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Study of the Aerodynamic Sampling Effects of a Holographic Cloud Droplet Instrument

机译:全息云滴仪器的空气动力学采样效果研究

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Computational fluid dynamics and particle tracing simulations are presented for a cloud droplet sensor. Airspeeds and streamlines around the sensor are calculated at several wind speeds and their effect on the droplet sampling are examined. Particle tracing is used to study the effect of different wind speeds and droplet sizes on the sampling of the cloud droplets. Simulated droplet concentrations are confirmed by comparing them with measured wind tunnel data. Results demonstrate clear sampling effects that are functions of both wind speed and droplet size. Optimal compromise between maximal measurement volume and sampling effects is found and a simple approximation for sensor’s sampling bias is presented. The results show that CFD simulations can give valuable information about the sampling of droplets in an ideal environment with known droplet concentrations. Even in a wind tunnel, the true test conditions are often impossible to accurately determine. Thus by simulating the sampling effects in different conditions, the sensor can be calibrated for a wide range of naturally occurring cloud conditions.
机译:提出了云滴传感器的计算流体动力学和颗粒追踪模拟。在几种风速下计算传感器周围的空速和流线,并检查其对液滴采样的影响。粒子跟踪用于研究不同的风速和液滴大小对云滴采样的影响。通过将其与测得的风洞数据进行比较,可以确定模拟的液滴浓度。结果表明,清晰的采样效果是风速和液滴大小的函数。找到了最大测量量和采样效果之间的最佳折衷,并给出了传感器采样偏差的简单近似值。结果表明,CFD仿真可以提供有关在已知液滴浓度的理想环境中进行液滴采样的有价值的信息。即使在风洞中,通常也无法准确确定真实的测试条件。因此,通过模拟不同条件下的采样效果,可以针对各种自然发生的云条件对传感器进行校准。

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