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Multi-Source Monitoring Data Fusion Comprehensive Evaluation Method for the Safety Status of Deep Foundation Pit

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Listed:
  • Bo Wu

    (College of Civil Engineering and Architecture, Guangxi University, Nanning 530004, China
    School of Civil and Architectural Engineering, East China University of Technology, Nanchang 330013, China)

  • Yu Wei

    (College of Civil Engineering and Architecture, Guangxi University, Nanning 530004, China)

  • Guowang Meng

    (College of Civil Engineering and Architecture, Guangxi University, Nanning 530004, China)

  • Shixiang Xu

    (School of Civil and Architectural Engineering, East China University of Technology, Nanchang 330013, China)

  • Qinshan Wang

    (Jinan Rail Transit Group Co., Ltd., Jinan 250014, China)

  • Dianbin Cao

    (Jinan Rail Transit Group Co., Ltd., Jinan 250014, China)

  • Chenxu Zhao

    (China Railway Beijing Engineering Group Co., Ltd., Beijing 102308, China)

Abstract

Construction of the deep foundation pit (DFP) in subway stations is fraught with significant uncertainties, which may cause project delays due to discrepancies between single-indicator monitoring warning information and actual conditions at the site. Therefore, this article proposes a safety assessment method for DFP based on the Game-Cloud Model. An entirely quantitative assessment index system is established with on-site monitoring projects according to the design safety classification of DFP. Considering the one-sidedness of using a single method to determine the weights of assessment indices, game theory is introduced to calibrate the subjective and objective weights determined by the grey decision-making trial and evaluation laboratory (GDEMATEL) and the entropy method, respectively. Next, we use the forward cloud generator of the cloud model (CM) to generate the safety level membership function of the evaluation indicators. Finally, we quantitatively calculate the synthetic safety level of DFP using the comprehensive evaluation approach. A 19-day dynamic assessment was conducted on the actual engineering project by the proposed method. The results indicated that the synthetic safety level of the assessed area ranged between grades Ⅰ and Ⅱ, corresponding to Negligible and Acceptable in the acceptance criteria. Compared with the single-indicator monitoring warning results, it was more in line with on-site observation, which verified its reliability and practicality.

Suggested Citation

  • Bo Wu & Yu Wei & Guowang Meng & Shixiang Xu & Qinshan Wang & Dianbin Cao & Chenxu Zhao, 2023. "Multi-Source Monitoring Data Fusion Comprehensive Evaluation Method for the Safety Status of Deep Foundation Pit," Sustainability, MDPI, vol. 15(15), pages 1-18, August.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:15:p:11809-:d:1208000
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    References listed on IDEAS

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    1. Lin, Song-Shun & Shen, Shui-Long & Zhou, Annan & Xu, Ye-Shuang, 2021. "Novel model for risk identification during karst excavation," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
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    3. Bai, Chunguang & Sarkis, Joseph, 2013. "A grey-based DEMATEL model for evaluating business process management critical success factors," International Journal of Production Economics, Elsevier, vol. 146(1), pages 281-292.
    4. Shen, Shui-Long & Lin, Song-Shun & Zhou, Annan, 2023. "A cloud model-based approach for risk analysis of excavation system," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
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