scholarly journals Condensational and Collisional Growth of Cloud Droplets in a Turbulent Environment

2019 ◽  
Vol 77 (1) ◽  
pp. 337-353 ◽  
Author(s):  
Xiang-Yu Li ◽  
Axel Brandenburg ◽  
Gunilla Svensson ◽  
Nils E. L. Haugen ◽  
Bernhard Mehlig ◽  
...  
Keyword(s):  
Size Distribution ◽  
Droplet Size ◽  
Early Stage ◽  
Droplet Size Distribution ◽  
Energy Dissipation Rate ◽  
Cloud Droplets ◽  
Navier Stokes Equation ◽  
Droplet Dynamics ◽  
Condensational Growth ◽  
Rain Formation

Abstract We investigate the effect of turbulence on the combined condensational and collisional growth of cloud droplets by means of high-resolution direct numerical simulations of turbulence and a superparticle approximation for droplet dynamics and collisions. The droplets are subject to turbulence as well as gravity, and their collision and coalescence efficiencies are taken to be unity. We solve the thermodynamic equations governing temperature, water vapor mixing ratio, and the resulting supersaturation fields together with the Navier–Stokes equation. We find that the droplet size distribution broadens with increasing Reynolds number and/or mean energy dissipation rate. Turbulence affects the condensational growth directly through supersaturation fluctuations, and it influences collisional growth indirectly through condensation. Our simulations show for the first time that, in the absence of the mean updraft cooling, supersaturation-fluctuation-induced broadening of droplet size distributions enhances the collisional growth. This is contrary to classical (nonturbulent) condensational growth, which leads to a growing mean droplet size, but a narrower droplet size distribution. Our findings, instead, show that condensational growth facilitates collisional growth by broadening the size distribution in the tails at an early stage of rain formation. With increasing Reynolds numbers, evaporation becomes stronger. This counteracts the broadening effect due to condensation at late stages of rain formation. Our conclusions are consistent with results of laboratory experiments and field observations, and show that supersaturation fluctuations are important for precipitation.

Turbulence Effects of Collision Efficiency and Broadening of Droplet Size Distribution in Cumulus Clouds

2018 ◽  
Vol 75 (1) ◽  
pp. 203-217 ◽  
Author(s):  
Sisi Chen ◽  
M. K. Yau ◽  
Peter Bartello
Keyword(s):  
Size Distribution ◽  
Droplet Size ◽  
Droplet Size Distribution ◽  
Droplet Growth ◽  
Small Scale ◽  
Cumulus Clouds ◽  
Collision Efficiency ◽  
Cloud Droplets ◽  
R Ratio ◽  
Condensational Growth

This paper aims to investigate and quantify the turbulence effect on droplet collision efficiency and explore the broadening mechanism of the droplet size distribution (DSD) in cumulus clouds. The sophisticated model employed in this study individually traces droplet motions affected by gravity, droplet disturbance flows, and turbulence in a Lagrangian frame. Direct numerical simulation (DNS) techniques are implemented to resolve the small-scale turbulence. Collision statistics for cloud droplets of radii between 5 and 25 μm at five different turbulence dissipation rates (20–500 cm2 s−3) are computed and compared with pure-gravity cases. The results show that the turbulence enhancement of collision efficiency highly depends on the r ratio (defined as the radius ratio of collected and collector droplets r/ R) but is less sensitive to the size of the collector droplet investigated in this study. Particularly, the enhancement is strongest among comparable-sized collisions, indicating that turbulence can significantly broaden the narrow DSD resulting from condensational growth. Finally, DNS experiments of droplet growth by collision–coalescence in turbulence are performed for the first time in the literature to further illustrate this hypothesis and to monitor the appearance of drizzle in the early rain-formation stage. By comparing the resulting DSDs at different turbulence intensities, it is found that broadening is most pronounced when turbulence is strongest and similar-sized collisions account for 21%–24% of total collisions in turbulent cases compared with only 9% in the gravitational case.

