Modeling the Chemical Pollution of the Area by the Random-Addition Method

Abstract

Currently, a significant group of industrial facilities can be classified as chemically hazardous facilities (CHFs). To predict the spread of harmful impurities in the programs being developed, Gaussian and Lagrangian models are actively used, on the basis of which the complexes used both in the EMERCOM of Russia and in research organizations are being implemented. These complexes require the introduction of a large amount of information, including the characteristics of the wind field in the distribution of an emergency chemically hazardous substance, which limits their use. In systems, the formation of which is influenced by a large number of different random factors, spatial scaling (similarity) is often found, and one or another parameter can be described using the methods of fractal geometry, which in the past few decades has been actively and successfully applied to the description of various physical objects. The purpose of this study is to analyze the possibility of using the random-addition method for early prediction of the distribution of harmful impurities in the surface air layer during the short-term release of a substance on the surface as a result of an emergency.

Machine Learning Methods Based on Geophysical Monitoring Data in Low Time Delay Mode for Drilling Optimization

“…Vector measuring systems are highly efficient [40], [41], [42] and can be used to detect and locate geodynamic processes. This control method has a high noise immunity and sensitivity compared to fixing the amplitude parameters of the anomalous components of the electromagnetic field.…”