scholarly journals Monte Carlo simulations of two-component drop growth by stochastic coalescence

2008 ◽  
Vol 8 (2) ◽  
pp. 7289-7313 ◽  
Author(s):  
L. Alfonso ◽  
G. B. Raga ◽  
D. Baumgardner
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Stochastic Algorithm ◽  
Aerosol Composition ◽  
Particle Charging ◽  
Two Component ◽  
Different Types ◽  
Framework Species ◽  
Stochastic Coalescence ◽  
Good Agreement

Abstract. The evolution of two-dimensional drop distributions is simulated in this study using a Monte Carlo method.~The stochastic algorithm of Gillespie (1976) for chemical reactions in the formulation proposed by Laurenzi et al. (2002) was used to simulate the kinetic behavior of the drop population. Within this framework species are defined as droplets of specific size and aerosol composition. The performance of the algorithm was checked by comparing the numerical with the analytical solutions found by Lushnikov (1975). Very good agreement was observed between the Monte Carlo simulations and the analytical solution. Simulation results are presented for bi-variate constant and hydrodynamic kernels. The algorithm can be easily extended to incorporate various properties of clouds such as including several crystal habits, different types of soluble CCN, particle charging and drop breakup.

scholarly journals Monte Carlo simulations of two-component drop growth by stochastic coalescence

2009 ◽  
Vol 9 (4) ◽  
pp. 1241-1251 ◽  
Author(s):  
L. Alfonso ◽  
G. B. Raga ◽  
D. Baumgardner
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Numerical Solutions ◽  
Initial Conditions ◽  
Stochastic Algorithm ◽  
Aerosol Composition ◽  
Aerosol Mass ◽  
Two Component ◽  
Framework Species ◽  
Stochastic Coalescence

Abstract. The evolution of two-dimensional drop distributions is simulated in this study using a Monte Carlo method. The stochastic algorithm of Gillespie (1976) for chemical reactions in the formulation proposed by Laurenzi et al. (2002) was used to simulate the kinetic behavior of the drop population. Within this framework, species are defined as droplets of specific size and aerosol composition. The performance of the algorithm was checked by a comparison with the analytical solutions found by Lushnikov (1975) and Golovin (1963) and with finite difference solutions of the two-component kinetic collection equation obtained for the Golovin (sum) and hydrodynamic kernels. Very good agreement was observed between the Monte Carlo simulations and the analytical and numerical solutions. A simulation for realistic initial conditions is presented for the hydrodynamic kernel. As expected, the aerosol mass is shifted from small to large particles due to collection process. This algorithm could be extended to incorporate various properties of clouds such several crystals habits, different types of soluble CCN, particle charging and drop breakup.

scholarly journals Universal dependence of the total number albedo of photons on the mean number of photon scatterings

2011 ◽  
Vol 26 (3) ◽  
pp. 249-253 ◽  
Author(s):  
Vladan Ljubenov ◽  
Rodoljub Simovic
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Analytic Functions ◽  
Least Squares Method ◽  
Mcnp Code ◽  
Initial Photon ◽  
Aluminum Iron ◽  
Universal Dependence ◽  
The Mean ◽  
Good Agreement

This paper presents the results of research on photon reflection from plane targets based on Monte Carlo simulations performed by the MCNP code. Five materials (water, concrete, aluminum, iron, and copper) are examined in the area of initial photon energies of up to 200 keV. The values of the total number albedo for photons dependent on the initial photon energy or the mean number of photon scatterings are calculated and graphically presented. We have shown that the values of the total number albedo for different target materials, expressed as a function of the mean number of photon scatterings, are in good agreement with each other and can be approximated by simple, universal analytic functions obtained by the least squares method. The accuracy of these analytic appoximations is confirmed by their comparison with the results of PENELOPE and FOTELP Monte Carlo codes.

Non-Equilibrium Critical Relaxation of Heisenberg Ferromagnets with Long-Range Correlated Defects

2012 ◽  
Vol 190 ◽  
pp. 39-42
Author(s):  
M. Medvedeva ◽  
Pavel V. Prudnikov
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Critical Behavior ◽  
Critical Exponents ◽  
Heisenberg Model ◽  
Three Dimensional ◽  
Initial State ◽  
Short Time ◽  
Theoretic Description ◽  
Good Agreement

The dynamic critical behavior of the three-dimensional Heisenberg model with longrangecorrelated disorder was studied by using short-time Monte Carlo simulations at criticality.The static and dynamic critical exponents are determined. The simulation was performed fromordered initial state. The obtained values of the exponents are in a good agreement with resultsof the field-theoretic description of the critical behavior of this model in the two-loopapproximation.

Kinetic Monte Carlo simulations of nanocolumn formation in two-component epitaxial growth

2010 ◽  
Vol 96 (7) ◽  
pp. 071913 ◽  
Author(s):  
Shu Zheng ◽  
Wenguang Zhu ◽  
Y. F. Gao ◽  
G. M. Stocks ◽  
Zhenyu Zhang
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Epitaxial Growth ◽  
Kinetic Monte Carlo ◽  
Two Component ◽  
Kinetic Monte Carlo Simulations

On the Estimation of the Kurtosis in Directional Sea States for Freak Wave Forecasting

2011 ◽  
Vol 41 (8) ◽  
pp. 1484-1497 ◽  
Author(s):  
Nobuhito Mori ◽  
Miguel Onorato ◽  
Peter A. E. M. Janssen
Keyword(s):  
Monte Carlo ◽  
Energy Distribution ◽  
Monte Carlo Simulations ◽  
Initial Conditions ◽  
Laboratory Data ◽  
Dispersion Effect ◽  
Freak Wave ◽  
Wave Forecasting ◽  
Directional Sea States ◽  
Good Agreement

Abstract Based on Monte Carlo simulations of the nonlinear Schrödinger equation in two horizontal dimensions, the dependence of the kurtosis on the directional energy distribution of the initial conditions is examined. The parametric survey is carried out to obtain the behavior of the kurtosis as function of the Benjamin–Feir index and directional spread in directional sea states. As directional dispersion effect becomes significant, the kurtosis monotonically decreases in comparison with the unidirectional waves. A parameterization of the kurtosis estimated from directional spectra is proposed here; the error of the parameterization is at most 10%. The parameterization is verified against laboratory data, and good agreement is obtained.

scholarly journals Effective Thermal Conductivity of Spherical Particulate Nanocomposites: Comparison with Theoretical Models, Monte Carlo Simulations and Experiments

2014 ◽  
Vol 13 (03) ◽  
pp. 1450022 ◽  
Author(s):  
Hatim Machrafi ◽  
Georgy Lebon
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Theoretical Models ◽  
Irreversible Thermodynamics ◽  
Flux Vector ◽  
Heat Flux Vector ◽  
The Matrix ◽  
The Status ◽  
Independent Variable ◽  
Good Agreement

The purpose of this work is to study heat conduction in systems that are composed out of spherical micro-and nanoparticles dispersed in a bulk matrix. Special emphasis will be put on the dependence of the effective heat conductivity on various selected parameters as dimension and density of particles, interface interaction with the matrix. This is achieved by combining the effective medium approximation and extended irreversible thermodynamics, whose main feature is to elevate the heat flux vector to the status of independent variable. The model is illustrated by three examples: Silicium-Germanium, Silica-epoxy-resin and Copper-Silicium systems. Predictions of our model are in good agreement with other theoretical models, Monte-Carlo simulations and experimental data.

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