Numerical Simulation of Temperature Field During Plunger Surfacing Process Using ANSYS

Literature Overview

This paper by Zhang Guozheng from Shaanxi National Defense Industry Vocational and Technical College, published in Foundry Technology (2017, Vol. 38, No. 9, pp. 2265-2267), presents a three-dimensional finite element numerical simulation of the welding temperature field during plasma arc surfacing of a composite metal layer on a 45 steel plunger surface. The study uses ANSYS software to analyze the temperature distribution at different welding speeds and at various time steps, providing insights for welding process optimization and fatigue-related structural analysis.

Significance of Temperature Field Simulation in Surfacing

The temperature field during welding is the primary driving force for all subsequent metallurgical transformations, including phase changes, grain growth, residual stress development, and distortion. Understanding the temperature field distribution is therefore fundamental to predicting and controlling the microstructure and mechanical properties of surfacing repairs.

For plunger components, which are subjected to cyclic pressure and sliding contact loads in hydraulic systems, the quality of the surfacing repair is critical. The plunger surface must maintain dimensional accuracy, surface finish, and mechanical integrity after repair. Any distortion or residual stress from the surfacing process can compromise the plunger's sealing performance and fatigue life.

Numerical Simulation Methodology

Model Setup

The simulation was performed using ANSYS with the following approach:

Parameter	Description
Software	ANSYS (FEA package)
Element type	3D solid elements (e.g., SOLID70)
Boundary conditions	Fixed supports at plunger base, free surfaces elsewhere
Heat source model	Double-ellipsoidal or Gaussian moving heat source
Material	45 steel (base), composite alloy (surfacing layer)
Temperature-dependent properties	Thermal conductivity, specific heat, density as functions of temperature
Welding speeds	Multiple values (e.g., 50, 80, 100, 120 mm/min)

Thermal Boundary Conditions

The model incorporates:

Convective heat transfer from the weld surface to the surrounding air (heat transfer coefficient typically 10-25 W/m²·K)
Radiative heat transfer from the weld surface (Stefan-Boltzmann radiation with emissivity 0.8-0.9 for oxidized steel)
Contact heat transfer at the plunger base (if applicable)
Moving heat source representing the welding arc, which translates along the surfacing path at the specified welding speed

Temperature Field Results

The simulation reveals several important characteristics of the temperature field during plunger surfacing:

Asymmetric temperature distribution: The temperature field is asymmetric along the welding direction, with higher temperatures ahead of the arc (due to preheating by the moving heat source) and lower temperatures behind the arc (due to heat dissipation).
Effect of welding speed: At lower welding speeds, the heat input per unit length is higher, resulting in wider high-temperature zones and slower cooling rates. At higher welding speeds, the heat input per unit length is lower, resulting in narrower high-temperature zones and faster cooling rates.
Temperature gradients: The maximum temperature gradients occur at the fusion boundary and in the HAZ, where the temperature changes most rapidly. These high gradients are the primary cause of thermal stresses and residual stresses in the weld.
Cyclic thermal loading: For multi-pass surfacing, each subsequent pass imposes a thermal cycle on the previously deposited material, causing re-heating and re-cooling that can modify the microstructure and residual stress state.

Process Optimization Insights

The numerical simulation results provide several practical insights for surfacing process optimization:

Welding Speed Selection

Welding Speed	Heat Input per Unit Length	HAZ Width	Cooling Rate	Expected Microstructure
Low (50 mm/min)	High	Wide	Slow	Coarse grains, possible grain growth
Medium (80-100 mm/min)	Moderate	Moderate	Moderate	Balanced microstructure
High (120+ mm/min)	Low	Narrow	Fast	Fine grains, possible martensite

For plunger surfacing, a medium welding speed is typically optimal, providing sufficient heat input for good wetting and deposition while maintaining adequate cooling rates to produce fine-grained microstructures.

Residual Stress Prediction

The temperature field simulation can be extended to predict residual stresses by coupling the thermal analysis with a mechanical analysis. The residual stress distribution is primarily determined by:

Thermal contraction during cooling, which is constrained by the surrounding cooler material
Phase transformation strains (austenite to martensite in high-carbon surfacing alloys)
Plastic deformation during welding

For plunger applications, the residual stress state is particularly important because it influences the fatigue life of the surfacing repair. Tensile residual stresses at the surface reduce fatigue life, while compressive residual stresses improve it. The numerical simulation can guide the selection of welding parameters and post-weld treatment to achieve a favorable residual stress state.

Distortion Prediction

The temperature field distribution also determines the thermal distortion of the plunger during surfacing. Non-uniform heating causes differential expansion, which can lead to warping, bowing, or ovality of the plunger surface. The simulation can predict the magnitude and direction of distortion, allowing engineers to design fixture arrangements or apply counter-distortion strategies to maintain dimensional accuracy.

Integration with Engineering Practice

The numerical simulation approach has several practical applications in plunger surfacing repair:

Process parameter optimization: By running simulations with different welding speeds, current levels, and voltage settings, engineers can identify the optimal parameter combination that minimizes residual stress and distortion while achieving the required deposition quality.
Multi-pass planning: For thick surfacing layers requiring multiple passes, the simulation can predict the thermal history of each pass and the cumulative effect on the microstructure and residual stress state. This enables the design of optimal pass sequences and interpass temperatures.
Fatigue life prediction: The residual stress distribution predicted by the simulation can be used as input for fatigue life analysis, enabling engineers to predict the service life of the surfacing repair under cyclic loading conditions.
Quality control baseline: The simulation results provide a theoretical baseline against which experimental measurements (e.g., thermocouple readings, strain gauge measurements) can be compared, helping to identify process deviations and improve process control.

Study Insights and Limitations

The numerical simulation approach provides a powerful tool for understanding and optimizing the plunger surfacing process. However, several limitations should be acknowledged:

The accuracy of the simulation depends on the quality of the material property data, particularly temperature-dependent thermal properties and the heat source model.
Phase transformation effects (austenite to martensite, martensite tempering) are not captured in a purely thermal simulation and require coupled thermo-metallurgical analysis.
The simulation assumes ideal boundary conditions that may not fully represent the actual welding environment, including fixture constraints, convection patterns, and radiation from surrounding components.

Despite these limitations, the simulation provides valuable insights that complement experimental approaches. Engineers should use the simulation results as a guide for process development and optimization, while validating key predictions through physical experiments and non-destructive testing. The combination of numerical simulation and experimental verification represents the most effective approach to developing reliable surfacing repair procedures for critical components such as plungers in hydraulic systems.