MULTI-OBJECTIVE PARTICLE SWARM OPTIMIZATION OF THE K-TYPE SHELL AND TUBE HEAT EXCHANGER (CASE STUDY)

被引:2
|
作者
Nadi, M. [1 ]
Ehyaei, M. A. [1 ]
Ahmadi, A. [2 ]
Turgut, O. E. [3 ]
机构
[1] Islamic Azad Univ, Dept Mech Engn, Pardis Branch, Pardis New City, Iran
[2] Iran Univ Sci & Technol, Sch New Technol, Tehran, Iran
[3] Bakircay Univ, Fac Engn, Dept Mech Engn, Menemen Izmir, Turkey
来源
JOURNAL OF THERMAL ENGINEERING | 2021年 / 7卷 / 03期
关键词
Cryogenic; Heat exchanger; Optimization; Objective; GLOBAL SENSITIVITY-ANALYSIS; ECONOMIC OPTIMIZATION; GENETIC ALGORITHMS; ENVIRONMENTAL-ANALYSIS; SHAPE OPTIMIZATION; DESIGN APPROACH; THERMAL DESIGN; EXERGY; COST; ENTROPY;
D O I
10.18186/thermal.888261
中图分类号
O414.1 [热力学];
学科分类号
摘要
This paper investigated optimization of two objectives function include the total amount of heat transfer between two mediums and the total cost of shell and tube heat exchanger. The study was carried out for k-type heat exchanger of the cryogenic unit of gas condensates by multiple objective particle swarm optimization. Six decision variables including pipe pitch ratio, pipe diameter, pipe number, pipe length, baffle cut ratio, and baffle distance ratio were taking into account to conduct this simulation-based research. The results of mathematical modeling confirmed the actual results (data collected from the evaporator unit of the Tehran refinery's absorption chiller). The optimization results revealed that the two objective functions of heat transfer rate and the total cost were in contradiction with each other. The results of the sensitivity analysis showed that with change in the pitch ratio from 1.25 to 2, the amount of heat transfer was reduced from 420 to 390 kW about 7.8%. Moreover, these variations caused reduction in cost function from 24,500 to 23,500 $, less than 1%. On the other hand, an increase in pipe length from 3 to 12 meters, the heat transfer rate raised from 365 to 415 kW by 13.7%, while the cost increased from 20,000$ to 24500$ about 22%.
引用
收藏
页码:570 / 583
页数:14
相关论文
共 50 条
  • [21] Experimental and numerical study on the heat transfer and flow characteristics in shell side of helically coiled tube heat exchanger based on multi-objective optimization
    Wang, Guanghui
    Wang, Dingbiao
    Deng, Jing
    Lyu, Yiming
    Pei, Yuanshuai
    Xiang, Sa
    INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER, 2019, 137 : 349 - 364
  • [22] Energy-economic analysis and optimization of a shell and tube heat exchanger using a multi-objective heat transfer search algorithm
    Prajapati, Parth
    Raja, Bansi D.
    Patel, Vivek
    Jouhara, Hussam
    THERMAL SCIENCE AND ENGINEERING PROGRESS, 2024, 56
  • [23] Optimal Design of Shell-and-Tube Heat Exchanger Based on Particle Swarm Optimization Technique
    Jalilirad, S.
    Cheraghali, M. H.
    Ashtiani, H. Ahmadi Danesh
    JOURNAL OF COMPUTATIONAL APPLIED MECHANICS, 2015, 46 (01): : 21 - 29
  • [24] Techno-economic optimization of a shell and tube heat exchanger by genetic and particle swarm algorithms
    Sadeghzadeh, H.
    Ehyaei, M. A.
    Rosen, M. A.
    ENERGY CONVERSION AND MANAGEMENT, 2015, 93 : 84 - 91
  • [25] Many-objective optimization of shell and tube heat exchanger
    Raja, Bansi D.
    Jhala, R. L.
    Patel, Vivek
    THERMAL SCIENCE AND ENGINEERING PROGRESS, 2017, 2 : 87 - 101
  • [26] Dynamic Multi-Swarm Particle Swarm Optimization for Multi-Objective Optimization Problems
    Liang, J. J.
    Qu, B. Y.
    Suganthan, P. N.
    Niu, B.
    2012 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2012,
  • [27] Multi-Objective Particle Swarm Optimization based on particle density
    Hasegawa T.
    Ishigame A.
    Yasuda K.
    IEEJ Transactions on Electronics, Information and Systems, 2010, 130 (07) : 1207 - 1212+16
  • [28] Multi-objective optimization using bat algorithm for shell and tube heat exchangers
    Tharakeshwar, T. K.
    Seetharamu, K. N.
    Prasad, B. Durga
    APPLIED THERMAL ENGINEERING, 2017, 110 : 1029 - 1038
  • [29] Robust optimization using multi-objective particle swarm optimization
    Ono S.
    Yoshitake Y.
    Nakayama S.
    Artificial Life and Robotics, 2009, 14 (02) : 174 - 177
  • [30] A modified particle swarm optimization for multimodal multi-objective optimization
    Zhang, XuWei
    Liu, Hao
    Tu, LiangPing
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2020, 95