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USING 3D-PRINTED ANALOGUES TO UNDERSTAND THE AERODYNAMICS OF COMPLEX ICE PARTICLES

USING 3D-PRINTED ANALOGUES TO UNDERSTAND THE AERODYNAMICS OF COMPLEX ICE PARTICLES
使用 3D 打印类似物了解复杂冰颗粒的空气动力学
批准号:
NE/R00014X/1
负责人:
Chris Westbrook
金额:
$48.2万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2017
资助国家:
英国
项目状态:
已结题
起止时间:
2017 至 --

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中文摘要
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英文摘要
Many of the clouds in the atmosphere contain ice particles. These ice particles play an important role in the climate system, because high-altitude cirrus clouds cover around 30% of the globe at any one time, and act to warm the planet. Ice particles are also important for the development of precipitation, and not only in cold polar climates: even in mid-latitudes (like the UK), over three quarters of the precipitation that falls originates as snowflakes aloft - it is just that most of it melts before arriving at the surface.Ice particles, both in clouds and in snowfall at the surface, precipitate. In other words, they are able to grow large enough to fall through the air. This has several implications. The most obvious of these is that the rate at which the particles fall out controls the transport of water vertically through the atmosphere and to the surface. More subtly, the movement of each ice particle through the air directly influences the rate at which the particle grows, evaporates and melts. For example, if the air is humid enough, water molecules will diffuse to the ice crystal's surface and deposit there, leading to growth. If the particle is stationary, this growth occurs steadily but slowly, because the growing ice crystal depletes the vapour around it, leading to a shallow gradient in the concentration of molecules. If the particle is falling, this growth can occur much faster, because the ice crystal is constantly falling into fresh, humid air, leading to steep concentration gradients. The quantitative details of exactly how fast an ice particle of a given size and shape falls, and how much the growth rates are enhanced by, is determined by the airflow around the ice particle, or its aerodynamics. Unfortunately, this is an area of cloud physics where our understanding is extremely limited. The aerodynamics of simple shapes like spheres, spheroids and discs is well studied. However it is clear from observation of natural ice particles that they are not simple in their geometry. Instead the particles are often complex and irregular in their shape. We have almost no high-quality data on the aerodynamics of such particles. As a result, even state-of-the-art microphysical models are forced to approximate the aerodynamical effects on ice processes as though these complex irregular particles were spheres or spheroids, hoping that this is an adequate approximation. To solve this problem, experimental data is needed for the aerodynamics of particles with the complex shapes that we observe in the atmosphere. The stumbling block is that making suitable observations of natural ice particles in free-fall is extremely challenging. In snowfall at the surface the particles are small, fragile, easily blown by the wind, and likely to melt or evaporate if not handled with great care. Direct sampling of falling particles in cirrus clouds is impossible. In neither case is it possible to directly determine the airflow around the particle or the influence of that flow on the microphysical process rates.In this project we overcome these problems with the use of analogues. Using 3D printing techniques we will create plastic particles with the same complex geometry as natural ice particles. By dropping the particles in tanks of liquids, and through air in the laboratory and a vertical wind tunnel, we can determine how the fall speed of the particles is controlled by their size and geometry. Exploiting recent developments in tomographic particle imaging velocimetry we can measure the airflow around the falling analogues. From this we can directly determine how the airflow enhances the particle growth, evaporation and melting rates.
期刊论文(4)
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会议论文
DOI: 10.1063/5.0064902
发表时间: 2021-10
期刊: Physics of Fluids
影响因子: 4.6
作者: [G. Tagliavini;Mark W. McCorquodale;C. Westbrook;M. Holzner]
通讯作者: G. Tagliavini;Mark W. McCorquodale;C. Westbrook;M. Holzner
TRAIL part 2: A comprehensive assessment of ice particle fall speed parametrisations
TRAIL 第 2 部分:冰粒下落速度参数化的综合评估
DOI: 10.1002/qj.3936
发表时间: 2020
期刊: Quarterly Journal of the Royal Meteorological Society
影响因子: 8.9
作者: [McCorquodale M]
通讯作者: McCorquodale M
Drag coefficient prediction of complex-shaped snow particles falling in air beyond the Stokes regime
斯托克斯范围外空气中复杂形状雪粒的阻力系数预测
DOI: 10.1016/j.ijmultiphaseflow.2021.103652
发表时间: 2021
期刊: International Journal of Multiphase Flow
影响因子: 3.8
作者: [Tagliavini G]
通讯作者: Tagliavini G
TRAIL: A novel approach for studying the aerodynamics of ice particles
TRAIL:研究冰粒空气动力学的新方法
DOI: 10.1002/qj.3935
发表时间: 2020
期刊: Quarterly Journal of the Royal Meteorological Society
影响因子: 8.9
作者: [McCorquodale M]
通讯作者: McCorquodale M
New measurements of snowflake scattering and microstructure using a novel Multi-Wavelength, Multi-Angle Scatterometer (MuWMAS)
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    NE/W000946/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $103.56万
  • 财政年份:
    2022
  • 负责人:
    Chris Westbrook
  • 依托单位:
A new signal processing technology to eliminate range sidelobes in meteorological radar data
  • 批准号:
    NE/L011603/1
  • 项目类别:
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  • 资助金额:
    $8.52万
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    2014
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Exploiting multi-wavelength radar Doppler spectra to characterise the microphysics of ice hydrometeors
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    NE/K012444/1
  • 项目类别:
    Research Grant
  • 资助金额:
    $21.47万
  • 财政年份:
    2013
  • 负责人:
    Chris Westbrook
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