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Word cloudA word cloud is a visual representation of the most frequently used words in a text or a set of texts. The words appear in different sizes, with the size of each word being proportional to its frequency of occurrence in the text. The more frequently a word is used, the larger it appears in the word cloud. This technique allows for a quick visualization of the most important themes and concepts in a text.
In the context of this page, the word cloud was generated from the publications of the author {}. The words in this cloud come from the titles, abstracts, and keywords of the author's articles and research papers. By analyzing this word cloud, you can get an overview of the most recurring and significant topics and research areas in the author's work.
The word cloud is a useful tool for identifying trends and main themes in a corpus of texts, thus facilitating the understanding and analysis of content in a visual and intuitive way.
Blanchet, M., Zayni, M. K., & Laurendeau, É. (2024, July). Contribution to IPW2 by Studying Single and Multi-Layer Icing in 2D, 2.5D and 3D [Paper]. 2024 AIAA Aviation Forum and Ascend, Las Vegas, Nevada, USA. External link
Blanchet, M., Bourgault-Côté, S., & Laurendeau, É. (2023, June). Advancements in CHAMPS for Multi-Layer Ice Accretion on Aircraft [Paper]. SAE International Conference on Icing of Aircraft, Engines, and Structures (ICE 2023), Vienna, Austria. External link
Blanchet, M. (2022). Modeling of Transitional Flows on Roughened Surfaces for Icing Applications [Master's thesis, Polytechnique Montréal]. Available
Bilodeau-Bérubé, C., Blanchet, M., & Laurendeau, É. (2022, June). Comparison of a correlation-based transitional model coupled to SA and kw-SST turbulence models [Paper]. AIAA AVIATION 2022 Forum, Chicago, Illinois, USA. External link
Blanchet, M., Bourgault-Côté, S., & Laurendeau, É. (2022, June). Conservative hyperbolic droplet solver for aircraft icing [Paper]. AIAA AVIATION 2022 Forum, Chicago, Illinois, USA. External link
Bourgault-Côté, S., Papillon Laroche, H., Blanchet, M., & Laurendeau, É. (2022, June). Contribution to IPW1 by studying multi-layer icing convergence in 2D/2.5D [Paper]. AIAA AVIATION 2022 Forum, Chicago, Illinois, USA. External link
Laurendeau, É., Blanchet, M., Zayni, M. K., Hann, R., Radenac, E., Mussa, I., & Pueyo, A. (2024, July). Summary From the 2nd AIAA Ice Prediction Workshop [Paper]. 2nd AIAA Ice Prediction Workshop, Las Vegas, Nevada. External link
Zayni, M. K., Blanchet, M., & Laurendeau, É. (2024, July). Lagrangian Particle Tracking for Ice Accretion Applications [Paper]. 2024 AIAA Aviation Forum and Ascend, Las Vegas, Nevada, USA. External link
Zayni, M. K., Blanchet, M., & Laurendeau, É. (2023, May). Recent developments of the multi-physics solver champs-ice [Paper]. Canadian Society for Mechanical Engineering (CSME) / Computational Fluid Dynamics Society of Canada (CFD Canada). International congress, Sherbrooke, Qc, Canada (6 pages). Published in Progress in Canadian Mechanical Engineering, 6. External link
Zayni, M. K., Blanchet, M., & Laurendeau, É. (2023, May). Recent developments of the multi-physics solver champs-ice [Paper]. Canadian Society for Mechanical Engineering International Congress (CSME 2023) & Computational Fluid Dynamics Canada International Congress (CFD 2023), Sherbrooke, Qc, Canada (6 pages). External link
