Collisional Evolution of the Asteroid Size Distribution: A Numerical Simulation

1993 ◽  
pp. 403-404
Author(s):  
A. Campo Bagatin ◽  
P. Farinella ◽  
P. Paolicchi
Keyword(s):  
Numerical Simulation ◽  
Size Distribution ◽  
Collisional Evolution

Numerical Simulation and Experiment of Atomization Field of Fan-Shaped Atomization Nozzle for Plant Protection UAV

2021 ◽  
Vol 14 ◽  
Author(s):  
Maohua Xiao ◽  
Yuanfang Zhao ◽  
Zhenmin Sun ◽  
Chaohui Liu ◽  
Tianpeng Zhang
Keyword(s):  
Numerical Simulation ◽  
Size Distribution ◽  
Droplet Size ◽  
Plant Protection ◽  
Cone Angle ◽  
Droplet Size Distribution ◽  
Droplet Velocity ◽  
Inlet Pressure ◽  
Spray Cone Angle ◽  
Spray Cone

Background: There are drift and volatilization of the droplets produced by the plant protection Unmanned Aerial Vehicle (UAV) under the influence of external wind speed and its flight speed. Objective: It studied the atomization characteristics of its fan-shaped atomizing nozzle under different inlet pressures and inner cavity diameters. Methods: For the start, the Realizable k-ε turbulence model, DPM discrete phase model and TAB breakup model are used to make a numerical simulation of the spray process of the nozzle. Then, the SIMPLE algorithm is used to obtain the droplet size distribution diagram of the nozzle atomization field. At last, the related test methods are used to study its atomization performance, and the changes of atomization angle and droplet velocity under different inlet pressures and inner cavity diameters and the distribution of droplet size are discussed. Results: The research results show that under the same inner cavity diameter, as the inlet pressure increases, the spray cone angle of the nozzle and the droplet velocity at the same distance from the nozzle increase. As the distance from the nozzle increases, the droplet velocity decreases gradually, the droplet size distribution moves to the direction of small diameter, and the droplets in the anti-drift droplet size area increase. Under the same inlet pressure, as the diameter of the inner cavity increases, the spray cone angle first increases and then decreases, and the droplet velocity at the same distance from the nozzle increases. As the distance from the nozzle increases, the droplet velocity decreases gradually, the droplet size distribution moves to the direction of large diameter, and the large size droplets increase, which cannot meet the anti-drift volatilization effect. Conclusion: Under the parameter set in this study, when the inlet pressure is 0.6MPa and the inner cavity diameter is 2mm, the atomization result is the best.

scholarly journals Impactor Flux on the Pluto-Charon System

2009 ◽  
Vol 5 (S263) ◽  
pp. 98-101 ◽  
Author(s):  
Gonzalo C. de Elía ◽  
Romina P. Di Sisto ◽  
Adrián Brunini
Keyword(s):  
Size Distribution ◽  
Kuiper Belt ◽  
Primary Source ◽  
Mean Motion ◽  
Stability And Instability ◽  
The Stability ◽  
Mean Motion Resonance ◽  
Collisional Evolution

AbstractIn this work, we study the impactor flux on Pluto and Charon due to the collisional evolution of Plutinos.To do this, we develop a statistical code that includes catastrophic collisions and cratering events, and takes into account the stability and instability zones of the 3:2 mean motion resonance with Neptune. Our results suggest that if 1 Pluto-sized object is in this resonance, the flux of D = 2 km Plutinos on Pluto is ~4–24 percent of the flux of D = 2 km Kuiper Belt projectiles on Pluto. However, with 5 Pluto-sized objects in the resonance, the contribution of the Plutino population to the impactor flux on Pluto may be comparable to that of the Kuiper Belt. As for Charon, if 1 Pluto-sized object is in the 3:2 resonance, the flux of D = 2 km Plutinos is ~10–63 percent of the flux of D = 2 km impactors coming from the Kuiper Belt. However, with 5 Pluto-sized objects, the Plutino population may be a primary source of the impactor flux on Charon. We conclude that it is necessary to specify the Plutino size distribution and the number of Pluto-sized objects in the 3:2 Neptune resonance in order to determine if the Plutino population is a primary source of impactors on the Pluto-Charon system.