scholarly journals Dinamika tetes dalam kolom isian

2018 ◽  
Vol 7 (1) ◽  
pp. 710
Author(s):  
Danu Ariono ◽  
Dwiwahju Sasongko ◽  
Priyono Kusumo
Keyword(s):  
Mass Transfer ◽  
Transfer Coefficient ◽  
Mass Transfer Coefficient ◽  
Size Distribution ◽  
Droplet Size ◽  
Droplet Diameter ◽  
Mass Transfer Rate ◽  
Packed Column ◽  
Droplet Size Distribution ◽  
Droplet Dynamics

To date, evaluation of the performance of liquid-liquid extraction in packed columns has not been able to produce satisfactory results, because the correlations used in this evaluation are empirical in nature, with a very limited range of validity. One of the causes of this limitation is the use of the assumption that the dynamics of liquid dispersed in droplets is constant (in terms of shape, dimensions, and numbers), so that the mass transfer interfacial area and mass transfer coefficient in the column are assumed to be constant. In reality, dynamics of droplets in a column is not constant, due to the imbalance between droplet coalescence and disintegration. For a given droplet diameter, there is an increase in numbers of droplets due to coalescence of smaller droplets, and a  decrease in numbers of droplets due to disintegration into smaller droplets. These coalescence and disintegration phenomena may be caused by various factors, including the existence of packings which impede the flow of droplets. These phenomena impact the mass transfer rate from continuous to dispersed phase, and vice versa, due to a variation in the interfacial contact area and mass transfer coefficient. The observation of droplet dynamics from droplet formation until its motion through void spaces between packings is a critical factor in developing a model that can describe the performance of the packed column. The dynamics of droplets is influenced by various operational and physical variables.  A droplet dynamics experiment has been undertaken, aimed at obtaining the droplet size distribution at specific heights along the column. This distribution is to be used to develop mass transfer coefficient correlations in the continuous and dispersed phases.Keywords: droplet size distribution, packed column Abstrak Evaluasi unjuk kerja ekstraksi cair-cair dalam kolom isian (packed column) hingga saat ini belum dapat memberikan hasil yang memuaskan karena korelasi-korelasi yang  digunakan  masih  bersifat  empiris serta daerah keberlakuannya sangat terbatas. Salah satu penyebab keterbatasan berlakunya korelasi tersebut ialah penggunaan anggapan bahwa dinamika cairan yang terdispersi dalam bentuk tetesan bersifat konstan (bentuk, ukuran serta jumlahnya), sehingga harga luas perpindahan massa dan harga koefisien perpindahan massa dalam kolom dianggap tetap. Kenyataannya dinamika tetesan dalam kolom tidak konstan akibat adanya tetesan yang bergabung dan pecah dalam jumlah yang  tidak sama. Pada suatu harga diameter tetesan tertentu, ada penambahan jumlah tetesan akibat penggabungan tetesan­ tetesan yang ukurannya lebih kecil serta adanya pengurangan jumlah tetesan akibat pecahnya tetesan menjadi tetesan-tetesan yang lebih kecil. Peristiwa penggabungan dan pemecahan tetesan dapat disebabkan berbagai faktor temasuk adanya isian yang menghalangi gerakan tetesan. Kejadian tersebut akan mempengaruhi laju proses perpindahan massa dari fasa kontinyu ke fasa  terdispersi  atau sebaliknya, karena adanya variasi luas permukaan kontak serta koefisien perpindahan massanya. Pengamatan dinamika tetesan mulai saat pembentukan tetes hingga pergerakannya saat melewati sela-sela isian merupakan faktor penting dalam  membangun model  yang  dapat menggambarkan unjuk kerja kolom isian. Dinamika tetesan tersebut dipengaruhi oleh berbagai variabel operasi dan variabel fisik. Eksperimen dinamika fetes yang dilakukan diarahkan untuk memperoleh distribusi ukuran tetes pada posisi ketinggian tertentu dan distribusi tersebut akan digunakan untuk pengembangan  korelasi koefisien perpindahan massa difasa  dispersi danfasa kontinyu.Kata kunci: distribusi ukuran tetes, kolom isian.

