scholarly journals Review of the manuscript "The impact of fluctuations and correlations in droplet growth by collision-coalescence revisited. Part I: Numerical calculation of post-gel droplet size distribution"

2017 ◽  
Author(s):  
Anonymous
Keyword(s):  
Numerical Calculation ◽  
Size Distribution ◽  
Droplet Size ◽  
Droplet Size Distribution ◽  
Droplet Growth ◽  
The Impact

scholarly journals The impact of fluctuations and correlations in droplet growth by collision-coalescence revisited. Part I: Numerical calculation of post-gel droplet size distribution

2016 ◽  
Author(s):  
Lester Alfonso ◽  
Graciela B. Raga
Keyword(s):  
Size Distribution ◽  
Droplet Size ◽  
Sol Gel ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Stochastic Simulation Algorithm ◽  
Droplet Growth ◽  
Sol Gel Transition ◽  
The Impact ◽  
Gel Transition

Abstract. The impact of stochastic fluctuations in cloud droplet growth is a matter of broad interest, since stochastic effects are one of the possible explanations of how cloud droplets cross the size-gap and form the raindrop embryos that trigger warm rain development in cumulus clouds. Most theoretical studies in this topic rely on the use of the kinetic collection equation, or the stochastic simulation algorithm (Gillespie 1975). However, the kinetic collection equation is a deterministic equation with no stochastic fluctuations. Moreover, the traditional calculations using the kinetic collection equation are not valid when the system undergoes a transition from a continuous distribution to a distribution plus a runaway raindrop embryo (known as the sol-gel transition). On the other hand, the stochastic simulation algorithm, although intrinsically stochastic, fails to reproduce adequately the large end of the droplet size distribution due to the huge number of realizations required. Therefore, the full stochastic description of cloud droplet growth must be obtained from the solution of the master equation for stochastic coalescence. In this study the master equation is used to calculate the evolution of the droplet size distribution after the sol-gel transition. These calculations show that after the formation of the raindrop embryo, the expected droplet mass distribution strongly differs from the results obtained with the kinetic collection equation. Furthermore, the low mass bins and bins from the gel fraction are strongly anti-correlated in the vicinity of the critical time, this being one of the possible explanations for the differences between the kinetic and stochastic approaches after the sol-gel transition. Calculations performed within the stochastic framework provide insight into the inability of explicit microphysics cloud models to explain the droplet spectral broadening observed in small, warm clouds.

scholarly journals The impact of fluctuations and correlations in droplet growth by collision–coalescence revisited – Part 1: Numerical calculation of post-gel droplet size distribution

2017 ◽  
Vol 17 (11) ◽  
pp. 6895-6905 ◽  
Author(s):  
Lester Alfonso ◽  
Graciela B. Raga
Keyword(s):  
Size Distribution ◽  
Droplet Size ◽  
Sol Gel ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Stochastic Simulation Algorithm ◽  
Droplet Growth ◽  
Sol Gel Transition ◽  
The Impact ◽  
Gel Transition

Abstract. The impact of stochastic fluctuations in cloud droplet growth is a matter of broad interest, since stochastic effects are one of the possible explanations of how cloud droplets cross the size gap and form the raindrop embryos that trigger warm rain development in cumulus clouds. Most theoretical studies on this topic rely on the use of the kinetic collection equation, or the Gillespie stochastic simulation algorithm. However, the kinetic collection equation is a deterministic equation with no stochastic fluctuations. Moreover, the traditional calculations using the kinetic collection equation are not valid when the system undergoes a transition from a continuous distribution to a distribution plus a runaway raindrop embryo (known as the sol–gel transition). On the other hand, the stochastic simulation algorithm, although intrinsically stochastic, fails to adequately reproduce the large end of the droplet size distribution due to the huge number of realizations required. Therefore, the full stochastic description of cloud droplet growth must be obtained from the solution of the master equation for stochastic coalescence. In this study the master equation is used to calculate the evolution of the droplet size distribution after the sol–gel transition. These calculations show that after the formation of the raindrop embryo, the expected droplet mass distribution strongly differs from the results obtained with the kinetic collection equation. Furthermore, the low-mass bins and bins from the gel fraction are strongly anticorrelated in the vicinity of the critical time, this being one of the possible explanations for the differences between the kinetic and stochastic approaches after the sol–gel transition. Calculations performed within the stochastic framework provide insight into the inability of explicit microphysics cloud models to explain the droplet spectral broadening observed in small, warm clouds.

