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An iterative Langevin solution for contaminant dispersion simulation using the Gram-Charlier PDF [An article from: Environmental Modelling and Software]
Description
This digital document is a journal article from Environmental Modelling and Software, published by Elsevier in 2005. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.
Description:
An alternative numerical method to solve the three-dimensional stochastic Langevin equation applied to the air pollution dispersion is proposed and tested. We obtain a first-order differential equation whose solution is known and determined by an integrating factor. A Langevin model for inhomogeneous turbulence is obtained, considering the Gram-Charlier Probability Density Function (PDF) of turbulent velocity. The calculus process is based on an iterative scheme through the Picard Iterative Method. Numerical simulations and comparisons with measured data from two different tracer experiments are realized, showing a good agreement between predicted and observed values. Furthermore, the results obtained with the new approach are compared with the ones obtained by three different models.
Description:
An alternative numerical method to solve the three-dimensional stochastic Langevin equation applied to the air pollution dispersion is proposed and tested. We obtain a first-order differential equation whose solution is known and determined by an integrating factor. A Langevin model for inhomogeneous turbulence is obtained, considering the Gram-Charlier Probability Density Function (PDF) of turbulent velocity. The calculus process is based on an iterative scheme through the Picard Iterative Method. Numerical simulations and comparisons with measured data from two different tracer experiments are realized, showing a good agreement between predicted and observed values. Furthermore, the results obtained with the new approach are compared with the ones obtained by three different models.
