Analysis and Prediction of Morphology and Properties of Laser-Directed Energy Deposition CoCrFeNi High-Entropy Alloy Using Response Surface Methodology and Non-dominated Sorting Genetic Algorithm II

Abstract

The laser-directed energy deposition (LDED) technique exhibits unique advantages in the production of high-entropy alloy (HEA), offering a novel approach for repairing and fabricating HEA coatings. However, the quality of deposited tracks is significantly influenced by multiple process parameters. To achieve well-formed and high-quality deposited tracks, this study employs response surface methodology (RSM) to investigate the underlying reasons and patterns governing the impacts of pivotal parameters on various assessment criteria of tracks. Based on the mathematical model of parameter-response correlation developed by RSM, the optimization was carried out by executing the second generation multi-objective optimization non-dominated sorting genetic algorithm II (NSGA-II) using Matlab code. The outcomes illustrate the Pareto frontiers of optimal coupling of multiple process parameters and multiple-objective matching of deposited tracks evaluation indicators. When employing the optimal process parameters, the microstructure gradually refines into non-directional equiaxed grains along the deposition direction, accompanied by a three-step stable increase in micro-hardness, yielding a single track with excellent morphology and microstructure. These findings provide theoretical support for the deposition of HEA with excellent morphology and performance.