Multi-objective optimization of a non-uniform sinusoidal mini-channel heat sink by coupling genetic algorithm and CFD model

被引:0
|
作者
Ge, Ya [1 ]
Yin, Weixing [1 ]
Lin, Yousheng [1 ]
He, Kui [1 ]
He, Qing [1 ]
Huang, Si-Min [1 ]
机构
[1] Dongguan Univ Technol, Engn Res Ctr Distributed Energy Syst, Guangdong Prov Key Lab Distributed Energy Syst, Dongguan 523808, Peoples R China
基金
中国国家自然科学基金;
关键词
Heat sink; Non-uniform wavy channel; Multi-objective genetic algorithm; Multi-criteria decision-making; Heat transfer enhancement; WAVY CHANNEL; PERFORMANCE; DESIGN;
D O I
10.1016/j.applthermaleng.2024.124198
中图分类号
O414.1 [热力学];
学科分类号
摘要
Wavy mini-channel heat sinks (MCHS) can disrupt the development of the thermal boundary layer, resulting in superior performance compared to straight MCHS. For complete utilization of the coolant, this study proposed and optimized a non-uniform sinusoidal MCHS with varying wavelength or varying amplitude along the flow direction. The optimization for five design variables was accomplished through a multi-objective genetic algorithm, where the thermal resistance B or the pressure drop gyp p were defined as two objectives. The computational fluid dynamics (CFD) software was employed to solve all direct problems encountered during the evolutionary process. Compared to the straight MCHS with different channel widths, the optimal designs achieved reductions of 27.74 % in B or 59.51 % in gy p . Simultaneously, all the optimal values of the wavelength ratio and amplitude ratio indicate that enhancing the heat transfer performance downstream is more efficient. It was observed that among the five design variables, the number of wave cycles is the most relevant parameter with a Spearman's correlation up to 0.983. Subsequently, a multiple-criteria decision-making approach was employed to ascertain the best compromise solution to balance the two objectives. Although the B of the best compromise solution could be higher by 38.57 % than that of the lowest B solution, the gyp p presents a more substantial reduction of 92.45 % after the trade-off. Compared to the straight MCHS with the same gy p , the best compromise solution with varying wavelength reduces the B and the standard temperature deviation by 26.20 % and 76.98 % respectively, while lowering the average base temperature by 3.07 K. Therefore, the optimal non-uniform wavy MCHS, along with the optimization approach presented, is meaningful for practical applications.
引用
收藏
页数:13
相关论文
共 50 条
  • [41] A Non-uniform Clustering Based Evolutionary Algorithm for Solving Large-Scale Sparse Multi-objective Optimization Problems
    Shao, Shuai
    Tian, Ye
    Zhang, Xingyi
    BIO-INSPIRED COMPUTING: THEORIES AND APPLICATIONS, PT 1, BIC-TA 2023, 2024, 2061 : 103 - 116
  • [42] Three-objective shape optimization and parametric study of a micro-channel heat sink with discrete non-uniform heat flux boundary conditions
    Hadad, Yaser
    Ramakrishnan, Bharath
    Pejman, Reza
    Rangarajan, Srikanth
    Chiarot, Paul R.
    Pattamatta, Arvind
    Sammakia, Bahgat
    APPLIED THERMAL ENGINEERING, 2019, 150 : 720 - 737
  • [43] A SIMPLIFIED MULTI-OBJECTIVE GENETIC ALGORITHM OPTIMIZATION MODEL FOR CANAL SCHEDULING
    Peng, S. Z.
    Wang, Y.
    Khan, S.
    Rana, T.
    Luo, Y. F.
    IRRIGATION AND DRAINAGE, 2012, 61 (03) : 294 - 305
  • [44] A Genetic Cloud-model Algorithm to the Multi-objective Optimization Problem
    Li, Chunjie
    Chen, Tao
    Dong, Jun
    2008 4TH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS, NETWORKING AND MOBILE COMPUTING, VOLS 1-31, 2008, : 7760 - 7763
  • [45] Multi-objective optimization of a plate and frame heat exchanger via genetic algorithm
    Hamidreza Najafi
    Behzad Najafi
    Heat and Mass Transfer, 2010, 46 : 639 - 647
  • [46] Multi-objective optimization of a plate and frame heat exchanger via genetic algorithm
    Najafi, Hamidreza
    Najafi, Behzad
    HEAT AND MASS TRANSFER, 2010, 46 (06) : 639 - 647
  • [47] Multi-objective energy consumption scheduling based on decomposition algorithm with the non-uniform weight vector
    Lu, Hui
    Zhang, Mengmeng
    Fei, Zongming
    Mao, Kefei
    APPLIED SOFT COMPUTING, 2016, 39 : 223 - 239
  • [48] Non-Uniform Metamaterial Mushroom Antennas via a Genuine Multi-Objective Bayesian Optimization Method
    Zeng, Yunjia
    Qing, Xianming
    Chia, Michael Yan-Wah
    2024 18TH EUROPEAN CONFERENCE ON ANTENNAS AND PROPAGATION, EUCAP, 2024,
  • [49] A decision support tool coupling a causal model and a multi-objective genetic algorithm
    Blecic, Ivan
    Cecchini, Arnaldo
    Trunfio, Giuseppe A.
    APPLIED INTELLIGENCE, 2007, 26 (02) : 125 - 137
  • [50] A decision support tool coupling a causal model and a multi-objective genetic algorithm
    Blecic, I
    Cecchini, A
    Trunfio, GA
    INNOVATIONS IN APPLIED ARTIFICIAL INTELLIGENCE, 2005, 3533 : 628 - 637