Uncertainty Tracking and Geotechnical Reliability Updating Using Bayesian Networks

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Bayesian networks are proposed as a tool to integrate reliability and influential variables relating to the slope stability of an idealized embankment. The site investigation (extent) and slope geometry, as well as the material properties and their spatial variability, are considered within a Bayesian network. The random finite element method (RFEM) is used to quantify the slope reliability and demonstrate the overall methodology. Prior probabilities of geometry, material parameters and their heterogeneity are obtained from ‘initial’ site investigation data. Probabilistic distributions of slope performance (factor of safety) are obtained by Bayesian inference in the network to investigate the impact of additional site investigation. The amount of additional site investigation required to increase the geotechnical reliability is assessed. This work illustrates the applicability of Bayesian networks as an effective reliability and uncertainty assessment tool that can aid decision making for site investigation and during maintenance, where new observations can be readily integrated to obtain updated reliability estimates.
Original languageEnglish
Title of host publicationProceedings of the 7th International Symposium on Geotechnical Safety and Risk (ISGSR 2019)
Subtitle of host publicationState-of-the-Practice in Geotechnical Safety and Risk
EditorsJianye Ching, Dian-Qing Li, Jie Zhang
Place of PublicationTaipei, Taiwan
Number of pages6
ISBN (Electronic)978-981-11-2725-0
Publication statusPublished - 2019
EventISGSR 2019: 7th International Symposium on Geotechnical Safety and Risk - National Taiwan University of Science and Technology, Taipei, Taiwan
Duration: 11 Dec 201913 Dec 2019


ConferenceISGSR 2019: 7th International Symposium on Geotechnical Safety and Risk
Abbreviated titleISGSR 2019
Internet address

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.


  • Bayesian network
  • geotechnical reliability
  • random fields
  • slope reliability
  • spatial variability
  • uncertainty


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