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This present research work examines the mechanical characteristics of aluminium deposition on carbon steel by friction surfacing and further simulates by using a variety of transmutational optimization techniques. To simulate the outcomes of aluminium deposition like coating thickness and coating width, three optimization techniques were used namely response surface methodology, artificial neural network, and particle swarm optimization. Several experimental samples were prepared by using different data combinations and consequently the accuracy level of each individual computations is recorded and compared. The simulation results showed that the particle swarm optimization (PSO)-based simulation outperformed compared to artificial neural network (ANN) and response surface methodology (RSM) with the lowest mean squared error. For the PSO-based simulation, the minimal mean squared error for coating width, coating thickness, tensile strength, and bending strength was found to be as low as 0.27326%, 0.3853%, 0.04775% and 0.1842%, respectively. It was also noted that the PSO-based simulation’s processing time was much lesser than ANN and RSM simulation.

During friction surfacing of dissimilar alloys, different shielding techniques are used to avoid oxidation and corrosion behaviour of developed coatings. The present study explores the effect mechanical and corrosion performance of friction surfaced aluminium deposits over carbon steel by forced convection nitrogen shielding (FCNS) process. Appropriate friction surfacing process parameters are selected for experimental work, and the substrate plate was maintained a constant preheating temperature of 200 °C for obtaining better deposition. During deposition process, three different volume flow rates of nitrogen gas were supplied, namely FCNS-5, FCNS-10, and FCNS-15. The developed coating’s mechanical strength and corrosion behaviour are intensively investigated and compared with the coating developed by without apply of forced convention process (FCNS-0). The microstructural image received from electron backscattered diffraction (EBSD shows that the restoration activities and dynamically recrystallized grain growth are high towards higher volume of nitrogen supplied during FCNS process; as a result, an improved mechanical strength of the coating was achieved. Furthermore, the corrosion behaviour was analysed by electrochemical impedance and potentiodynamic polarization test. The impedance test shows a less corrosion current of the aluminium coating at FCNS-15 process. The potential dynamic polarization test confirms a lesser I corr and higher E corr value of aluminium coating in FCNS-15 process which proved a better corrosion resistance deposition compared to other processes.