Probabilistic analysis of geosynthetic-reinforced and pile-supported embankments

Xiangfeng Guo, Tuan A. Pham, Daniel Dias

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

This paper presents a probabilistic analysis of a geosynthetics-reinforced and pile-supported (GRPS) embankment by using reliability, sensitivity and uncertainty propagation techniques. Compared to the traditional deterministic evaluation methods, the analyses performed in this work allow designers to rationally consider the uncertainties of material properties and quantify their influences on the embankment performance. Additionally, complementary information/results could be obtained which enables an informed design decision for engineers. This feature is further enhanced in the paper by proposing a new analysis procedure in which four carefully selected probabilistic techniques are combined with an efficient deterministic model. The contribution of the proposed procedure lies in providing a variety of valuable results (e.g., failure probability and sensitivity index) related to the GRPS embankment performance but with a limited computational time. An application of the procedure is presented in the paper. The obtained results revealed that the studied GRPS embankments have relatively low failure probabilities considering a usual traffic loading but could be risky under extreme loading conditions. Based on the sensitivity analysis, all the random parameters are ranked according to their quantified importance. Some discussions are also provided, trying to link the procedure with practical designs and to explain the uncertainty modeling with more details.

Original languageEnglish
Article number104595
JournalComputers and Geotechnics
Volume142
Early online date15 Dec 2021
DOIs
Publication statusE-pub ahead of print - 15 Dec 2021

Keywords

  • Geosynthetics
  • Piled embankment
  • Probabilistic analysis
  • Reliability analysis
  • Sensitivity analysis
  • Uncertainty propagation

ASJC Scopus subject areas

  • Geotechnical Engineering and Engineering Geology
  • Computer Science Applications

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