Welding enables cost-effective fabrication of large structures in shipbuilding, aerospace and automotive industries, but repeated thermal cycles during multi-stage assembly inevitably cause distortions that often exceed design tolerances, degrading structural performance and requiring costly corrections. Despite significant advances in local weld modelling, predicting distortion in large, complex assemblies remains challenging due to interactions among material properties, structural geometry, heat input, welding sequence and restraint conditions, particularly for lightweight, thin-walled high-strength steels and aluminium alloys. This review synthesises research from 2000 to 2025 to assess distortion prediction and mitigation strategies for large metallic structures, emphasising industrial applicability. Thermo-elasto-plastic finite element methods provide high accuracy but at significant computational cost and inherent strain-based approaches offer efficient large-scale simulations but rely on calibration and simplifying assumptions, while local/global methods balance accuracy and computational efficiency. Data-driven surrogate models are emerging for rapid prediction and optimisation. No single approach is universally transferable across structural configurations, with scalability generally achieved at the expense of calibration requirements and application-specific assumptions. Distortion mitigation is most effective at the design stage through welding sequence optimisation and structural planning. In-process techniques such as thermal tensioning and controlled restraint further reduce distortions, while post-welding corrections remain less efficient. The literature is strongly concentrated on conventional structural steels, with only approximately 10
To investigate the weld bead formation behavior of MAG surfacing on a Q235 steel substrate inclined at 45° and the effects of overlap ratio on single-layer multipass deposited layers, a single-factor experimental method was employed to analyze the effects of wire feed speed, welding speed, and shielding gas flow rate on the morphology of single-pass weld beads. Subsequently, single-layer multipass surfacing experiments with different overlap ratios were conducted under the selected process conditions. Meanwhile, a finite element model was established using Simufact Welding to analyze the evolution of the temperature field and equivalent stress during the surfacing process. The experimental results showed that increasing the welding speed from 3 to 4 mm/s increased the weld bead width from 5.10 to 6.00 mm and the penetration depth from 1.21 to 1.52 mm, thereby improving the surface continuity and cross-sectional forming quality of the weld bead. The effects of five overlap ratios (15
Cu/Al interconnects in advanced electronic packaging face a fundamental conflict between low-temperature bonding and long-term thermal reliability. To address this, a SAC0307/Zn/Cu hybrid solder was employed for ultrasonic-assisted bonding of Cu and Al at 180 °C. The Cu content was varied from 0 to 20 wt.
Third-generation medium-manganese steel offers both a low cost and an excellent combination of strength and ductility, holding immense potential for automotive light-weighting applications. However, the influences of microstructures in the welding zone on propagation behaviors of fatigue cracks remain unclear. In this study, a 6-mm-thick plate made of medium-manganese steel is welded using laser welding and gas tungsten arc welding (GTAW) processes. Through combinations of optical microscopy, scanning electron microscopy, X-ray diffraction, electron backscatter diffraction, and fatigue testing, the relationships between microstructures and fatigue crack propagation behaviors in the base metal, laser weld zone, and GTAW zone are systematically investigated. Results indicate that the microstructure in the laser weld zone consists mainly of martensite with a small amount of bainite, whereas the GTAW zone is mainly composed of martensite and bainite with trace martensite-austenite (M-A) constituents. Both microstructures are significantly different from the ferrite-austenite structure of the base metal. Paris-law fitting yielded the fatigue crack growth rate equations for the base metal, laser weld zone, and GTAW zone. Analyses reveal that during steady-state propagation, with ΔK in the range of 15–30 MPa · m1/2, the crack growth rates follow the order: laser weld zone < base metal < GTAW zone. Notably, within the base metal, the fatigue crack propagation rate is jointly influenced by micro-texture and the density of high-angle grain boundaries. Specifically, prior-austenite grain boundaries, martensite packet boundaries, and lath block boundaries are found to effectively impede the crack growth rate.
The overall performance and lifetime of additively manufactured parts are strongly influenced by the local thermal history of the material. A realistic thermal process simulation allows prediction, interpretation and optimization of local microstructural evolutions, residual stress formations, defect formations and the resulting material properties. A pivotal point in thermal simulation is the adequate modeling of the local energy deposition imposed on the material by the heat source. Most commonly, a Gaussian-based model describes the heat distribution, based on measurements of the laser intensity profile. However, due to the complex nature of heat source–material interaction and its dependency on material, temperature and process parameters, it is unclear whether the heat flux also follows a Gaussian distribution. To study this assumption, four common heat source models, two-dimensional Gaussian, double ellipsoid, conical Gaussian and hemispherical, were investigated. First, their functional relations and thermal outcomes were implemented via FE simulations of a bead-on-plate model, enabling study of process parameters, material properties and geometrical aspects as process variables. Next, the models were validated for two AM cases using electric arc and laser beam heat sources, and the thermal histories were compared. The results reveal that using the Gaussian-based heat distribution can cause the temperature maxima to trail the heat source centre. This is particularly related to the rate of heat conduction from the melt pool to the surrounding base material and the heating rate. Since these phenomena depend on material properties and process parameters, considering both enables more accurate optimization of the AM process.
