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Multifactor Uncertainty Analysis of Construction Risk for Deep Foundation Pits.

Authors :
Zhang, Wei
Huang, Zhen
Zhang, Jiabing
Zhang, Ruifu
Ma, Shaokun
Source :
Applied Sciences (2076-3417); Aug2022, Vol. 12 Issue 16, pN.PAG-N.PAG, 18p
Publication Year :
2022

Abstract

As it is affected by many uncertain factors, the construction risk of deep foundation subway station pits involves fuzzy and random uncertainties. Considering the fuzzy and random uncertainties involved in risk evaluation, an improved fuzzy comprehensive evaluation method combining a triangular cloud model and the probability density function (PDF) is proposed in this study. First, with reference to the actual situation of deep foundation pit construction, the sources of construction risk are identified, and a construction risk evaluation index system is established. Second, the Delphi method is used to analyse the importance of each index of the evaluation object in order to obtain the evaluation data. The fuzzy best worst method (FBWM) is used to calculate the weight of the evaluation indices. Then, the triangular cloud model is used to represent the risk grade membership function. In addition, the fuzzy comprehensive evaluation method is used to comprehensively evaluate the construction risk of deep foundation pits. The fuzzy comprehensive evaluation vector is obtained for the indices possibility (P) and loss (C), and the weighted average value of the vector's risk grade is calculated. Finally, probability analysis is carried out using PDF to determine the risk grade of P and C, and thus, to determine the risk grade of deep foundation pit construction. This method optimises the risk evaluation process of deep foundation pit construction and realises the visualisation of the comprehensive evaluation results, making the risk evaluation process transparent and convenient for use by risk analysts. This method is applied to predict the construction risk grade of a deep foundation pit project in Nanning, China, and the prediction results are consistent with the actual situation. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20763417
Volume :
12
Issue :
16
Database :
Complementary Index
Journal :
Applied Sciences (2076-3417)
Publication Type :
Academic Journal
Accession number :
158733004
Full Text :
https://doi.org/10.3390/app12168122