Join SRK's Senior Geotechnical Engineer, Ignacio Vernengo as he discusses using Bayesian statistics to obtain a more meaningful estimation of shear strength based on available data and prior knowledge of the parameters.
Day 1 | Session 2a
Abstract
This paper covers the estimation of shear strength parameter values for input into slope stability analysis of tailings storage facilities.
The paper describes the current industry practice of selecting a single (sometimes arbitrary) conservative value for each parameter and proposes to use Bayesian statistics to obtain a meaningful probabilistic evaluation of the strength envelope based on the available data and knowledge of the parameters.
The concept of prediction intervals was used to define the strength parameters with selected levels of confidence for the analysis. The paper describes the advantages of the Bayesian approach, including mainly the quantification of uncertainty, traceability of the results, incorporation of prior knowledge and update with new information. The paper uses data from a real project to show the shear strength parameter estimation results for both methods and undertakes a 2D limit equilibrium slope stability analysis, highlighting the differences in the results obtained.
The authors believe that the proposed method is robust and systematic and aligns with the risk approach to tailings management proposed by the Global Industry Standard on Tailings Management (GISTM). The use of the proposed Bayesian approach provides the required inputs to estimate the probability of failure for an embankment, which is considered a preferred outcome when compared with a factor of safety, as it is usually the practice in the industry. A discussion including further work and the potential to use these techniques in other areas of tailings design and operation is also provided.
Authors:
- I. Vernengo Lezica
- L.F. Contreras
