Reliability Analysis of Embankment Dams
S. Lacasse, Farrokh Nadim, Zhicheng Liu, Unni K. Eidsvig
Abstract
S. Lacasse, Farrokh Nadim, Zhicheng Liu, Unni K. Eidsvig
Abstract
The reliability analyses of one rockfill embankment dam in Norway are presented. The event tree analysis and the Bayesian network approaches, the latter combined with Monte Carlo simulations, were used to obtain the annual probability of dam breach. The analyses were run partly in a workshop format, as a process to reach consensus among several experts on the parameters to consider in the calculation of probabilities. The analyses illustrate that the reliability analyses enabled the identification of an unexpected mode of failure and later quantified the effect of rehabilitation measures on the estimated probability of dam breach.
OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
The reliability analyses of one rockfill embankment dam in Norway are presented. The event tree analysis and the Bayesian network approaches, the latter combined with Monte Carlo simulations, were used to obtain the annual probability of dam breach. The analyses were run partly in a workshop format, as a process to reach consensus among several experts on the parameters to consider in the calculation of probabilities. The analyses illustrate that the reliability analyses enabled the identification of an unexpected mode of failure and later quantified the effect of rehabilitation measures on the estimated probability of dam breach.
Key concepts: Reliability (semiconductor), Bayesian network, Embankment dam, Levee, Monte Carlo method, Reliability engineering, Law of total probability, Event tree