Risk Assessment of Deep Foundation Pit Construction Based on Analytic Hierarchy Process and Fuzzy Mathematics
Author(s): |
Guowang Meng
Jingsong Huang Bo Wu Yanping Zhu Shixiang Xu Jianhua Hao |
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Medium: | journal article |
Language(s): | English |
Published in: | Advances in Civil Engineering, January 2020, v. 2020 |
Page(s): | 1-12 |
DOI: | 10.1155/2020/8840043 |
Abstract: |
The construction risk of deep foundation pit (DFP) engineering is high, and accidents occur frequently. It is necessary to evaluate the risk of deep foundation pits before construction. At present, although there are many risk assessment methods, there is not one with strong applicability and high accuracy. Based on expert scoring, this paper analyses the risk from two aspects (the severity of consequences and the probability of occurrence), divides the severity of the consequences into five indexes, calculates the risk by using the analytic hierarchy process (AHP), and sets the expert weight index so that the subjective expert scoring result can obtain the best possible objective calculation result. In addition, this paper uses the membership function from fuzzy mathematics to establish the level of risk and optimize the evaluation criteria of risk events. An engineering example is introduced, and the result of the risk assessment shows that the evaluation result R (risk value) obtained by the optimized risk assessment method in this paper is 7.9 and that the level of risk is grade III. The risk assessment method proposed in this paper has strong applicability and can obtain more accurate evaluation results. This method can provide a reference for the risk assessment of deep foundation pit engineering. |
Copyright: | © Guowang Meng 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. |
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10474970 - Published on:
15/11/2020 - Last updated on:
02/06/2021