Near-contact motion and coalescence of inertial droplets in turbulence: simulations, laboratory experiments and field measurements

湍流中惯性液滴的近接触运动和合并：模拟、实验室实验和现场测量

• 批准号: 1605195
• 负责人: Gregory Bewley
• 金额: $ 40万
• 依托单位: Cornell University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-08-01 至 2021-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1605195&HistoricalAwards=false
• 关键词: Near; contact; motion; coalescence; inertial

PI: Collins, LanceProposal Number: 1605195A comprehensive research approach, involving high fidelity computations, experiments in a laboratory and field experiments is proposed to understand and predict the behavior of drops suspended in turbulent flows. This problem is very important for the behavior of clouds in the atmosphere. In addition to atmospheric applications, there are many other application areas with engineering interest, where this work can have an impact, including diesel engines, sprays, atomization, and powder manufacturing and inhalation drug therapy. Despite more than a half-century of research, there remains considerable uncertainty on how turbulence enhances the coalescence rate of suspended droplets. This study addresses that uncertainty through the direct measurement of droplet collision/coalescence rates in direct numerical simulations (DNS), experiments and in field measurements over a wide range of conditions. The focus of the study will be on the direct measurement of coalescence rates of droplets driven by turbulence. This has application to a wide range of multiphase flows, but the application of primary importance to this proposal is the processing of clouds in the atmosphere. Under certain conditions, clouds evolve faster than microphysical models can predict. It is believed that atmospheric turbulence could explain the acceleration of cloud formation. This study will bring together a synergistic combination of three scientific tools for analyzing natural turbulent flow phenomena: DNS; laboratory experiments; and field measurements. The overarching goal is to generate definitive coalescence data from high-resolution DNS and state-of-the-art laboratory and field experiments under conditions of near parametric similarity. This investigation will include the first experimental measurements of the coalescence rate for inertial droplets in a turbulent flow field, both in the laboratory and in natural conditions. Only with this collective effort can this be achieved - any one or two of these techniques alone will not sufficient. In addition to the engineering impacts of the proposed work, the proposed activities include educational and outreach activities that are targeted towards encouraging underrepresented minorities into the academy.

PI: Collins， LanceProposal Number: 1605195A综合研究方法，包括高保真计算，实验室实验和现场实验，以了解和预测悬浮在湍流中的液滴的行为。这个问题对大气中云的行为是非常重要的。除了大气应用之外，还有许多其他具有工程兴趣的应用领域，其中包括柴油发动机，喷雾，雾化，粉末制造和吸入药物治疗。尽管经过了半个多世纪的研究，湍流如何提高悬浮液滴的聚结率仍然存在相当大的不确定性。本研究通过直接数值模拟（DNS）、实验和在广泛条件下的现场测量直接测量液滴碰撞/聚结率来解决这种不确定性。研究的重点将是直接测量湍流驱动下液滴的聚结率。这适用于大范围的多相流，但对这一建议最重要的应用是处理大气中的云。在某些条件下，云的演化速度比微物理模型所能预测的要快。人们相信大气湍流可以解释云的加速形成。本研究将汇集三个科学工具的协同组合来分析自然湍流现象：DNS；实验室实验;现场测量。总体目标是在接近参数相似性的条件下，从高分辨率DNS和最先进的实验室和现场实验中生成明确的聚结数据。这项研究将包括在实验室和自然条件下对湍流场中惯性液滴聚结率的首次实验测量。只有通过这种集体努力才能实现这一目标——单独使用这些技术中的任何一种或两种都是不够的。除了拟议工作的工程影响外，拟议的活动还包括旨在鼓励代表性不足的少数民族进入学院的教育和推广活动。