Grant: Canada Research Chairs

Climate change is one of the most critical issues of our time. To mitigate its consequences, several solutions are suggested central to which, is the successful production of clean or low-emission electricity. In Canada, nuclear energy has been contributing significantly to producing reliable low-emission energy. More than 15% of energy in Canada and 50% in Ontario has been produced through CANada Deuterium Uranium (CANDU) nuclear reactors. To meet climate targets, the international energy agency has projected that in the next 20 years we will need to double our energy production through nuclear. This is translated to the refurbishment of current CANDU reactors and the deployment of a new Small Modular Reactor for installation at the Darlington nuclear site in Ontario. The lifespan of these reactors and their availability for producing energy are significantly affected by the performance of the materials used in the core of the reactors. Hence, ensuring the safe and sustainable operation of nuclear reactors requires the development of advanced predictive materials models that are validated against robust data sets through comprehensive experimentation. This program focuses on the development of novel and advanced multiphysics numerical models that simulate the performance of the metals and alloys used in the core of nuclear reactors. For the first time, multiscale, microstructure-sensitive damage models will be coupled with irradiation and environmental induced degradation mechanisms to simulate under what circumstances reactor materials might fail. In collaboration with world-leading international laboratories, advanced experimental methods will be developed and employed to validate the numerical models. The models will further be used to tailor optimized materials microstructures for designing critical engineering components that will be used in other low-emission energy sectors. It is expected that this program will contribute significantly to ensuring the safe operation of nuclear reactors, reduce the cost of excessive experimentation in industry by developing accurate predictive models, and enhance equity and diversity in the energy sector through training a diverse group of highly qualified personnel.