Lagrangian Droplet Dynamics in the Subsiding Shell of a Cloud Using Direct Numerical Simulations

2015 ◽  
Vol 72 (10) ◽  
pp. 4015-4028 ◽  
Author(s):  
Vincent E. Perrin ◽  
Harmen J. J. Jonker
Keyword(s):  
Size Distribution ◽  
Droplet Size ◽  
Evaporative Cooling ◽  
Mixing Layer ◽  
Droplet Size Distribution ◽  
Small Scale ◽  
Cumulus Clouds ◽  
Droplet Dynamics ◽  
Turbulent Dissipation ◽  
Environmental Air

Abstract This study investigates the droplet dynamics at the lateral cloud–environment interface in shallow cumulus clouds. A mixing layer is used to study a small part of the cloud edge using direct numerical simulation combined with a Lagrangian particle tracking and collision algorithm. The effect of evaporation, gravity, coalescence, and the initial droplet size distribution on the intensity of the mixing layer and the evolution of the droplet size distribution is studied. Mixing of the droplets with environmental air induces evaporative cooling, which results in a very characteristic subsiding shell. As a consequence, stronger horizontal velocity gradients are found in the mixing layer, which induces more mixing and evaporation. A broadening of the droplet size distribution is observed as a result of evaporation and coalescence. Gravity acting on the droplets allows droplets in cloudy filaments detrained from the cloud to sediment and remain longer in the unsaturated environment. While this effect of gravity did not have a significant impact in this case on the mean evolution of the mixing layer, it does contribute to the broadening of the droplet size distribution and thereby significantly increases the collision rate. Although more but smaller droplets result in more evaporative cooling, more droplets also increase small-scale fluctuations and the production of turbulent dissipation. For the smallest droplets considered with a radius of 10 μm, the authors found that, although a more pronounced buoyancy dip was present, the increase in dissipation rate actually led to a decrease in the turbulent intensity of the mixing layer. Extrapolation of the results to realistic clouds is discussed.

A Numerical Model for Oil Droplet Evolution Emanating from Blowouts

2014 ◽  
Vol 2014 (1) ◽  
pp. 561-571 ◽  
Author(s):  
Lin Zhao ◽  
Michel C. Boufadel ◽  
E. Eric Adams ◽  
Scott A. Socolofsky ◽  
Kenneth Lee
Keyword(s):  
Numerical Model ◽  
Size Distribution ◽  
Droplet Size ◽  
Volume Fraction ◽  
Control Volume ◽  
Droplet Size Distribution ◽  
Energy Dissipation Rate ◽  
Mixing Energy ◽  
Maximum Value ◽  
The Mean

ABSTRACT This paper presents the details of a numerical model that is capable of simulating the droplet size distribution emanating from blowouts. The model was obtained as a result of combination of traditional mechanistic models developed in reactors with jet (or plume) models to predict the evolution of the plume away from the orifice. Inputs to the model include the energy dissipation rate (or the mixing energy) and holdup, which is the volume fraction of oil in the control volume. These parameters vary as the plume spreads away from the orifice. They have a maximum value near the orifice and rapidly decrease as moving away from the orifice. The model was validated using experimental data available in the literature. Subsequently, the model was used to predict the evolution of droplets in the Deepwater Horizon incident. The model provides the variation of the mean diameter and the droplet size distribution with depths away from the orifice. The sensitivity of different parameters, such as interfacial tension which could present the addition of dispersants was also evaluated.

scholarly journals Chemical composition and droplet size distribution of cloud at the summit of Mount Tai, China

