Use of AI to speed up numerical simulations: application to the design of superconducting tapes for energy and medicine domains

Superconducting tapes are used in superconducting high-power devices, such as cables, fault current limiters, transformers, and superconducting machines such as motors or generators. They are also used in coils for magnetic-field generation, such as high magnetic field for fundamental research, proton therapy or fusion power. This project focusses on the development of numerical tools based on artificial intelligence to emulate 2-D and 3-D partial differential-equations solvers in the time domain and to apply these techniques to thin-film multilayer structures with nonlinear properties, such as superconducting tapes, in order to decrease the computation time with the end goal of designing the best superconducting-tape architecture considering variations in tape properties at the millimetre scale. Polytechnique Montréal will provide expertise in materials science and modelling and the National Research Council will provide expertise in AI and machine learning for simulation.

Project team

Prof. Frédéric Sirois

Dr. Frédéric Sirois is a full professor at Polytechnique Montréal. He has published over 100 scientific articles to date. His main research interests are the characterization and modelling of electric and magnetic properties of materials, modelling and design of electromagnetic and superconducting devices, and integration studies of superconducting equipment in power systems. He is one of the founders of the Superconductivity and Magnetism Laboratory, and he is also a member of the Regroupement québécois sur les matériaux de pointe (RQMP).

Find out more about Dr. Sirois.

Dr. Christian Lacroix

Dr. Christian Lacroix is a research associate at Polytechnique de Montréal. He is an expert in the characterization and modelling of electric and magnetic properties of materials. His main research interests include superconducting materials for high-power applications, magnetization dynamics in ferromagnetic materials, and light-matter interaction.

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Dr. Julio Valdés

Dr. Julio Valdés is senior research officer at the National Research Council Canada (Digital Technologies Research Centre, Data Science for Complex Systems Team). His topics of interest are data analytics, machine learning, computational intelligence, pattern recognition, digital image and signal processing and data visualization. His application areas cover multidisciplinary research in biology, medicine, civil and aerospace engineering, and earth, environmental and space sciences. He is a senior member of the IEEE and co-chair of the IEEE Computational Intelligence Society Task Force on Computational Intelligence in Earth and Environmental Sciences. He is also co-chair of the INNS Special Interest Group on the same topic. He is adjunct professor at the universities of Ottawa and Carleton. His record includes more than 270 publications in books, journals, conference papers and technical reports.

Dr. Alain Tchagang

Dr. Alain Tchagang is a research officer with the National Research Council. He has a wealth of research experience combining state-of-the-art methods in statistical signal processing and machine learning to tackle novel and challenging problems in life science, physics and engineering.

Find out more about Dr. Tchagang and his other projects.