Numerical Simulation of Solid-State Phase Transformation and Residual Stress in TIG Welding of Ti6Al4V Thin Sheets

Literature Overview and Research Background

This paper, published in 2022 in the journal China Shipbuilding (Vol. 63, Issue 5, pp. 53-70) by researchers from the China Ship Scientific Research Center and Shanghai Jiao Tong University, addresses a critical challenge in titanium alloy fabrication: understanding how welding parameters influence microstructure, residual stress, and deformation in Ti6Al4V thin sheets. The study employs a coupled thermo-structural-phase-field finite element framework built on the JMAK equation and the K-M equation to model solid-state phase transformations during TIG welding. This is particularly relevant for shipbuilding and aerospace applications where Ti6Al4V thin sheets (1.6 mm in this study) are increasingly used for their excellent strength-to-weight ratio and corrosion resistance, yet their welding remains notoriously difficult due to the complex alpha-beta phase behavior and high susceptibility to distortion and residual stress.

Core Technical Approach and Methodology

The researchers constructed a coupled thermal-microstructure-mechanical finite element model using Abaqus software. The thermal analysis incorporates a moving heat source model representing the TIG arc, while the phase transformation model uses the JMAK (Johnson-Mehl-Avrami-Kolmogorov) equation to describe the kinetics of alpha to beta phase transformation during cooling, and the K-M (Kohara-Matsumura) equation to model the reverse transformation upon reheating. This dual-equation approach captures the essential metallurgical behavior of Ti6Al4V during the multiple thermal cycles experienced in multi-pass welding.

The phase transformation model accounts for three principal phases: equilibrium alpha phase, alpha-prime martensite, and beta phase. The JMAK equation describes the fraction of transformed phase as a function of temperature and time, incorporating nucleation and growth kinetics parameters calibrated from dilatometry and DSC data. The K-M equation supplements this by modeling the transformation during reheating cycles, which is critical for understanding how prior welding passes affect subsequent passes.

The mechanical analysis couples the thermal and phase transformation fields to compute residual stresses and deformation. The key innovation lies in assigning distinct thermomechanical properties to each phase (alpha, alpha-prime, and beta), recognizing that these phases have significantly different elastic moduli, thermal expansion coefficients, and transformation-induced strains. This is a substantial improvement over conventional models that treat the weld zone as a homogeneous material with averaged properties.

Key Technical Parameters and Phase Behavior

The phase diagram of Ti6Al4V shows that the beta-transus temperature (approximately 995°C) separates the alpha-beta two-phase region from the single-phase beta region. During TIG welding, the weld centerline may exceed this temperature, producing a beta-only zone upon cooling that subsequently transforms to a mixture of alpha and alpha-prime martensite. The HAZ experiences temperatures between the beta-transus and the melting point, leading to alpha grain growth and partial beta formation. The base metal region remains below the beta-transus and retains its original microstructure.

The paper demonstrates that the hardness distribution across the weld joint correlates strongly with the simulated microstructure composition. Regions rich in alpha-prime martensite exhibit higher hardness due to the fine acicular structure and solute trapping, while regions with coarse alpha grains show lower hardness. The beta phase, when present in equilibrium conditions, is softer but more ductile. This phase-hardness relationship provides a quantitative basis for predicting mechanical properties from process parameters.

Residual Stress Analysis and Distortion Control

The residual stress distribution reveals characteristic patterns: high tensile longitudinal stresses in the weld centerline, compressive stresses in the HAZ, and a transition to near-zero stresses in the base metal. The paper highlights that the composition ratio of alpha and beta phases in different regions significantly influences the residual stress magnitude and distribution pattern. This is because the transformation strain associated with the beta-to-alpha-prime transformation (approximately 0.1-0.2% volumetric expansion) acts as an additional internal strain source that superimposes on the thermal contraction strains.

The distortion analysis shows that the alpha-beta phase composition difference between the weld center and the base metal creates asymmetric strain fields, leading to angular distortion in thin sheets. The simulation results, when compared with measured deformation, confirm that the phase transformation-induced strain is a dominant contributor to the final distortion, particularly in thin sheets where the thermal mass is low and cooling rates are high.

Engineering Practice Implications and Reflections

This research has direct implications for welding process optimization in shipbuilding and aerospace manufacturing. The key insight is that welding parameters can be adjusted not merely to control heat input but to deliberately manipulate the phase composition in the weld zone. For example, increasing the welding speed reduces the time available for alpha-prime martensite formation, potentially yielding a more equilibrium alpha-beta structure with better ductility. Conversely, slower welding speeds promote martensitic transformation, which may be desirable for higher strength but at the cost of increased residual stress and potential cracking susceptibility.

From a practical standpoint, the phase-transformation-coupled FEM model provides a predictive tool that can be used in welding procedure qualification to screen parameter combinations before physical trials. This is especially valuable for titanium alloy welding, where material costs are high and trial-and-error experimentation is expensive. The model can also be used to evaluate the effectiveness of post-weld stress relief treatments by simulating the stress redistribution during heat treatment.

The study also underscores the importance of post-weld heat treatment in titanium alloy fabrication. The alpha-prime martensite formed during rapid cooling is metastable and can be softened by a tempering treatment (typically 450-550°C for 1-2 hours), which converts it to a more stable alpha-beta structure with improved ductility and fatigue resistance. The simulation framework developed here can be extended to model this post-weld heat treatment process, providing a complete process chain simulation from welding through final heat treatment.

A critical observation for engineers is that the residual stress state in titanium welds is not solely determined by thermal gradients but is significantly influenced by the phase transformation sequence and the thermomechanical property differences between phases. This means that conventional residual stress prediction models that ignore phase transformation will underestimate or mispredict the actual stress state, potentially leading to inadequate stress relief specifications or incorrect distortion compensation strategies.

The research methodology itself serves as a model for how to approach complex welding metallurgy problems: establish a physically grounded constitutive model, implement it in a validated FEM framework, and verify against experimental measurements. This rigorous approach builds confidence in simulation predictions and enables data-driven process optimization rather than purely empirical parameter tuning. For titanium alloy thin sheet welding in marine and aerospace applications, this work represents a significant advancement in our ability to predict and control weld quality through process parameter selection.