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Health Assessment of Foundation Pit Based on the Fuzzy Analytical Hierarchy Process

Author(s):
ORCID
ORCID


Medium: journal article
Language(s): English
Published in: Advances in Civil Engineering, , v. 2022
Page(s): 1-8
DOI: 10.1155/2022/3245305
Abstract:

Many monitoring indexes affect the health condition of foundation pits to different extents. How to use a massive on-site monitoring dataset to quantitatively assess the health of foundation pits is a problem that deserves due consideration. This paper proposes a foundation pit health assessment model based on the fuzzy analytical hierarchy process (AHP) method. First, factors affecting the health of foundation pits are classified by the AHP, a hierarchical factor system for foundation pit health assessment is established, and the index scale method is used to assign weights to assessment factors at different hierarchical levels. Combined with the fuzzy mathematical method, the membership functions of four health degree levels (A to D) are constructed, and the determination range of each health degree level is given to realize the quantitative calculation of the health condition from the bottom-level assessment factor to the overall foundation pit. Considering that each assessment factor involves many monitoring points and different monitoring data, a comprehensive assessment operator is also constructed to highlight the most adverse impact. Finally, the proposed model is used to perform a health assessment of an actual foundation pit project, and the variation in the foundation pit health during the entire monitoring period is obtained. The health grade of the foundation pit is determined to be B, which is a basically healthy condition consistent with the on-site inspection results.

Copyright: © Jinbo Sun et al. et al.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10679004
  • Published on:
    18/06/2022
  • Last updated on:
    10/11/2022
 
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