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Optimization and Reliability Analysis of the Combined Application of Multiple Air Tanks Under Extreme Accident Conditions Based on the Multi-Objective Whale Optimization Algorithm

Author

Listed:
  • Ran Li

    (School of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266525, China)

  • Yanqiang Gao

    (Qingdao Municipal Engineering Group Co., Ltd., Qingdao 266409, China)

  • Yihong Guan

    (Department of Resources and Environment, Shandong Water Conservancy Vocational College, Rizhao 276826, China)

  • Mou Lv

    (School of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266525, China)

  • Hang Li

    (School of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266525, China)

Abstract

The operational condition of fire water supply aims to ensure the continuous and reliable supply of high-pressure water in emergency situations. Assuming a fire breaks out in a mountain village located far from the city center, due to the significantly higher flow rate and velocity of the water supply pipeline compared to normal operating conditions, any malfunction or shutdown of the pump caused by improper operation could result in catastrophic damage to the pipeline system. In response to the call for sustainable development, addressing this urgent academic challenge means finding a way to safely and economically maintain a continuous water supply to the target water demand point, even under extreme accident conditions. In this paper, drawing on engineering examples, we considered air tanks with varying process parameters installed at multiple locations within a water conveyance system to prevent water hammer and ensure water supply safety. To ensure that air tanks are of high quality and cost-effective after procurement and use, a multi-objective optimization design model comprising fitting, optimization, and evaluation plates was constructed, aimed at selecting certain process parameters. In the multi-objective optimization design model, Latin hypercube sampling improved by simulated annealing (LHS-SA), stepwise regression analysis (SRA), the Multi-Objective Whale Optimization Algorithm (MOWOA), and the Multi-Criteria Decision Analysis (MCDA) method with various weight biases are used to ensure the rationality of the optimization process. By comparing the optimization results obtained using these different MCDA methods, it is evident that the results output after AHP-EWM evaluation tend to be economic indicators, whereas the results output after FN-MABAC evaluation tend to be safety indicators. In addition, according to the sensitivity analysis of weight distribution, it can be inferred that the changes in maximum transient pressure head caused by water hammer have the most significant impact on final decision-making.

Suggested Citation

  • Ran Li & Yanqiang Gao & Yihong Guan & Mou Lv & Hang Li, 2025. "Optimization and Reliability Analysis of the Combined Application of Multiple Air Tanks Under Extreme Accident Conditions Based on the Multi-Objective Whale Optimization Algorithm," Sustainability, MDPI, vol. 17(5), pages 1-23, March.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:5:p:2172-:d:1604053
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    References listed on IDEAS

    as
    1. Ming Liang & Gen Yang & Xiaojun Zhu & Hua Cheng & Liugen Zheng & Hui Liu & Xianglin Dong & Yanhai Zhang, 2023. "AHP-EWM Based Model Selection System for Subsidence Area Research," Sustainability, MDPI, vol. 15(9), pages 1-24, April.
    2. Singh, Kunwar P. & Basant, Ankita & Malik, Amrita & Jain, Gunja, 2009. "Artificial neural network modeling of the river water quality—A case study," Ecological Modelling, Elsevier, vol. 220(6), pages 888-895.
    3. Wang, Jianzhou & Du, Pei & Niu, Tong & Yang, Wendong, 2017. "A novel hybrid system based on a new proposed algorithm—Multi-Objective Whale Optimization Algorithm for wind speed forecasting," Applied Energy, Elsevier, vol. 208(C), pages 344-360.
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