Journal of Welding Science

In Wire and arc additive manufacturing (WAAM) based on Gas metal arc welding (GMAW) is one of the methods of manufacturing metal layer by layer. One of this method's basic steps is predicting the welding geometry created in each welding step. In the current research, an experimental study was conducted in this field considering the effective parameters of welding geometry. For this purpose, three parameters of voltage, welding speed, and wire feeding speed were considered as effective parameters on the welding geometry of the process. The width and height of the weld bead was selected as the answer according to the type and application of the research. The least squares support vector machine was used to model the welding geometry in the process. The results obtained from the regression (R2) of train, test, validation, and total were 0.945, 0.793, 0.894, and 0.881 respectively. The comparison between the experimental data and the model data shows the significance of the proposed model.

Society's great and growing demand for buildings and structures has created the need to apply new construction methods to shorten construction times, make buildings lighter, extend their useful life, and make them more earthquake-proof. In the long term, the new methods will lead to structural optimization, increased building performance, and the achievement of optimal operating conditions. New technologies are meeting society's increasing need for special structures more than ever. Additive manufacturing is based on gas metal arc welding as one of the fastest and most cost-effective manufacturing methods for primary metal structures. For this purpose, the three parameters voltage, wire feed speed, and welding speed were considered initial parameters affecting the width and height of the welding flux. To investigate the effects of the process,

16 experiments with input parameters were evaluated. The width and height of the sweat pollen were determined by experimental investigations. Subsequently, the resulting welding geometry is modeled using three numerical modeling methods, including intensive learning machines, relevence vector machine, and fuzzy logic. The comparison between the experimental data and the results of the three generated models shows that fuzzy logic comes closest to the experimental data of the welding geometry of the modeling methods. For example, the test data of the generative fuzzy model resulted in an average error for height and width of 0.667 and 0.5477, respectively, and a root mean square error for height and width of 0.0046 and 0.3, respectively, which expresses the generalization ability and reliability compared to other modeling methods in this process. Finally, a metal pattern of a special structure was produced based on arc and wire additive manufacturing based gas metal arc welding.

Welding is one of the methods of surface repair of cast irons. In this study, surface repair of gray cast iron was first performed by gas metal arc welding method with ER70S-6 welding wire under inter-pulse current, heat input of 393 J/mm and dilution of 17%. Also, to compare the results, two samples were welded with ENi-CI and E6013 covered electrodes. Microstructural studies showed that the microstructure of the interface of the sample is composed of martensite with fine lathes and upper bainite. Despite the presence of cementite (Fe₃C) next to alpha iron (α-Fe) in the interface area, the formation of incomplete mixing zone with bainite lathes in the ferrite zone has led to increased toughness and prevented crack formation. The hardness of the ER70S-6 sample was similar to that of the E6013 sample at the interface, at about 809 Vickers, which is 334 Vickers higher than the hardness of the ENi-CI sample. The results of the open circuit potential and potentiodynamic polarization tests showed that the ER70-CI sample, with a corrosion potential and current of -653 mV and 6.8 μA/cm², had a higher polarization resistance and was more resistant to galvanic corrosion than the ENi-CI sample (-622 mV and 8.9 μA/cm²).