Reliability Analysis of Deep Foundation Pit Using the Gaussian Copula-Based Bayesian Network

Bin Tan () and Qiyuan Peng
Additional contact information
Bin Tan: School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China
Qiyuan Peng: School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China

Mathematics, 2024, vol. 12, issue 24, 1-25

Abstract: Urban underground space development has heightened concerns over the safety of deep foundation pit construction. This study conducted time-series monitoring of critical safety-influencing factors and applied the Gaussian copula-based Bayesian network (GCBN) model for comprehensive reliability analysis of deep foundation pit support structures. The GCBN model, integrating the multivariate data management of pair copula with Bayesian network’s uncertainty handling, found that building settlement has the greatest impact on the safety of deep foundation pit and revealed a reliability index ( β ) of 0.44 in an actual case, suggesting a hazardous condition. Based on the reliability index β , emergency measures were promptly taken. Compared to traditional reliability methods, the approach presented in this paper takes into account the dependence among monitoring indicators, which is more aligned with actual engineering conditions and holds significant reference value for the safety assessment of underground engineering structures.

Keywords: deep foundation pit; construction phase; pair-copula Bayesian model; risk assessment; reliability analysis (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/12/24/3961/pdf (application/pdf)
https://www.mdpi.com/2227-7390/12/24/3961/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:12:y:2024:i:24:p:3961-:d:1545650

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().