A CFD-BASED MICROSCOPIC-TO-MACROSCOPIC STUDY OF SUPERCOOLED LARGE DROPLETS FOR IN-FLIGHT ICING

飞行中结冰是一个航空安全问题，正在进行广泛的研究以减轻其风险。申请人花了15年时间来了解飞行中积冰的物理学和设计最佳防冰系统。因此，他的综合3D计算系统FENSAP-ICE在21个国家使用，从航空航天的角度来看，几乎是全世界。目前的挑战是保护飞机免受过冷大液滴（SLD）的影响，其尺寸范围从100微米到高达1000微米（铅笔尖的大小）。当云中的这种重液滴击中飞机时，它们可能会反弹，破碎并将过多的较小液滴溅回气流中，然后可以在下游未受保护的飞机表面上沉积和冻结，严重降低空气动力学性能。关于水滴飞溅和从高速飞机表面反弹的实验数据很少，因为结冰隧道很难复制SLD，以高速发射它们并使它们到达测试段而不会因重力而沉降。这项发现资助的重点是通过首先开发基于分析的双管齐下的微观描述，通过水平集和光滑粒子流体力学方法，以飞行速度撞击固体和/或液体表面的单个液滴，来克服这些缺点。然后，这些微观方法将提供一个模型，嵌入到反弹液滴的宏观3D欧拉CFD跟踪中，允许对SLD对特定飞机构成的危险进行无与伦比的详细物理评估，而不是来自实验的通用数据。 然后，我们将继续开发降阶建模技术，以数学方式混合来自计算和自然结冰测试的数据，并为SLD结冰中的飞机认证提供无与伦比的质量数据库。进一步将该数据库与实时气象数据相结合，可以导致机载SLD危险警报，以延迟或取消起飞和降落，及时警告退出云层，或避免在机场周围等待。 短期目标是开发-验证-验证所提出的模型;而长期目标是继续我们作为先驱和领导者的成功追求，在结冰合规和认证过程中为计算模拟发挥主导作用;提高航空安全。 该补助金是培养高素质人才的沃土，具有应用数学，物理学，计算科学和现实生活中的工程应用经验的明智组合，他们将继续在加拿大具有战略重要性的领域发挥重要的学术和工业作用。

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.