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• W4385665615 abstract "The difficulty in determining the rheological characteristics of tailings inside reservoirs as well as their intrinsic variability adds uncertainty to tailings dam failures in flood studies. Uncertainty propagation in non-Newtonian hydrodynamic models stands as a great scientific challenge. This article explores the sensibility of tailings dam breach flood mapping to rheological parameters in Bingham and Herschel-Bulkley (H-B) models. The developed approach was based on the probabilistic Latin Hypercube Sampling of rheological parameters. It was automated to propagate uncertainty throughout multiple hydrodynamic simulations using the HEC-RAS v.6.1 software. Rheological parameter ranges and distributions were based on a broad bibliographic review. Bingham models were revealed to be more sensitive than H-B in terms of simulated min-max area values: for Bingham, flood areas, maximum depths, and arrival times varied by 17.9%, 9.3%, and 8.2%, respectively; for H-B, variations were 25.7%, 5.1%, and 3.9%. However, Bingham was less sensitive in terms of hydrodynamically associated probability: high probability ratios were related to a small range of simulated areas in Bingham, while H-B presented great variability. Finally, for each model, the parameters that affect uncertainty the most were identified, reinforcing the importance of determining them properly. Furthermore, the identified parameter ranges for both models should be valuable for defining variable value boundaries for flood sensitivity tests on specific tailings materials for other case studies. The automated algorithm can be used or adapted for specific tests with other hydrodynamic simulations." @default.
• W4385665615 created "2023-08-09" @default.
• W4385665615 creator A5002852013 @default.
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• W4385665615 date "2023-08-08" @default.
• W4385665615 modified "2023-10-16" @default.
• W4385665615 title "Probabilistic Analysis of Floods from Tailings Dam Failures: A Method to Analyze the Impact of Rheological Parameters on the HEC-RAS Bingham and Herschel-Bulkley Models" @default.
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• W4385665615 doi "https://doi.org/10.3390/w15162866" @default.
• W4385665615 hasPublicationYear "2023" @default.
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