scholarly journals Aerosol indirect effect from turbulence-induced broadening of cloud-droplet size distributions

2016 ◽  
Vol 113 (50) ◽  
pp. 14243-14248 ◽  
Author(s):  
Kamal Kant Chandrakar ◽  
Will Cantrell ◽  
Kelken Chang ◽  
David Ciochetto ◽  
Dennis Niedermeier ◽  
...  
Keyword(s):  
Size Distribution ◽  
Droplet Size ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Aerosol Concentration ◽  
Droplet Radius ◽  
Droplet Growth ◽  
Moist Convection ◽  
Concentration Changes ◽  
Precipitation Formation

The influence of aerosol concentration on the cloud-droplet size distribution is investigated in a laboratory chamber that enables turbulent cloud formation through moist convection. The experiments allow steady-state microphysics to be achieved, with aerosol input balanced by cloud-droplet growth and fallout. As aerosol concentration is increased, the cloud-droplet mean diameter decreases, as expected, but the width of the size distribution also decreases sharply. The aerosol input allows for cloud generation in the limiting regimes of fast microphysics (τc<τt) for high aerosol concentration, and slow microphysics (τc>τt) for low aerosol concentration; here, τc is the phase-relaxation time and τt is the turbulence-correlation time. The increase in the width of the droplet size distribution for the low aerosol limit is consistent with larger variability of supersaturation due to the slow microphysical response. A stochastic differential equation for supersaturation predicts that the standard deviation of the squared droplet radius should increase linearly with a system time scale defined as τs−1=τc−1+τt−1, and the measurements are in excellent agreement with this finding. The result underscores the importance of droplet size dispersion for aerosol indirect effects: increasing aerosol concentration changes the albedo and suppresses precipitation formation not only through reduction of the mean droplet diameter but also by narrowing of the droplet size distribution due to reduced supersaturation fluctuations. Supersaturation fluctuations in the low aerosol/slow microphysics limit are likely of leading importance for precipitation formation.

Broadening of the Cloud Droplet Size Distribution due to Thermal Radiative Cooling: Turbulent Parcel Simulations

2020 ◽  
Vol 77 (6) ◽  
pp. 1993-2010
Author(s):  
Mares Barekzai ◽  
Bernhard Mayer
Keyword(s):  
Thermal Radiation ◽  
Droplet Size ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Growth Efficiency ◽  
Droplet Growth ◽  
Radiative Cooling ◽  
Radiative Effect ◽  
Diffusional Growth ◽  
The Impact

Abstract Despite impressive advances in rain forecasts over the past decades, our understanding of rain formation on a microphysical scale is still poor. Droplet growth initially occurs through diffusion and, for sufficiently large radii, through the collision of droplets. However, there is no consensus on the mechanism to bridge the condensation coalescence bottleneck. We extend the analysis of prior methods by including radiatively enhanced diffusional growth (RAD) to a Markovian turbulence parameterization. This addition increases the diffusional growth efficiency by allowing for emission and absorption of thermal radiation. Specifically, we quantify an upper estimate for the radiative effect by focusing on droplets close to the cloud boundary. The strength of this simple model is that it determines growth-rate dependencies on a number of parameters, like updraft speed and the radiative effect, in a deterministic way. Realistic calculations with a cloud-resolving model are sensitive to parameter changes, which may cause completely different cloud realizations and thus it requires considerable computational power to obtain statistically significant results. The simulations suggest that the addition of radiative cooling can lead to a doubling of the droplet size standard deviation. However, the magnitude of the increase depends strongly on the broadening established by turbulence, due to an increase in the maximum droplet size, which accelerates the production of drizzle. Furthermore, the broadening caused by the combination of turbulence and thermal radiation is largest for small updrafts and the impact of radiation increases with time until it becomes dominant for slow synoptic updrafts.

