IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i14p8378-d858543.html
   My bibliography  Save this article

Safety Assessment of Channel Seepage by Using Monitoring Data and Detection Information

Author

Listed:
  • Mengdie Zhao

    (School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou 450046, China
    Yellow River Engineering Consulting Co., Ltd., Zhengzhou 450003, China
    Henan Key Laboratory of Water Resources Conservation and Intensive Utilization in the Yellow River Basin, Zhengzhou 450008, China)

  • Chao Zhang

    (School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou 450046, China)

  • Shoukai Chen

    (School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou 450046, China
    Henan Key Laboratory of Water Resources Conservation and Intensive Utilization in the Yellow River Basin, Zhengzhou 450008, China)

  • Haifeng Jiang

    (College of Water Conservancy and Electric Power, Hohai University, Nanjing 210024, China)

Abstract

Seepage analysis has always been the focus of channel safety and stability research. Establishing a diagnosis method based on osmotic pressure monitoring data and combining the detection information to achieve osmotic safety is also an effective way to ensure the safety and stability of osmotic engineering. In this paper, a high-fill channel section of a water diversion project is taken as an example, and the study of osmotic safety is carried out by analyzing the engineering characteristics of linear engineering. High-fill channel sections were selected to study the temporal and spatial characteristics of various monitoring data reflecting the osmotic behavior of linear engineering; that is, these data reflect the time-varying regularity characteristics of the osmotic pressure value and the changing regularity of environmental variables. A single-point multifactor model of the monitoring data was established by establishing an evaluation index system, combining the monitoring index value method and the cloud model theory method according to the distribution law of the measured data and considering the uncertainty of the osmotic pressure data. Additionally, this model was integrated with the set pair analysis method to determine the monitoring data evaluation level; channel detection data information was collected, the abnormal detection of detection information was realized, and the monitoring data results were used to verify the detection results. In this way, an adaptive evaluation method reflecting the working behavior of high-filled channel sections is established, and a diagnostic technology for the safe operation of high-filled channel sections of linear engineering is proposed. The application results show that this method is suitable for engineering an osmotic safety assessment.

Suggested Citation

  • Mengdie Zhao & Chao Zhang & Shoukai Chen & Haifeng Jiang, 2022. "Safety Assessment of Channel Seepage by Using Monitoring Data and Detection Information," Sustainability, MDPI, vol. 14(14), pages 1-21, July.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:14:p:8378-:d:858543
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/14/8378/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/14/8378/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wei Ge & Zongkun Li & Robert Y. Liang & Wei Li & Yingchun Cai, 2017. "Methodology for Establishing Risk Criteria for Dams in Developing Countries, Case Study of China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(13), pages 4063-4074, October.
    2. Zhuguang Lan & Ming Huang, 2018. "Safety assessment for seawall based on constrained maximum entropy projection pursuit model," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 91(3), pages 1165-1178, April.
    3. Xiaoling Wang & Hongling Yu & Peng Lv & Cheng Wang & Jun Zhang & Jia Yu, 2019. "Seepage Safety Assessment of Concrete Gravity Dam Based on Matter-Element Extension Model and FDA," Energies, MDPI, vol. 12(3), pages 1-21, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kun Xu & Shuang Li & Jiao Liu & Cheng Lu & Guangzhe Xue & Zhengquan Xu & Chao He, 2022. "Evaluation Cloud Model of Spontaneous Combustion Fire Risk in Coal Mines by Fusing Interval Gray Number and DEMATEL," Sustainability, MDPI, vol. 14(23), pages 1-13, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jun Dong & Dongxue Wang & Dongran Liu & Palidan Ainiwaer & Linpeng Nie, 2019. "Operation Health Assessment of Power Market Based on Improved Matter-Element Extension Cloud Model," Sustainability, MDPI, vol. 11(19), pages 1-25, October.
    2. Hao Gu & Xiao Fu & Yantao Zhu & Yijun Chen & Lixian Huang, 2020. "Analysis of Social and Environmental Impact of Earth-Rock Dam Breaks Based on a Fuzzy Comprehensive Evaluation Method," Sustainability, MDPI, vol. 12(15), pages 1-15, August.
    3. Genbao Liu & Tengfei Zhao & Hong Yan & Han Wu & Fuming Wang, 2022. "Evaluation of Urban Green Building Design Schemes to Achieve Sustainability Based on the Projection Pursuit Model Optimized by the Atomic Orbital Search," Sustainability, MDPI, vol. 14(17), pages 1-23, September.
    4. Sen Zheng & Chongshi Gu & Chenfei Shao & Yating Hu & Yanxin Xu & Xiaoyu Huang, 2023. "A Novel Prediction Model for Seawall Deformation Based on CPSO-WNN-LSTM," Mathematics, MDPI, vol. 11(17), pages 1-22, August.
    5. Muhammad Ishfaque & Qianwei Dai & Nuhman ul Haq & Khanzaib Jadoon & Syed Muzyan Shahzad & Hammad Tariq Janjuhah, 2022. "Use of Recurrent Neural Network with Long Short-Term Memory for Seepage Prediction at Tarbela Dam, KP, Pakistan," Energies, MDPI, vol. 15(9), pages 1-16, April.
    6. Guanjie He & Junrui Chai & Yuan Qin & Zengguang Xu & Shouyi Li, 2020. "Coupled Model of Variable Fuzzy Sets and the Analytic Hierarchy Process and its Application to the Social and Environmental Impact Evaluation of Dam Breaks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(9), pages 2677-2697, July.
    7. Meimei Wu & Wei Ge & Zening Wu & Xi Guo & Danyang Di & Shuoqiao Huang, 2020. "Evaluation of the Benefits of Urban Water Resource Utilization Based on the Catastrophe and Emergy Methods," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(6), pages 1843-1853, April.
    8. Wang, Te & Li, Zongkun & Ge, Wei & Zhang, Hua & Zhang, Yadong & Sun, Heqiang & Jiao, Yutie, 2023. "Risk consequence assessment of dam breach in cascade reservoirs considering risk transmission and superposition," Energy, Elsevier, vol. 265(C).
    9. Gao, Guibing & Wang, Junshen & Yue, Wenhui & Ou, Wenchu, 2020. "Structural-vulnerability assessment of reconfigurable manufacturing system based on universal generating function," Reliability Engineering and System Safety, Elsevier, vol. 203(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:14:p:8378-:d:858543. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.