2017 ◽  
Author(s):  
Jiarong Li ◽  
Xinfeng Wang ◽  
Jianmin Chen ◽  
Chao Zhu ◽  
Weijun Li ◽  
...  
Keyword(s):  
Chemical Composition ◽  
Size Distribution ◽  
Droplet Size ◽  
Atmospheric Aerosols ◽  
Ph Value ◽  
Inorganic Ions ◽  
Droplet Size Distribution ◽  
Dilution Effect ◽  
Water Soluble ◽  
Cloud Droplets

Abstract. Chemical composition of 39 cloud samples and droplet size distribution in 24 cloud events were investigated at the summit of Mt. Tai from July to October 2014. Inorganic ions, organic acids, metals, HCHO, H2O2, sulfur(IV), organic carbon, element carbon as well as pH and electrical conductivity were analyzed. The acidity of the cloud water significantly decreased from a reported value of pH 3.86 in 2007–2008 (Guo et al., 2012) to pH 5.87 in the present study. The concentrations of nitrate and ammonium were both increased since 2007–2008, but the overcompensation of ammonium led to the increase of the mean pH value. The microphysical properties showed that cloud droplets were smaller than 26.0 μm and the most were in the range of 6.0–9.0 μm. The maximum droplet number concentration (Nd) was associated with droplet sizes of 7.0 μm. Cloud droplets exhibited a strong interaction with atmospheric aerosols. High PM2.5 level resulted in higher concentrations of water soluble ions and smaller sizes with more numbers of cloud droplets, and further gave rise to relatively high acidity. High degrees of relative humidity facilitated the formation of large cloud droplets and led to high liquid water contents under low PM2.5 level. The cloud droplets to wet deposition acted as an important sink of soluble material in the atmosphere and the dilution effect of the water content should be considered when estimating concentrations of soluble components in the cloud phase.

scholarly journals Cloud droplet size distribution broadening during diffusional growth: ripening amplified by deactivation and reactivation

2017 ◽  
Author(s):  
Fan Yang ◽  
Pavlos Kollias ◽  
Raymond A. Shaw ◽  
Andrew M. Vogelmann
Keyword(s):  
Droplet Size ◽  
Dynamic Models ◽  
Ostwald Ripening ◽  
Cloud Model ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Diffusional Growth ◽  
Cloud Droplets ◽  
Cloud Properties ◽  
Condensational Growth

Abstract. Cloud droplet size distributions (CDSDs), which are related to cloud albedo and lifetime, are usually broader in warm clouds than predicted from adiabatic parcel calculations. We investigate a mechanism for the CDSD broadening using a Lagrangian bin-microphysics cloud parcel model that considers the condensational growth of cloud droplets formed on polydisperse, sub-micrometer aerosols in an adiabatic cloud parcel that undergoes vertical oscillations, such as those due to cloud circulations or turbulence. Results show that the CDSD can be broadened during condensational growth as a result of Ostwald ripening amplified by droplet deactivation and reactivation, which is consistent with Korolev (1995). The relative roles of the solute effect, curvature effect, deactivation and reactivation on CDSD broadening are investigated. Deactivation of smaller cloud droplets, which is due to the combination of curvature and solute effects in the downdraft region, enhances the growth of larger cloud droplets and thus contributes particles to the larger size end of the CDSD. Droplet reactivation, which occurs in the updraft region, contributes particles to the smaller size end of the CDSD. In addition, we find that growth of the largest cloud droplets strongly depends on the residence time of cloud droplet in the cloud rather than the magnitude of local variability in the supersaturation fluctuation. This is because the environmental saturation ratio is strongly buffered by smaller cloud droplets. Two necessary conditions for this CDSD broadening, which generally occur in the atmosphere, are: (1) droplets form on polydisperse aerosols of varying hygroscopicity and (2) the cloud parcel experiences upwards and downwards motions. Therefore we expect that this mechanism for CDSD broadening is possible in real clouds. Our results also suggest it is important to consider both curvature and solute effects before and after cloud droplet activation in a cloud model. The importance of this mechanism compared with other mechanisms on cloud properties should be investigated through in-situ measurements and 3-D dynamic models.

