On The Statistical Probablistic Modelling Of The Diffusion Of Fine Solid Materials

Abstract

A complex methodology is proposed in this paper for studying the transport and diffusion processes of fine solid materials that occur in both air and water following the extraction of mineral resources. The behaviour, dispersion and fate of such materials are closely linked to their potential for environmental pollution. Therefore, a study of the above-mentioned processes would shed light on ways in which such pollution could be alleviated or eliminated.

To begin with, a simple procedure is developed for processing the synoptic observed data and for creating a database of climatic information on the region of interest. Discussion then moves on to the simulation of synoptic episodes using the Monte-Carlo technique, based on the consistent patterns emerging from the database. In the case of dust, this permits the modelling of the climatic main flows of air and of the pollutants that are time-dependent and heterogeneous in space. An algorithm is then presented for calculating pulsation of the main flow that allows the modelling of the diffusion process of fine solid material using, once again, the Monte-Carlo method.

Finally the results of three series of numerical experiments are discussed. It is shown that the proposed methodology can be used to predict the time it would take the experimental basins to self-cleanse themselves of the suspended solid pollutants at different concentrations.