Tailings Dams Failures: Updated Statistical Model for Discharge Volume and Runout
AbstractThis paper presents a statistical model to estimate the volume of released tailings (VF) and the maximum distance travelled by the tailings (Dmax) in the event of a tailings dam failure, based on physical parameters of the dams. The dataset of historical tailings dam failures is updated from the one used by Rico et al., (Floods from tailings dam failures, Journal of Hazardous Materials, 154 (1) (2008) 79–87) for their regression model. It includes events out of the range of the dams contained in the previous dataset. A new linear regression model for the calculation of Dmax, which considers the potential energy associated with the released volume is proposed. A reduction in the uncertainty in the estimation of Dmax when large tailings dam failures are evaluated, is demonstrated. Since site conditions vary significantly it is important to directly consider the uncertainty associated with such predictions, rather than directly using these types of regression equations. Here, we formally quantify the uncertainty distribution for the conditional estimation of VF and Dmax, given tailings dam attributes, and advocate its use to better represent the tailings dam failure data and to characterize the risk associated with a potential failure. View Full-Text
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Description: App to calculate Dmax and VF
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Concha Larrauri, P.; Lall, U. Tailings Dams Failures: Updated Statistical Model for Discharge Volume and Runout. Environments 2018, 5, 28.
Concha Larrauri P, Lall U. Tailings Dams Failures: Updated Statistical Model for Discharge Volume and Runout. Environments. 2018; 5(2):28.Chicago/Turabian Style
Concha Larrauri, Paulina; Lall, Upmanu. 2018. "Tailings Dams Failures: Updated Statistical Model for Discharge Volume and Runout." Environments 5, no. 2: 28.
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