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One of the mechanical properties of weldments influenced by the heat input generated by the Submerged Arc Welding (SAW) process is the Hardness of Weld Metal (HWM). This research was carried out to develop a non-linear regression model using the Response Surface Methodology (RSM) to predict the HWM in the SAW of low-carbon steel plates (St37) in the presence of Cr 2 O 3  nanoparticles. For developing the regression model, current, voltage, stick-out, welding speed, and Cr 2 O 3  nanoparticles were considered as the input variables and the HWM as the response. Analysis of variance was carried out to check the validity of the regression model and decide on the significant variables affecting the HWM. SEM and EDX analysis were performed on the weld to study the microstructure and elemental variables. The main and interactive effects of the input variables on the HWM were presented in graphical forms and analysed. The results showed that increasing the thickness of Cr 2 O 3  nanoparticles increased the HWM due to grain refinement in the weld metal. Furthermore, optimisation of the model was developed for finding the optimum values of the HWM. Finally, confirmation tests were carried out and they indicated that the error of the empirical model was 4.36%.

Modelling the hardness of weld metal in the submerged arc welding of low carbon steel plates: addition of CR 2 O 3 nanoparticles