate temperature fields in dissimilar material overlay welding has direct implications for process optimization and defect prediction:
| Engineering Application | Simulation-Based Insight |
|---|---|
| Preheat temperature selection | Simulation identifies minimum preheat required to keep peak cooling rate below cracking threshold |
| Travel speed optimization | Predicts HAZ width and cooling rate as functions of travel speed for different material combinations |
| Defect prediction | Identifies regions susceptible to hot cracking based on temperature gradient and solidification rate |
| PWHT parameter selection | Predicts residual stress distribution to guide stress relief heat treatment parameters |
| Multi-pass strategy | Optimizes interpass temperature and pass sequence to minimize cumulative thermal damage |
For practical overlay welding applications, such as hardfacing of carbon steel surfaces with high-alloy deposits or corrosion-resistant cladding of stainless steel on carbon steel, the simulation provides quantitative guidance that reduces trial-and-error and improves first-pass quality.
Study Insights and Methodological Contributions
The primary contribution of this work is the demonstration that ANSYS-based finite element analysis can be effectively applied to dissimilar material overlay welding temperature field simulation. The use of adaptive mesh refinement and APDL programming represents a methodological advancement over earlier static-mesh approaches, which required excessive computational resources for accurate weld pool representation.
The validation of the model against experimental thermocouple data provides confidence in the predictive capability of the simulation for engineering applications. Engineers can use this approach to optimize welding parameters before actual welding trials, reducing material waste and accelerating process development.
However, the study focuses solely on thermal analysis. A complete understanding of dissimilar material overlay welding requires coupled thermal-metallurgical analysis that predicts phase transformation, residual stress, and distortion. Future work should extend the model to include:
- Thermal-metallurgical coupling to predict microstructural evolution in the weld and HAZ
- Residual stress analysis using elastic-plastic-creep constitutive models
- Distortion prediction for thin-walled components where overlay welding induces significant deformation
- Comparison of different heat source models (double-ellipsoidal vs. Gaussian vs. conical) for their accuracy in representing different welding processes
This literature provides a solid foundation for computational welding science in the context of dissimilar material overlay welding. The methodology developed here can be extended to more complex geometries and multi-physics simulations, providing engineers with powerful tools for process optimization and defect prevention.