Monte-carlo simulation of auto- and cross-correlated turbulent velocity fluctuations (MC-LAGPAR II model)

Abstract This paper discusses the application of Monte-Carlo Lagrangian particle models for the simulation of turbulent dispersion phenomena in the atmosphere. This type of modeling approach requires a numerical scheme for the stochastic generation of wind fluctuations. A new, fully three-dimensional, Monte-Carlo scheme is proposed here which is able to generate wind fluctuations with a specified degree of auto- and cross-correlation. All three spatial cross-correlations are included in the numerical scheme. This numerical method has been programmed using the APL language (MC-LAGPAR 11 model) and successfully tested. The listing of the key APL computational routine is presented and provides an example of the flexibility and computational power of the APL compact notation.

[1]  M. Raupach,et al.  Markov-chain simulation of particle dispersion in inhomogeneous flows: The mean drift velocity induced by a gradient in Eulerian velocity variance , 1982 .

[2]  B. J. Legg,et al.  Turbulent dispersion from an elevated line source: Markov chain simulations of concentration and flux profiles , 1983 .

[3]  D. Thomson,et al.  Calculation of particle trajectories in the presence of a gradient in turbulent-velocity variance , 1983 .

[4]  Ruwim Berkowicz,et al.  Monte Carlo simulation of plume dispersion in the convective boundary layer , 1984 .

[5]  R. Davis.  On relating Eulerian and Lagrangian velocity statistics: single particles in homogeneous flows , 1982, Journal of Fluid Mechanics.

[6]  Paolo Zannetti.  New Monte Carlo scheme for simulating Lagranian particle diffusion with wind shear effects , 1984 .

[7]  Rudolf B. Husar,et al.  Monte Carlo Simulation of Daily Regional Sulfur Distribution: Comparison with SURE Sulfate Data and Visual Range Observations during August 1977 , 1981 .

[8]  R. Lange,et al.  ADPIC—A Three-Dimensional Particle-in-Cell Model for the Dispersal of Atmospheric Pollutants and its Comparison to Regional Tracer Studies , 1978 .

[9]  R W Hockney,et al.  Computer Simulation Using Particles , 1966 .

[10]  Steven R. Hanna,et al.  Lagrangian and Eulerian Time-Scale Relations in the Daytime Boundary Layer , 1981 .

[11]  D. T. Smith,et al.  Random-walk simulation of gradient-transfer processes applied to dispersion of stack emission from coal-fired power plants , 1982 .

[12]  Anne J. Ley,et al.  A random walk simulation of two-dimensional turbulent diffusion in the neutral surface layer , 1982 .

[13]  C. W. Watson,et al.  Monte Carlo simulation of the turbulent transport of airborne contaminants , 1975 .

[14]  G. W. Thurtell,et al.  Numerical simulation of particle trajectories in inhomogeneous turbulence, I: Systems with constant turbulent velocity scale , 1981 .