• CN: 11-2187/TH
  • ISSN: 0577-6686

Journal of Mechanical Engineering ›› 2022, Vol. 58 ›› Issue (22): 438-449.doi: 10.3901/JME.2022.22.438

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Research on Multi-objective Optimization of Pipeline Layout of LNG Refueling Station

WAN Qi-hang1, HE Bo-yan1,2, NIE Rui1, WANG Guo-biao1,2, YANG Jian-kun3   

  1. 1. Key Laboratory of Mechanism Theory and Equipment Design of Ministry of Education, Tianjin University, Tianjin 300354;
    2. International Institute for Innovative Design and Intelligent Manufacturing of Tianjin University in Zhejiang, Shaoxing 312099;
    3. CNOOC Energy Development Equipment Technology Co., Ltd., Shaoxing 312099
  • Received:2022-05-26 Revised:2022-08-01 Online:2022-11-20 Published:2023-02-07

Abstract: Liquefied natural gas(LNG) refueling station pipelines are installed at ambient temperature and served under low temperature, internal pressure, and a wide range of temperature fluctuations. An optimal design method is proposed for LNG pipeline layout based on a non-dominated solution sorting multi-objective genetic algorithm to reduce pipeline construction and operation costs and improve safety. In this method, a simplified model is established by introducing the transfer matrix method, which can realize the rapid and practical analysis of the stress and deformation and then conduct a comprehensive evaluation of the pipeline. In order to complete the pipeline layout that minimizes the length, the number of elbows, the loss of flow resistance, the stress, and the deformation under the premise of conforming to the engineering rules, an optimization model for LNG pipeline is established based on genetic algorithm. The multi-objective optimization method is used to obtain the Pareto optimal layout scheme in terms of the short path, low energy consumption, and high safety. Finally, thermal-structural coupling analysis is carried out on the optimized pipeline layout scheme under different working conditions to ensure its safe and reliable operation and verify the method's correctness and effectiveness.

Key words: piping layout, transfer matrix method, multi-objective optimization, genetic algorithm

CLC Number: