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Barbeau, L., Étienne, S., Béguin, C., & Blais, B. (2024). Solid–fluid force modeling: insights from comparing a reduced order model for a pair of particles with resolved CFD-DEM. International Journal of Multiphase Flow, 178, 104882 (23 pages). Disponible
Barbeau, L., Golshan, S., Deng, J., Étienne, S., Béguin, C., & Blais, B. (2024). High-order moving immersed boundary and its application to a resolved CFD-DEM model. Computers & Fluids, 268, 106094 (14 pages). Lien externe
Barbeau, L., Étienne, S., Béguin, C., & Blais, B. (2024). Solid–fluid force modeling: Insights from comparing a reduced order model for a pair of particles with resolved CFD-DEM. International Journal of Multiphase Flow, 178, 104882 (23 pages). Lien externe
Bibeau, V., Barbeau, L., Boffito, D. C., & Blais, B. (2023). Artificial neural network to predict the power number of agitated tanks fed by CFD simulations. Canadian Journal of Chemical Engineering, 101(10), 5992-6002. Disponible
Barbeau, L., Étienne, S., Béguin, C., & Blais, B. (2022). Development of a high-order continuous Galerkin sharp-interface immersed boundary method and its application to incompressible flow problems. Computers & Fluids, 239, 13 pages. Lien externe
Blais, B., Barbeau, L., Bibeau, V., Gauvin, S., Geitani, T. E., Golshan, S., Kamble, R., Mikahori, G., & Chaouki, J. (2020). Lethe: An open-source parallel high-order adaptative CFD solver for incompressible flows. SoftwareX, 12, 9 pages. Lien externe
Barbeau, L. (2024). Vers une approche CFD-DEM résolue d'ordre élevé pour la simulation directe d'écoulements autour d'essaims de particules [Thèse de doctorat, Polytechnique Montréal]. Accès restreint
