Dual layer metamodel-based safety assessment for rock wedge stability of a free-crested weir. (1st October 2022)

• Record Type: Journal Article
• Authors: Segura, Rocio L.; Fréchette, Valérie; Miquel, Benjamin; Paultre, Patrick
• Is Part Of: Engineering structures. Volume 268(2022)
• Publication Date: 2022-10-01
• Subjects: Metamodel -- Foundation stability -- Wedge analysis -- Probabilistic analysis -- Free-crested weir -- Safety assessment; Structural engineering -- Periodicals; Structural analysis (Engineering) -- Periodicals; Construction, Technique de la -- Périodiques; Génie parasismique -- Périodiques; Pression du vent -- Périodiques; Earthquake engineering; Structural engineering; Wind-pressure; Periodicals; 624.105
• DOI: 10.1016/j.engstruct.2022.114691
• Languages: English
• ISSNs: 0141-0296

Abstract

Abstract: A key problem in gravity dams is providing sufficient stability to prevent sliding, and the difficulty increases with the number of weak structural planes in the dam foundation. Probabilistic methods allow different loading, material and geometric configurations to be considered, constituting the basis of more adequate design and assessment procedures. Metamodels drastically reduce the need for simulation runs, thereby decreasing the time and effort needed to simulate the structural response when analyzing a wide variety of dam-system scenarios. In this paper, a fragility-based safety assessment of a free-crested weir with respect to its rock foundation stability is performed using a dual-layer metamodel. The first layer emulates and replaces the continuous output of the software and allows the safety factor to be predicted, while the second layer provides the probability of not reaching this safety factor by generating parameterized multivariate fragility functions. To explicitly account for the effects of parameter uncertainties, multidimensional integration is implemented to update the fragility functions. Accordingly, recommendations can be formulated concerning the conditioning parameter's minimum values to achieve the expected performance when additional information regarding the remaining parameters is acquired. The results show that improving the knowledge of the loading (seismic and reservoir) parameters reduces the uncertainties in parameters such as cohesion to meet the safety factor requirements. Highlights: Fragility-based safety assessment of a free-crested weir using a dual-layer metamodel. The first layer emulates and replaces the continuous output of the software. The second layer provides the probability of exceeding a safety factor by generating parameterized multivariate fragility functions. Minimum values recommendations are formulated to achieve the expected performance when additional information is acquired. Improving the knowledge of the loading (seismic and reservoir) parameters reduces the uncertainties to meet the safety factor requirements.