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Optimization of Dual-Design Operation Ventilation System Network Based on Improved Genetic Algorithm

Author

Listed:
  • Yanbo Feng

    (School of Mechanical Engineering, Tongji University, Shanghai 200070, China)

  • Han Zhu

    (School of Mechanical Engineering, Tongji University, Shanghai 200070, China)

  • Xiwen Feng

    (School of Mechanical Engineering, Tongji University, Shanghai 200070, China)

  • Qianru Chen

    (School of Mechanical Engineering, Tongji University, Shanghai 200070, China)

  • Xiangyu Sun

    (Tongji Architectural Design (Group) Co., Ltd., Shanghai 200092, China)

  • Zhengrong Li

    (School of Mechanical Engineering, Tongji University, Shanghai 200070, China)

Abstract

The COVID-19 pandemic has emphasized the crucial role of ventilation systems in mitigating cross-infections, especially in infectious-disease hospitals. This study introduces a dual-design operation ventilation system that can operate under two sets of ventilation conditions for normal and epidemic times. A challenge is optimizing duct diameters for required airflow while maintaining hydraulic balance. We designed an improved genetic algorithm with an adaptive penalty factor and velocity constraint, as well as the improved crossover probability and mutation probability. The improved genetic algorithm is suitable for ventilation system networks, which can find a better combination of air duct diameters to improve the hydraulic balance rate and reduce the usage of air valves, resulting in efficient hydraulic balancing commissioning. A supply air ventilation system of an actual hospital in China was selected as a case study, and the number of imbalanced air ducts was reduced from 14 to 4. Compared with the traditional genetic algorithm, it has a faster search speed and a better global search ability, which is effective for the optimal design of ventilation system networks.

Suggested Citation

  • Yanbo Feng & Han Zhu & Xiwen Feng & Qianru Chen & Xiangyu Sun & Zhengrong Li, 2023. "Optimization of Dual-Design Operation Ventilation System Network Based on Improved Genetic Algorithm," Energies, MDPI, vol. 16(24), pages 1-15, December.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:24:p:7931-:d:1294918
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    References listed on IDEAS

    as
    1. Kun Ding & Yong Ni & Lingfeng Fan & Tian-Le Sun & Tabasam Rashid, 2022. "Optimal Design of Water Supply Network Based on Adaptive Penalty Function and Improved Genetic Algorithm," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-8, March.
    2. Yunjun Zhang & Yuying Li & Lu Wang & Mingyuan Li & Xiaohua Zhou, 2020. "Evaluating Transmission Heterogeneity and Super-Spreading Event of COVID-19 in a Metropolis of China," IJERPH, MDPI, vol. 17(10), pages 1-11, May.
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    4. Tianwei Mu & Yaqi Li & Ziyi Li & Luyue Wang & Haoqiang Tan & Chengzhi Zheng, 2021. "Improved Network Reliability Optimization Model with Head Loss for Water Distribution System," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(7), pages 2101-2114, May.
    5. Dyani Lewis, 2020. "Is the coronavirus airborne? Experts can’t agree," Nature, Nature, vol. 580(7802), pages 175-175, April.
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