Fluid Flow Phenomena and Droplet Size Distribution Along the Feed Spreader of Large Oil/Water Tank Separators

2009 ◽  
Author(s):  
Jose G. Severino ◽  
Luis E. Gomez ◽  
Steve J. Leibrandt ◽  
Ram S. Mohan ◽  
Ovadia Shoham
Keyword(s):  
Size Distribution ◽  
Droplet Size ◽  
Separation Efficiency ◽  
Droplet Size Distribution ◽  
Separation Performance ◽  
Water Tank ◽  
Water Dispersion ◽  
Flow Phenomena ◽  
Oil Water ◽  
The Impact

Large gravity separation tanks play an essential role in crude oil production in many fields worldwide. These tanks are used to separate water from an oil-rich stream before safely returning it to the environment. The oil/water dispersion enters the tanks through a feed spreader consisting of an array of pipes with small effluent nozzles. A major challenge is being able to predict oil/water dispersion distribution along the spreader as well as, the maximum water droplet size exiting through the effluent nozzles, under a given set of conditions. The capacity of the studied tank is 80,000 barrels (12,719 m3). Current feed stream is about 60,000 bpd (9,540 m3/day) of wet crude containing about 20% water by volume. A significant increase in flow rates and water volume fraction is anticipated [7], as more wells are added and existing ones mature. This work is aimed at investigating the separation performance of these tanks under current and future flow conditions; focusing primarily on the flow phenomena and droplet size distribution inside the spreader. The main objective is then to identify the impact of the spreader’s geometry and piping configuration on flow behavior and tank’s separation efficiency. The final product provides key information needed for mechanistic modeling the tank separation performance and optimizing tank components’ design. The feed spreader is simulated using Computational Fluid Dynamics (CFD) to assess oil/water flow distribution inside the network. Droplet size distribution along branch-pipes effluent nozzles in, including droplet breakup and coalescence has been studied using the Gomez mechanistic model [2] with input from CFD results. An experimental investigation of the spreader using a scaled prototype was also conducted to better understand flow phenomena and verify the CFD models. Results confirm the occurrence of significant maldistribution of the water and oil phases along the spreader that could impair separation efficiency.

scholarly journals Influence of Microphysical Variability on Stochastic Condensation in a Turbulent Laboratory Cloud

2018 ◽  
Vol 75 (1) ◽  
pp. 189-201 ◽  
Author(s):  
N. Desai ◽  
K. K. Chandrakar ◽  
K. Chang ◽  
W. Cantrell ◽  
R. A. Shaw
Keyword(s):  
Relaxation Time ◽  
Size Distribution ◽  
Droplet Size ◽  
Droplet Size Distribution ◽  
Number Concentration ◽  
Droplet Growth ◽  
Diffusional Growth ◽  
Phase Relaxation ◽  
Distribution Width ◽  
Phase Relaxation Time

Diffusional growth of droplets by stochastic condensation and a resulting broadening of the size distribution has been considered as a mechanism for bridging the cloud droplet growth gap between condensation and collision–coalescence. Recent studies have shown that supersaturation fluctuations can lead to a broadening of the droplet size distribution at the condensational stage of droplet growth. However, most studies using stochastic models assume the phase relaxation time of a cloud parcel to be constant. In this paper, two questions are asked: how variability in droplet number concentration and radius influence the phase relaxation time and what effect it has on the droplet size distributions. To answer these questions, steady-state cloud conditions are created in the laboratory and digital inline holography is used to directly observe the variations in local number concentration and droplet size distribution and, thereby, the integral radius. Stochastic equations are also extended to account for fluctuations in integral radius and obtain new terms that are compared with the laboratory observations. It is found that the variability in integral radius is primarily driven by variations in the droplet number concentration and not the droplet radius. This variability does not contribute significantly to the mean droplet growth rate but does contribute significantly to the rate of increase of the size distribution width.

