过冷大水滴粒径分布的欧拉-拉格朗日混合抽样算法及对冰型影响

过冷大水滴（supercooled large droplet，SLD）云雾环境不同于常规粒径范围的过冷水滴，具有更大的粒径范围和复杂的水滴粒径分布形式，使得结冰的冰型异常复杂，从而给飞行器的飞行安全带来了前所未有的挑战。现有结冰数值模拟方法仅能模拟单一粒径的水滴，无法准确模拟真实SLD云雾环境“双峰分布”的粒径分布特性和相应的冰型。为了准确高效模拟SLD这种粒径分布特性，本文提出了一种基于Rosin-Rammler 分布函数进行欧拉-拉格朗日混合抽样的水滴轨迹模拟算法。通过该方法收集水滴，再利用结冰模型与水膜模型计算表面溢流传热和冰高，从而实现了准确高效的SLD粒径分布的结冰数值模拟，并通过2.5维算例研究了SLD粒径分布对机翼结冰的冰型特征以及冰型空间随机性的影响。结果表明SLD的粒径分布对冰型有较大的影响，冰型特征和冰型随机性与MVD和粒径分布方差紧密关联。

Eulerian-Lagrangian Sampling Method of SLD Droplet Size Distribution and its Influence on Ice Shapes

The supercooled large droplet (SLD) environments are sharply different from those of traditional supercooled droplets with small sizes, lying in the fact that the SLD environment has a wider range of droplet sizes and complex droplet size distribution forms, which makes ice shapes complex and has brought an unprecedented challenge to airline safety. The existing numerical icing simulation methods can only simulate traces of single-size droplets, lacking the ability to simulate traces of the bimodal droplet size distributions and the corresponding ice shapes in the SLD environment precisely. In order to simulate the characteristics of the SLD droplet size distributions precisely and efficiently, a mixed Eulerian-Lagrangian sampling method based on Rosin-Rammler distribution function was proposed. Water droplets were collected via this method, and heat transfer and ice accretion were calculated with the icing model and the water film model, through which a precise and efficient numerical icing simulation of the SLD droplet size distributions was realized. Furthermore, research was done via 2.5D cases on the impact of the SLD droplet size distributions on ice shape characteristics and ice shape spatial randomness. The results show that droplet size distributions do affect ice shapes, and ice shape characteristics and ice shape randomness are closely related to the MVD and the distribution variance.