Ering, Pinom and Sivakumar Babu, GL (2017) A Bayesian framework for updating model parameters while considering spatial variability. In: Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards, 11 (4). pp. 285-298. ISSN 1749-9518
Full text not available from this repository.Abstract
The study presents a recent slope failure in India which resulted in the burial of a village and claimed large number of lives. Current methods of probabilistic back analysis incorporate uncertainty in the analysis but do not consider spatial variability. In this study, back analysis is performed using Bayesian analysis in conjunction with random field theory. The probabilistic method is shown to be efficient in back-analysing a slope failure. It also provides confidence in parameter values to be used for post-failure slope design. The back analysis method which does not consider spatial variability overestimates the uncertainty in analysis, which can lead to uneconomical slope remediation design and measures.
| Item Type: | Journal Article |
|---|---|
| Publication: | Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards |
| Publisher: | Taylor and Francis Ltd. |
| Additional Information: | The copyright for this article belongs to the Taylor and Francis Ltd. |
| Keywords: | Back analysis; Bayesian analysis; probability; random field; slope remedial design; spatial variability |
| Department/Centre: | Division of Mechanical Sciences > Civil Engineering |
| Date Deposited: | 02 Jun 2022 06:06 |
| Last Modified: | 02 Jun 2022 06:06 |
| URI: | https://eprints.iisc.ac.in/id/eprint/73039 |
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