The Influence of Gravity and Mass Loading on the Coalescence of Aerodynamically Interacting Droplets in Homogeneous Isotropic Turbulence

IF 3 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Journal of the Atmospheric Sciences Pub Date : 2023-09-01 DOI:10.1175/jas-d-22-0267.1
Antoine Michel, Ahmad Ababaei, Bogdan Rosa
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Abstract

Abstract The collision–coalescence of cloud droplets in atmospheric turbulent flow is analyzed numerically using direct numerical simulation coupled to a Lagrangian particle tracking. The droplet aerodynamic interactions (AI) are represented for employing two complementary approaches. For large separations, the interaction forces are evaluated by the superposition of Stokes disturbance velocities generated by moving particles. When the distance between droplets is comparable to their mean radii, lubrication forces are additionally considered. Simulation results show that without gravitational acceleration, aerodynamic interactions decrease the kinetics of the coalescence process but do not significantly impact the size spectrum broadening. The influence of AI on the coalescence kinetics is more complex in the presence of gravity and depends on the mass loading and on droplet inertia. Long-range aerodynamic interactions reduce the coalescences in dilute suspensions but increase the collision rate in dense suspensions of high-inertia droplets. In contrast, lubrication forces decrease the collision rate regardless of the mass loading. The collision efficiency induced by aerodynamic interactions additionally is influenced by the radius ratio of colliding droplets and the mechanisms leading to raindrops formation and growth. In cloud-like conditions, both long- and short-range AI decrease the fraction of raindrops created by collisions between droplets (autoconversion) while promoting raindrops growth by accretion (collection by settling drops). In turn, aerodynamic interactions favor the growth of a limited number of droplets and promote the broadening of the droplet size spectrum. This effect is stronger in dilute suspensions of weakly inertial droplets, corresponding to the flow properties encountered in developing precipitation.
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重力和质量载荷对均匀各向同性湍流中相互作用的液滴聚并的影响
摘要采用直接数值模拟和拉格朗日粒子跟踪相结合的方法,对大气湍流中云滴碰撞合并过程进行了数值分析。液滴气动相互作用(AI)采用两种互补的方法表示。对于大的分离,相互作用力由运动粒子产生的斯托克斯扰动速度的叠加来评估。当液滴之间的距离与其平均半径相当时,还要考虑润滑力。模拟结果表明,在没有重力加速度的情况下,气动相互作用降低了聚结过程的动力学,但对尺寸谱展宽没有显著影响。在重力存在的情况下,人工智能对聚结动力学的影响更为复杂,并且取决于质量载荷和液滴惯性。远程空气动力相互作用减少了稀悬液中的聚结,但增加了高惯性液滴稠密悬液中的碰撞率。相反,无论质量载荷如何,润滑力都会降低碰撞率。此外,碰撞液滴的半径比以及雨滴形成和生长的机理也影响着气动相互作用引起的碰撞效率。在类似云的条件下,远程和短程人工智能都减少了水滴之间碰撞(自动转换)产生的雨滴的比例,同时通过积聚(沉淀水滴收集)促进雨滴的增长。反过来,气动相互作用有利于有限数量液滴的生长,并促进液滴尺寸谱的拓宽。这种效应在弱惯性液滴的稀悬浮液中更强,与发展中降水遇到的流动特性相对应。
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来源期刊
Journal of the Atmospheric Sciences
Journal of the Atmospheric Sciences 地学-气象与大气科学
CiteScore
0.20
自引率
22.60%
发文量
196
审稿时长
3-6 weeks
期刊介绍: The Journal of the Atmospheric Sciences (JAS) publishes basic research related to the physics, dynamics, and chemistry of the atmosphere of Earth and other planets, with emphasis on the quantitative and deductive aspects of the subject. The links provide detailed information for readers, authors, reviewers, and those who wish to submit a manuscript for consideration.
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