ANSYS-Based Stress Analysis of Flat Plate Surfacing Solidification Process Study Note

Literature Overview

The paper by Hao Zilong and Shi Guanglin from Guangxi University of Science and Technology presents a finite element analysis (FEA) of the temperature field and stress field during flat plate surfacing solidification using ANSYS. The study employs a Gaussian surface heat source model with APDL (ANSYS Programming Language) to simulate the moving heat source, providing insights into residual stress distribution and thermal cracking susceptibility. This computational approach offers engineers a powerful tool for process optimization before physical trials.

Core Technical Content

FEA Model Description

The simulation model includes the following key elements:

Model Parameter	Specification
Base material	25 steel (Q235 equivalent)
Geometry	Flat plate, typical dimensions
Heat source model	Gaussian surface heat source
Heat source distribution	Three-dimensional Gaussian function
Moving heat source	Implemented via ANSYS APDL
Analysis type	Three-dimensional transient thermo-mechanical
Element type	Solid72 (thermal), Solid95/96 (structural)
Contact conditions	Adhesive contact at fusion boundary

Gaussian Heat Source Model

The heat source is defined as a surface Gaussian distribution:

q(x,y) = (3Q)/(πR²) × exp(-3r²/R²)

Where:

Q = Total heat input rate (W)
R = Effective heat source radius (mm)
r = Radial distance from heat source center (mm)

The moving heat source is implemented through APDL commands that update the heat source position at each time step, simulating the welding travel direction.

Stress Field Results

The simulation reveals distinct stress distribution patterns:

Stress Component	Maximum Location	Typical Value	Physical Origin
Longitudinal stress (σx)	Weld bead center	200–350 MPa (tensile)	Contraction during solidification and cooling
Transverse stress (σy)	Fusion boundary	150–280 MPa (tensile)	Constraint from surrounding base metal
Residual stress	HAZ and fusion zone	Complex distribution	Thermal gradients and phase transformations

Key Findings on Thermal Cracking Susceptibility

The study identifies two critical process parameters that influence thermal cracking tendency:

Welding current reduction: Lower current reduces the peak temperature and thermal gradient, decreasing the driving force for hot cracking. The optimal current range for 25 steel surfacing is 200–280 A.
Welding speed increase: Higher travel speed reduces the heat input per unit length, narrowing the HAZ and reducing the volume of material subject to high thermal gradients. However, excessive speed may lead to incomplete fusion or lack of penetration.

Process Parameter	Effect on Thermal Cracking	Recommended Range
Welding current	Higher current → higher cracking risk	200–280 A
Welding speed	Higher speed → lower cracking risk	300–500 mm/min
Heat input	Lower heat input → lower cracking risk	1.0–2.0 kJ/mm
Preheat temperature	Higher preheat → lower cracking risk	50–150°C
Electrode diameter	Smaller diameter → lower heat input	1.0–1.6 mm

Engineering Practice Integration

Application of FEA Results to Process Optimization

The computational approach described in this paper can be integrated into engineering practice through the following workflow:

Pre-trial simulation: Before physical welding trials, simulate the expected stress field for proposed parameters to identify potential cracking risks.
Parameter optimization: Use simulation results to narrow the parameter search space, reducing the number of physical trials required.
Post-trial validation: Compare simulated stress distributions with experimental measurements (such as X-ray diffraction or hole-drilling method) to validate the model.
Scale-up prediction: Use validated models to predict behavior for different plate thicknesses or geometries without additional trials.

FMEA Integration for Surfacing Process

The simulation results can be integrated into a Failure Mode and Effects Analysis (FMEA) for surfacing operations:

Failure Mode	Cause	Effect	Severity	Detection	Prevention
Hot cracking	High thermal gradient	Surface cracks in weld bead	9	Visual/PT	Reduce current, increase speed
Cold cracking	High residual stress + H hardness	Delayed cracking in HAZ	10	MT/UT after 48h	Preheat, PWHT, low-H electrode
Excessive distortion	High heat input	Geometric deviation	6	Dimensional check	Reduce heat input, back-up plate
Poor fusion	Low current/high speed	Lack of fusion at fusion boundary	8	RT/UT	Optimize parameters via FEA

Comparison with Experimental Data

The FEA predictions should be validated against experimental measurements:

Measurement Method	What It Measures	Typical Agreement with FEA
X-ray diffraction	Surface residual stress	±20–30 MPa
Hole-drilling	Near-surface stress profile	±25–40 MPa
Neutron diffraction	Bulk stress distribution	±15–25 MPa
Strain gauge	Real-time stress during welding	±30–50 MPa
DIC (Digital Image Correlation)	Displacement field	±5–10%

Key Questions and Reflections

Several aspects of this computational study merit further consideration:

Model accuracy: The Gaussian heat source model is a simplification of the actual arc heat transfer. How does this simplification affect stress prediction accuracy, particularly near the fusion boundary?
Material properties: The temperature-dependent material properties used in the model are critical for accurate stress prediction. How sensitive are the results to variations in thermal conductivity and elastic modulus?
Phase transformation: The model may not fully capture the effects of phase transformations (austenite to ferrite/pearlite) on residual stress. How significant is this omission for 25 steel?
Multi-pass effects: The study focuses on single-pass surfacing. How do results differ for multi-pass applications where thermal cycling from subsequent passes modifies the stress field?

The finding that longitudinal stress maximum occurs at the weld bead center while transverse stress maximum occurs at the fusion boundary is consistent with established welding mechanics theory. The longitudinal stress arises from the constrained contraction of the weld metal during solidification and cooling, while the transverse stress is a reaction stress developed in the surrounding base metal.

Study Insights and Implications

This FEA-based study demonstrates the practical value of computational methods in surfacing process optimization. For engineers, the key insight is that welding current and travel speed are the primary parameters controlling thermal cracking susceptibility, with current reduction and speed increase being the most effective countermeasures. The ANSYS-based approach provides a systematic framework for process development that reduces trial-and-error experimentation while providing physical understanding of stress development mechanisms. For production engineers, the recommended parameter ranges (200–280 A current, 300–500 mm/min speed for 25 steel surfacing) provide a starting point for qualification trials that can be refined through FEA-guided optimization. The integration of computational analysis with experimental validation represents the modern approach to welding process development, enabling faster qualification cycles and more reliable process windows for surfacing applications.