In Situ Synthesis of Cr2AlC Gradient Coating by Plasma Transferred Arc Cladding

Li, Yongjun; Chen, Hualin; Zhang, Zanzan; Wen, Xu; Wang, Zhipeng; Feng, Zongjian; Li, Zhigang; Kuang, Yunkun; Zhang, Xiaobin

doi:10.1007/s11666-023-01530-4

Cited by 2 publications

(1 citation statement)

References 37 publications

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“…As one of the MOGA techniques, the NSGA‐II has been widely adopted by many researchers due to its special characteristics of fast sorting and elite MOGA. [ 32–34 ] For example, Yang et al [ 30 ] performed a multi‐objective optimization strategy based on the RSM and a genetic algorithm for the design of a spiral separator with holes. Based on this strategy, they obtained a separator structure with higher efficiency and lower resistance.…”

Section: Non‐dominated Sorting Genetic Algorithm‐iimentioning

confidence: 99%

Multi‐objective optimization of drainage‐plates in wave‐plate mist eliminators using experiment and data‐driven modelling for lower water loss and energy requirement

et al. 2022

Can J Chem Eng

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Wave-plate mist eliminators are widely employed as gas-liquid separation devices to prevent the liquid escaping from thermal power plants or other cooling towers. In this study, the wave-plate mist eliminator with drainage plates was numerically analyzed and the effects between geometrical variables on two objectives, namely, pressure drop (ΔP) and separation efficiency (η), were revealed. Plate spacing, width, and length, as well as the relative position of the drainage plate, were thoroughly investigated. A combined strategy was developed for multi-objective optimization of the wave-plate mist eliminator by integrating computational fluid dynamics (CFD) simulation, response surface methodology (RSM), non-dominated sorting genetic algorithm-II (NSGA-II), and a technique for order of preference by similarity to ideal solution (TOPSIS) method. The results demonstrated that the relative position of drainage plates has a greater impact on the overall performance, whereas the width of drainage plates has the minimum effect. With the implementation of NSGA-II and the TOPSIS method, an optimal solution for the design of the mist eliminator was obtained. After comparing with the baseline case, the optimized case presents promising characteristics with high separation efficiency (enhanced by 3.6% ~9.06%) and a low energy consumption coefficient (reduced by 72.30% at η = 45%).

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Section: Non‐dominated Sorting Genetic Algorithm‐iimentioning

confidence: 99%