Viscosity plays a pivotal role in the performance of welding fluxes by directly affecting the weld pool and the resultant weld metal, both of which are largely determined by heat and mass transfer during the welding process. Accurate viscosity prediction is essential for developing high-quality welding fluxes. However, existing models struggle to capture the complex nonlinear relationships between viscosity, composition, and temperature, which may significantly compromise robustness and generalization. To address this challenge, we incorporate NBO/Si (the average number of non-bridging oxygens per network former Si4⁺) as an intrinsic structural descriptor and propose a structure-informed deep neural network (S-DNN) that hierarchically models the composition-structure-viscosity relationship, effectively capturing nonlinear viscosity features. The S-DNN demonstrates excellent predictive performance (coefficient of determination [R2] = 0.9053, mean absolute error [MAE] = 0.0633 Pa·s, and root mean square error [RMSE] = 0.1101 Pa·s). Cross-validation employing multiple experimental datasets further validates the generalization and engineering applicability. Incorporating structural descriptors improves model performance by providing physical constraints. Compared to a basic deep neural network that relies solely on composition and temperature, S-DNN offers significantly higher accuracy. This work establishes a reliable, data-driven framework for the intelligent design of welding fluxes.
High-frequency induction welding (HFIW) is the predominant process used to weld strip edges during the production of automotive structural tubing. The high-throughput nature of HFIW makes it ideal for welding advanced high-strength steel tubes; however, oxides containing Al, Mn, and Si can sometimes form along the strip edges and become entrapped within the weld bond line. In welds containing oxide inclusions, the strength and ductility of the weld joint will be significantly decreased. High operational costs of running a tube make it difficult to determine favorable conditions for oxide inclusion formation through mill trials. This study shows that the Gleeble was capable of providing insights on appropriate welding temperatures to achieve defect-free HFIW in TRIP 690. The simulated samples reproduced the bond line and heat-affected zone microstructures of the industrially produced HFIW welds. Mechanical characterization revealed similar hardness distribution across the Gleeble and HFIW welds. Notably, bond line oxide inclusions, such as those found in HFIW tubes, were also observed in the simulated welds. The effects of these inclusions on tensile properties and fracture mechanisms in industrial and simulated welds were determined, and ideal conditions for producing oxide-free welds to ensure superior weld mechanical properties were determined.
Residual stress (RS) from welding poses major challenges, especially in dissimilar joints such as 1018 steel and 304 stainless steel, where thermal expansion mismatches intensify tensile stress. Conventional post-weld heat treatments, although effective for homogeneous materials, often require substantial energy, specialized equipment, and extensive processing time, making them less practical for dissimilar metal weld applications. This study explores an alternative, energy-efficient method — ultrasonic impact treatment (UIT) — to address RS in both similar and dissimilar metal welds. This study employs UIT on the top and bottom surfaces of welds and measures RS in the longitudinal, transverse, and normal directions using neutron diffraction at a high flux isotope reactor. Findings reveal that UIT significantly reduces longitudinal RS in similar welds but introduces moderate increases in transverse and normal RS due to stress redistribution dynamics. UIT demonstrates strong potential for RS modification; however, its application to dissimilar welds, such as 1018 and 304, requires careful parameter control to account for asymmetric material behavior and ensure consistent stress relief.
Further development of manufacturing methods and metallic alloys is crucial for creating next-generation energy production systems with enhanced strength, toughness, creep resistance, and/or corrosion resistance. For wire-based additive manufacturing (AM), wire materials are often cheaper than powdered metal, impurity contents are easier to control, deposition rates are substantially higher than those of powder-based AM, and wire arc AM is backed by decades of experience in multipass welding, cladding, and build-up repairs. To further expand the capabilities of wire arc additive manufacturing, a multiwire gas tungsten arc welding AM system was developed to independently introduce two commercially available nickel-based alloys, Alloy 617 and Alloy 740H, as weld wires into a single weld pool, thereby introducing chemical composition gradients with the intent of altering local material properties. This research analyzed weld metal dilutions and evaluated the composition profiles at different proportions of nickel alloy filler wires. The work demonstrated that multiwire gas tungsten arc-directed energy deposition can deposit graded compositions predictably via a simple mathematical analysis based on mass balance.
The use of scrap for steel making has increased worldwide and is expected to continue as steelmakers and users pursue sustainability efforts. Advances in steelmaking practices have enabled greater scrap recyclability and energy savings, but have come at the cost of reduced control over residual elements such as copper. This work studies the effect of increased copper content, up to 0.26 wt-%, on the base-metal microstructure and resistance spot-welding behavior of a low-carbon automotive sheet steel. Alloys were subcritically annealed prior to spot welding, tensile-shear testing, electrical resistivity measurements, and microstructural analysis. The higher-copper alloys showed increased base-metal strength, likely due to copper solid-solution strengthening. The higher-copper content alloys also exhibited higher electrical resistivity, resulting in a greater incidence of expulsion during resistance spot welding. Despite increased expulsion at high welding currents, resistance spot welds of the higher copper content alloys showed higher strength and lower ductility in tensile-shear testing. This work shows that elevated residual copper content can be accommodated in welded automotive steel sheets, provided base metal processing and welding parameters are adjusted to account for its influence.