scholarly journals A New Mechanism of Droplet Size Distribution Broadening during Diffusional Growth

2013 ◽  
Vol 70 (7) ◽  
pp. 2051-2071 ◽  
Author(s):  
Alexei Korolev ◽  
Mark Pinsky ◽  
Alex Khain
Keyword(s):  
Size Distribution ◽  
Droplet Size ◽  
Initial Conditions ◽  
Droplet Size Distribution ◽  
Cloud Base ◽  
Diffusional Growth ◽  
Cloud Droplets ◽  
Droplet Concentration ◽  
Droplet Sizes ◽  
Precipitation Formation

Abstract A new mechanism has been developed for size distribution broadening toward large droplet sizes. This mechanism may explain the rapid formation of large cloud droplets, which may subsequently trigger precipitation formation through the collision–coalescence process. The essence of the new mechanism consists of a sequence of mixing events between ascending and descending parcels. When adiabatically ascending and descending parcels having the same initial conditions at the cloud base arrive at the same level, they will have different droplet sizes and temperatures, as well as different supersaturations. Isobaric mixing between such parcels followed by further ascents and descents enables the enhanced growth of large droplets. The numerical simulation of this process suggests that the formation of large 30–40-μm droplets may occur within 20–30 min inside a shallow adiabatic stratiform layer. The dependencies of the rate of the droplet size distribution broadening on the intensity of the vertical fluctuations, their spatial amplitude, rate of mixing, droplet concentration, and other parameters are considered here. The effectiveness of this mechanism in different types of clouds is discussed.

scholarly journals Chemical composition and droplet size distribution of cloud at the summit of Mount Tai, China

2017 ◽  
Vol 17 (16) ◽  
pp. 9885-9896 ◽  
Author(s):  
Jiarong Li ◽  
Xinfeng Wang ◽  
Jianmin Chen ◽  
Chao Zhu ◽  
Weijun Li ◽  
...  
Keyword(s):  
Chemical Composition ◽  
Size Distribution ◽  
Droplet Size ◽  
Ph Value ◽  
Inorganic Ions ◽  
Droplet Size Distribution ◽  
Dilution Effect ◽  
Cloud Water ◽  
Water Soluble ◽  
Cloud Droplets

Abstract. The chemical composition of 39 cloud samples and droplet size distributions in 24 cloud events were investigated at the summit of Mt. Tai from July to October 2014. Inorganic ions, organic acids, metals, HCHO, H2O2, sulfur(IV), organic carbon, and elemental carbon as well as pH and electrical conductivity were analyzed. The acidity of the cloud water significantly decreased from a reported value of pH 3.86 during 2007–2008 (Guo et al., 2012) to pH 5.87 in the present study. The concentrations of nitrate and ammonium were both increased since 2007–2008, but the overcompensation of ammonium led to an increase in the mean pH value. The microphysical properties showed that cloud droplets were smaller than 26.0 µm and most were in the range of 6.0–9.0 µm at Mt. Tai. The maximum droplet number concentration (Nd) was associated with a droplet size of 7.0 µm. High liquid water content (LWC) values could facilitate the formation of larger cloud droplets and broadened the droplet size distribution. Cloud droplets exhibited a strong interaction with atmospheric aerosols. Higher PM2. 5 levels resulted in higher concentrations of water-soluble ions and smaller sizes with increased numbers of cloud droplets. The lower pH values were likely to occur at higher PM2. 5 concentrations. Clouds were an important sink for soluble materials in the atmosphere. The dilution effect of cloud water should be considered when estimating concentrations of soluble components in the cloud phase.

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