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 Long-resident droplets at the stratocumulus top

2016 ◽  
Vol 16 (10) ◽  
pp. 6563-6576 ◽  
Author(s):  
Alberto de Lozar ◽  
Lukas Muessle
Keyword(s):  
Size Distribution ◽  
Droplet Size ◽  
Large Scale ◽  
Turbulence Models ◽  
Longwave Radiation ◽  
Droplet Size Distribution ◽  
Droplet Growth ◽  
Small Scale ◽  
Radiative Cooling ◽  
Stratocumulus Clouds

Abstract. Turbulence models predict low droplet-collision rates in stratocumulus clouds, which should imply a narrow droplet size distribution and little rain. Contrary to this expectation, rain is often observed in stratocumuli. In this paper, we explore the hypothesis that some droplets can grow well above the average because small-scale turbulence allows them to reside at cloud top for a time longer than the convective-eddy time t*. Long-resident droplets can grow larger because condensation due to longwave radiative cooling, and collisions have more time to enhance droplet growth. We investigate the trajectories of 1 billion Lagrangian droplets in direct numerical simulations of a cloudy mixed-layer configuration that is based on observations from the flight 11 from the VERDI campaign. High resolution is employed to represent a well-developed turbulent state at cloud top. Only one-way coupling is considered. We observe that 70 % of the droplets spend less than 0.6t* at cloud top before leaving the cloud, while 15 % of the droplets remain at least 0.9t* at cloud top. In addition, 0.2 % of the droplets spend more than 2.5t* at cloud top and decouple from the large-scale convective eddies that brought them to the top, with the result that they become memoryless. Modeling collisions like a Poisson process leads to the conclusion that most rain droplets originate from those memoryless droplets. Furthermore, most long-resident droplets accumulate at the downdraft regions of the flow, which could be related to the closed-cell stratocumulus pattern. Finally, we see that condensation due to longwave radiative cooling considerably broadens the cloud-top droplet size distribution: 6.5 % of the droplets double their mass due to radiation in their time at cloud top. This simulated droplet size distribution matches the flight measurements, confirming that condensation due to longwave radiation can be an important mechanism for broadening the droplet size distribution in radiatively driven stratocumuli.

The Measuring of Sodium Droplet Size Distribution and its Impact on the Consequence of Sodium Spray Fire

2017 ◽  
Author(s):  
Wang Guozhi ◽  
Du Haiou ◽  
Wang Rongdong ◽  
Shi Wentao ◽  
Piao Jun
Keyword(s):  
Size Distribution ◽  
Droplet Size ◽  
Input Data ◽  
Drop Size ◽  
Droplet Size Distribution ◽  
Drop Size Distribution ◽  
Liquid Sodium ◽  
The Real ◽  
Temperature And Pressure ◽  
The Impact

The sodium droplet size distribution has significant impact on the consequence of sodium spray fire. And it is fundamental input data for the validation and application of sodium spray fire code. The experiments were carried out in a closed vessel to measure the sodium droplet size distribution. Liquid sodium of 250 °C was sprayed downward into the vessel in the form of sodium droplets through a nozzle with a diameter of 2.4mm. The vessel was inerted by argon gas to prevent the sodium droplets from burning. A real time spray droplet sizing system based on ensemble diffraction technique was used to measure the size of the droplets. And the laser beam was passed through two glass windows on the wall of the vessel to reach the sodium droplets. The tests showed that the sizes of the sodium droplets ranged from 184μm to 1000μm at the nozzle pressure of 0.15MPa. And median diameter was 532μm. The sodium spray fire code named NACOM was used to evaluate the impact of particle size distribution on sodium fire. The measured sodium droplets size distribution and the Nukiyama-tanasama drop size distribution were divided into 11 groups to be used as input data for the NACOM code. A comparison showed that 23% of particles in Nukiyama-tanasama drop size distribution were over 1000μm, while the largest size of particles in the measured sodium droplets was 1000μm. The calculation by NACOM code showed that the trend and value of temperature and pressure in the vessel were similar, so to some extent Nukiyama-tanasama drop size distribution is a good approximation of the real sodium droplet size distribution. However, Nukiyama-tanasama drop size distribution may be unsuitable for application in sodium fire safety analysis, because the temperature and pressure calculated from which was lower than that of the real droplet size distribution.

Sign in / Sign up

Export Citation Format

Share Document