Planetesimals to planets: Numerical simulation of collisional evolution

Icarus ◽  
1978 ◽  
Vol 35 (1) ◽  
pp. 1-26 ◽  
Author(s):  
Richard Greenberg ◽  
John F. Wacker ◽  
William K. Hartmann ◽  
Clark R. Chapman
Keyword(s):  
Numerical Simulation ◽  
Collisional Evolution

Kinetic Modeling and Monte-Carlo Simulations of Droplet Coalescence in a Turbulent Gas Flow

2002 ◽  
Author(s):  
Philippe Villedieu ◽  
Olivier Simonin
Keyword(s):  
Numerical Simulation ◽  
Monte Carlo ◽  
Kinetic Model ◽  
Size Distribution ◽  
Density Function ◽  
Droplet Size ◽  
Gas Flow ◽  
Droplet Size Distribution ◽  
Monte Carlo Algorithm ◽  
Droplet Coalescence

Two-phase gas-droplet flows are involved in a lot of industrial applications, especially in the combustion field (Diesel engine, turbomachinery, rocket engine,…). Among all the characteristics of the spray, the droplet size distribution generally has a major influence on the global performances of the system and must be accurately taken into account in a numerical simulation code. This is a difficult task because the carrier gas flow is very often turbulent. Hence, droplets located in the vicinity of the same point may have different velocities and coalesce, leading at the end to a strong modification of the initial droplet size distribution. The first part of our contribution will be devoted to the presentation of a new kinetic model for droplet coalescence in turbulent gas flows. This model is an extension, to the case of sprays, of the ideas introduced by Simonin, Deutsch and Lavie´ville in [1]. The key ingredient is the use of the “joint density function”, fgp (t, x, r, v, u), representing the density of droplets at time t, located at point x, with radius r and velocity v and “viewing” an instantaneous turbulent gas velocity u. The great advantage of using fgp (t, x, r, v, u) instead of the usual density function fp (t, x, r, v) is the possibility to close the collision operator, in the governing kinetic equation, with less restrictive assumptions on the velocity correlations of two colliding droplets. The link between this model and the usual one (relying on the so-called “chaos assumption”) will be discussed. In the second part of our contribution, we shall present a new Monte-Carlo algorithm derived from our kinetic model. Numerical simulation results, for some academic test cases (homogeneous isotropic turbulence), will be shown and compared to the results obtained with a classical algorithm for droplet collision, based on the chaos assumption (see for example [2] or [3]). The figure 1 below shows a comparison between the temporal evolution of the mass mean radius computed by a classical collision model (neglecting the influence of gas and droplet velocity correlation) and by the “joint-pdf” based model. In the first case, the growth rate of the droplet, due to coalescence phenomena, is overestimated. Moreover, figure 2 shows that the droplet kinetic energy, induced by the turbulent gas motion, decays rapidly with the chaos assumption based model, as already noticed by Lavie´ville et al [1] in the case of solid particle collisions.

Numerical Simulation of Subcooled Flow Boiling Using a Bubble Tracking Method

2016 ◽  
Author(s):  
Tomio Okawa ◽  
Naoki Miyano ◽  
Kazuhiro Kaiho ◽  
Koji Enoki
Keyword(s):  
Numerical Simulation ◽  
Size Distribution ◽  
Void Fraction ◽  
Bubble Size ◽  
Flow Boiling ◽  
Bubble Nucleation ◽  
Bubble Size Distribution ◽  
Subcooled Flow Boiling ◽  
Tracking Method ◽  
Subcooled Flow

The process of bubble nucleation in subcooled flow boiling was visualized using a high speed camera to show that the bubble size can be significantly different between the nucleation sites. However, the bubble size is usually assumed constant in the numerical simulation of subcooled flow boiling. To explore the effect of the bubble size distribution on the void fraction in subcooled flow boiling, numerical simulations were performed using a bubble tracking method in which the size and position of each bubble are calculated individually using a Lagrangian coordinates. In the present simulation, the void fraction was greater when the bubble size distribution was taken into consideration. Since the bubble tracking method requires many correlations, further improvement is necessary. The present numerical results however indicate that the bubble size distribution should be taken in to consideration to evaluate the void fraction in subcooled flow boiling accurately.

Numerical simulation of the retrieval of aerosol size distribution from multiwavelength laser radar measurements

1989 ◽  
Vol 28 (24) ◽  
pp. 5259 ◽  
Author(s):  
Pu Qing ◽  
Hideaki Nakane ◽  
Yasuhiro Sasano ◽  
Shinzo Kitamura
Keyword(s):  
Numerical Simulation ◽  
Size Distribution ◽  
Laser Radar ◽  
Aerosol Size Distribution ◽  
Radar Measurements ◽  
Multiwavelength Laser

Numerical simulation of sub-cooled cavitating flow by using bubble size distribution

2003 ◽  
Vol 12 (4) ◽  
pp. 350-356 ◽  
Author(s):  
Yutaka Ito ◽  
Hideki Wakamatsu ◽  
Takao Nagasaki
Keyword(s):  
Numerical Simulation ◽  
Size Distribution ◽  
Bubble Size ◽  
Bubble Size Distribution ◽  
Cavitating Flow
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