Subventions et des contributions :

Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2022-2023)

In-flight icing is an aviation safety concern under extensive research to mitigate its risks. The applicant has devoted 15 years to the understanding of the physics of in-flight ice accretion and the design of optimal ice protection systems. As a result, his comprehensive 3D computational system, FENSAP-ICE, is in use in 21 countries, literally worldwide in terms of aerospace. A current challenge is to protect aircraft against Supercooled Large Droplets (SLD), whose sizes range from 100 to as high as 1000 microns (the size of the tip of a lead pencil). When such heavy droplets in a cloud hit an aircraft, they may bounce, shatter and splash back a plethora of smaller droplets into the airflow that can then depose and freeze on downstream unprotected aircraft surfaces, severely degrading aerodynamic performance. Little experimental data exists for droplets' splashing and bouncing off high speed aircraft surfaces, because icing tunnels have difficulties reproducing SLD, launching them at high speeds and getting them to reach the test section without settling due to gravity. The focus of this Discovery Grant is to circumvent these shortcomings by first developing an analytically-based two-pronged microscopic description of individual droplets impacting on solid and/or liquid surfaces, at flight speeds, via Level Set and Smoothed-Particle Hydrodynamics Methods. These microscopic approaches will then provide a model to be embedded into a macroscopic 3D Eulerian CFD tracking of bounced droplets, permitting an unparalleled detailed physics-based assessment of the dangers posed by SLD to a specific aircraft, as opposed to the generic data from experiments.

We will then continue our development of Reduced Order Modeling techniques to mathematically blend data from Computational and natural icing testing and produce a database of unmatched quality for the certification of aircraft in SLD icing. Further combining this database with real-time meteorological data can lead to an onboard SLD hazard alert to delay or cancel takeoff and landing, timely warn to exit from a cloud, or avoid holding around an airport.

The short-term objective is to develop-verify-validate the proposed models; while the long-term objective is to continue our successful quest, as pioneers and leaders, in carving a predominant role for computational simulation within icing compliance and certification processes; increasing aviation safety.

This grant is a fertile ground to cultivate Highly Qualified Personnel, with a judicious mix of applied mathematics, physics, computational sciences and real-life engineering applications experience, who will continue playing important academic and industrial roles in areas of strategic importance to Canada.