Multi-fidelity approach for the probabilistic assessment of dams

The proposed project seeks to evaluate the stability of concrete hydraulic structures using a progressive method that balances precision and computational expenses. By examining various simplification assumptions and analyzing different loading conditions, while incorporating machine learning techniques to merge data with different levels of accuracy, the project aims to enhance the evaluation of risks associated with hydraulic structures, facilitating better decision-making. Partnering with Hydro-Québec, a leading provider of renewable energy, the project will benefit the organization by enhancing safety assessments, optimizing resource management, and enabling proactive maintenance. Furthermore, by ensuring the stability of hydropower generation, the project contributes to Canada’s sustainability targets, reducing dependence on fossil fuels and minimizing CO2 emissions, which supports the nation’s commitment to fortify and sustain critical infrastructure in the long run.

Faculty Supervisor:

Patrick Paultre

Student:

Partner:

Hydro-Quebec

Discipline:

Engineering

Sector:

Energy and Utilities; Environmental Science and Technology; Water

University:

Université de Sherbrooke

Program: