Three-Dimensional Dynamic Simulation of Temperature Field in Submerged Arc Plate Overlay Welding

Research Overview and Technical Motivation

The 2009 study by Shi Baoshan, He Kuanfang, and He Hezhi from Beijing Institute of Technology Zhuhai College and South China University of Technology presents a three-dimensional dynamic finite element simulation of the temperature field during submerged arc welding (SAW) plate overlay operations. Funded by the National Natural Science Foundation of China (grants 10472034 and 10590351), this research represents a significant advancement in the computational modeling of weld overlay processes, providing insights into thermal phenomena that are difficult to capture through experimental measurement alone.

The motivation for this work stems from the need to predict and control the thermal history of overlay deposits, which directly influences the microstructure, mechanical properties, residual stress distribution, and distortion of the final product. Submerged arc welding is one of the most widely used processes for overlay applications due to its high deposition rate, deep penetration, and excellent shielding provided by the flux. Understanding the temperature field evolution is essential for optimizing process parameters and ensuring quality.

Simulation Methodology and Model Development

The three-dimensional dynamic simulation approach employed in this study involves the development of a finite element model that accounts for the sequential deposition of overlay layers, the movement of the heat source, and the changing geometry of the weld pool as each pass is completed. The model must incorporate:

The double-ellipsoidal heat source model, commonly used in welding simulations, represents the heat input as two ellipsoidal volumes, one for the front region of the arc (where energy penetrates deeper) and one for the rear region (where energy spreads more laterally). The parameters of this model are calibrated to match the welding current, voltage, and travel speed used in the actual process.

The dynamic nature of the simulation means that the temperature field evolves continuously as the arc moves along the weld path. At each time step, the model calculates the temperature distribution throughout the workpiece and the previously deposited layers, accounting for heat conduction, convection at the surface, and radiation losses. The results provide a complete thermal history for every point in the model, which can be used to predict microstructural transformations using coupled thermal-metallurgical models.

Key Results and Thermal Analysis

The simulation results reveal several important characteristics of the temperature field during submerged arc plate overlay welding. The peak temperature in the weld pool typically reaches 1800–2200°C, depending on the heat input and material properties. The cooling rate at the solidification front, which determines the primary microstructure of the overlay deposit, can be estimated from the temperature gradient and the velocity of the solidification front.

The temperature distribution shows significant asymmetry between the leading and trailing edges of the weld pool, with steeper temperature gradients at the trailing edge due to the directional movement of the heat source. This asymmetry influences the solidification pattern and can lead to directional solidification effects in the overlay microstructure.

For multi-pass overlay, the thermal history of previously deposited layers is significantly affected by subsequent passes. The reheat temperature of earlier layers can approach 600–800°C, which may cause grain growth, phase transformations, or stress relief in the previously solidified material. This interpass heating effect is critical for understanding the final properties of multi-layer overlay deposits.

The cooling rate distribution across the overlay thickness is particularly important. The region near the substrate experiences faster cooling due to heat extraction by the base metal, while the top surface of the overlay cools more slowly. This gradient in cooling rate leads to variations in grain size, phase composition, and hardness across the overlay thickness, with harder, finer-grained microstructure near the bond line and coarser, potentially more austenitic structure near the surface.

Engineering Applications and Process Optimization

The temperature field simulation results have direct applications in process optimization and quality prediction. By understanding how welding parameters influence the thermal history, the engineer can select parameters that produce the desired cooling rates and microstructural characteristics. For example:

• Increasing welding current increases heat input, reduces cooling rate, and promotes coarser microstructure with potentially higher retained austenite content.
• Increasing travel speed reduces heat input, increases cooling rate, and produces finer microstructure with potentially higher hardness but also higher residual stress.
• Adjusting the voltage modifies the arc characteristics and penetration profile, affecting the dilution ratio and the thermal gradient at the overlay-substrate interface.

The simulation also provides insights into distortion prediction. The non-uniform temperature distribution during welding creates differential thermal expansion and contraction, leading to angular and longitudinal distortion of the plate. By predicting the distortion pattern, the engineer can design appropriate fixtures, select welding sequences, or plan post-weld straightening operations to minimize dimensional deviations.

The residual stress prediction capability of the thermal simulation, when coupled with elastic-plastic analysis, provides additional value for assessing the long-term performance of overlay components. High tensile residual stresses at the overlay-substrate interface can promote crack initiation under cyclic loading, while compressive residual stresses can be beneficial for fatigue resistance.

Methodological Reflections and Limitations

While the three-dimensional dynamic simulation provides powerful insights into the thermal behavior of submerged arc overlay welding, several limitations must be acknowledged. The model assumes perfect thermal contact between layers, which may not represent the actual condition if lack of fusion or porosity is present. The material properties used in the model are typically derived from homogeneous material data and may not accurately represent the heterogeneous, potentially diluted composition of the actual overlay deposit.

Furthermore, the simulation typically does not account for the effects of flux composition on heat transfer, the electromagnetic forces acting on the weld pool, or the metallurgical transformations that occur during cooling. These phenomena can significantly influence the final properties of the overlay and would require additional coupled models for comprehensive prediction.

Despite these limitations, the thermal simulation remains an invaluable tool for process development and optimization. The results provide a foundation for understanding the fundamental thermal phenomena that govern overlay quality, and the methodology can be extended to include coupled thermal-metallurgical-mechanical models for more comprehensive predictions.

This study represents an important contribution to the computational modeling of weld overlay processes, demonstrating the value of three-dimensional dynamic simulation in understanding complex thermal phenomena that are difficult to observe experimentally. The approach established here can be adapted to other overlay processes and materials, providing a framework for computational process optimization in surface engineering applications.