Dimension-reduction of spatial outputs within an uncertainty quantification framework: application to tailings dam-breach flow studies

• Grant number: 23/08472-0
• Support Opportunities: Scholarships abroad - Research Internship - Doctorate
• Start date: October 01, 2023
• End date: September 27, 2024
• Field of knowledge: Engineering - Civil Engineering - Hydraulic Engineering
• Principal Investigator: Geraldo de Freitas Maciel
• Grantee: Yuri Taglieri Sáo
• Supervisor: Pascal Noble
• Host Institution: Faculdade de Engenharia (FEIS). Universidade Estadual Paulista (UNESP). Campus de Ilha Solteira. Ilha Solteira , SP, Brazil
• Institution abroad: Institut National des Sciences Appliquées de Toulouse (INSA Toulouse), France
• Associated to the scholarship: 22/05184-1 - Probabilistic approach in tailings dam break studies aiming the definition of a consistent methodology, BP.DR

Abstract

Tailing dams are structures susceptible to failure and present extraordinary risks to public safety and environment. Given those risks and the recent disasters in Mount Polley (Canada - 2014), Mariana (Brazil - 2015) and Brumadinho (Brazil - 2019), numerical analyses of hypothetical dam breaches over complex terrains must be carried out to estimate inundation and deposition areas of tailings, flow velocities and arrival times at locations of interest. There are still no standardized and specific methodologies for these studies, beyond the fact that non-Newtonian physical characteristics of tailings introduce significant uncertainties to the analysis (e.g. released volume, breach hydrograph and tailings rheology). The lack of a standardized methodology along with the uncertainty produced by tailings physical properties converge to the application of a probabilistic approach to assess dam-breach tailings flows. In this context, the general objective of the main Ph. D. thesis project is to propose a deterministic numerical methodology based on the solution of Shallow-Water Equations for non-Newtonian fluids and focused on the Uncertainty Quantification and the Global Sensitivity Analysis of input parameters over output variables through probabilistic modeling. To improve the contributions of the main Ph. D. thesis project, this current proposal aims to present a research internship project to be carried out at the Institut National des Sciences Appliquées (INSA), more specifically at the Institut de Mathématiques de Toulouse (IMT), France, with the support of the Research Internship Abroad (RIA - BEPE). The proposed activities will guide two complementary frameworks: 1) the deterministic framework, to solve numerically the Shallow-Water Equations over a complex terrain; and 2) the Uncertainty Quantification and probabilistic frameworks to carry out procedures of surrogate modelling and Global Sensitivity Analysis focused on spatial outputs. The mentioned competencies are worked by INSA professors/researchers involved in the project, under the coordination of Prof. Pascal Noble. (AU)