Design optimization of a shell-and-tube heat exchanger with disc-and-doughnut baffles for aero-engine using one hybrid method of NSGA II and MOPSO. (January 2023)

• Record Type: Journal Article
• Authors: Xu, Zhe; Ning, Xin; Yu, Zongling; Ma, Yufeng; Zhao, Zhiyong; Zhao, Binghao
• Is Part Of: Case studies in thermal engineering. Volume 41(2023)
• Publication Date: 2023-01
• Subjects: Performance prediction -- Parametric study -- Configuration optimization -- Slipcevie -- Sobol' -- NSGA II-MOPSO; NSGA II-MOPSO Non-dominated Sorting Genetic Algorithm II- Multi-objective Particle Swarm Optimization; Heat engineering -- Case studies -- Periodicals; 621.40205
• DOI: 10.1016/j.csite.2022.102644
• Languages: English
• ISSNs: 2214-157X

Abstract

Abstract: A performance prediction model is built utilizing Slipcevie method and the experimental verification results show that the average errors of Q, Δ P t, Δ P s are 4.4%, 5.3%, 6.0%, respectively. Through parametric study of D do_i, D db, N b by Sobol' method based on the model, it could be found that the parameters' effects are unlinear and conflicted in most cases, and whether the interaction between factors is considered or not, the influences of D db, D do_i, and N b on Q /Δ P t, Q /Δ P s, and G are the strongest, respectively. One configuration optimization method by NSGA II-MOPSO is proposed to increase Q /Δ P t, Q /Δ P s and decrease G, simultaneously, and the comparison results between four chosen optimal solutions and the original indicate that Q /Δ P t increases by 1.50% on average, and Q /Δ P s increases by 32.35% on average, while G averagely decreases by 29.18%. Besides, optimization comparison among NSGA II-MOPSO, NSGA II, and MOPSO is conducted and it could be concluded that NSGA II-MOPSO is the best, followed by MOPSO and then NSGA II, which illustrates that this method is feasible and valid, and could provide significant guidance for design.