Simulation of exchange processes in multi-component environments with account of data uncertainty

Authors:
raw_author_name: Svitlana Gadetska
raw_affiliation_string: Харківський національний автомобільно-дорожній університет, Харків
raw_author_name: Valeriy Dubnitskiy
raw_affiliation_string: Харківський навчально-наукового інститут “Каразінський банківський інститут” Харківського національного університету ім. В. Н. Каразіна, Харків
raw_author_name: Yuri Kushneruk
raw_affiliation_string: Харківський національний університет Повітряних Сил імені Івана Кожедуба, Харків
raw_author_name: Yuriy Ponochovnyi
raw_affiliation_string: Полтавський державний аграрний університет, Полтава
raw_author_name: Alexander Khodyrev
raw_affiliation_string: Харківський навчально-науковий інститут “Каразінський банківський інститут” Харківського національного університету ім. В. Н. Каразіна, Харків

Abstract: The goal of the work. Proposals for methods of solving systems of linear homogeneous and non-homogeneous differential equations with constant and variable coefficients that defined in interval form and intended for modeling exchange processes in multicomponent environments. Research subject: systems of linear homogeneous and non-homogeneous differential equations with constant and variable coefficients defined in interval form. Research method: interval analysis. The obtained results. Systems of linear homogeneous and non-homogeneous differential equations, which are used in modeling exchange processes in multicomponent environments, are considered. Such systems can be considered, for example, in problems of chemical kinetics, materials science, and the theory of Markov processes. To obtain the solution of these equations, specialized calculators of analytical transformations were used and tested. The Matlab system (ode15s solver) was used for numerical analysis of systems of differential equations. It is shown that the application of interval methods of numerical analysis at the initial stage of system modeling has some advantages over probabilistic methods because they do not require knowledge of the laws of distribution of the results of the system state parameter measurements and their errors. It is shown that existing methods of solving systems of linear differential equations can be divided into two groups. Common to these groups is the use of interval expansion of classical methods for solving differential equations given in interval form. The difference between these two groups of methods is as follows. The methods of the first group can be used for all types of differential equations but require the creation of special software. The peculiarity of the methods of the second group is that they can be used to solve equations analytically or using numerical analysis packages. The application of the methods of the second group is shown on the example of solving a system of differential equations, the coefficients of which are determined in interval form. The system of these equations is intended for modeling the processes of exchange with the external environment of the elements of the model of a specific physical system. In the case when the coefficients of these equations are variables, their piecewise-constant approximation is applied and a criterion that determines the possibility of its application is given. The technique proposed in the paper can be applied to solve systems of linear homogeneous and non-homogeneous differential equations with constant and variable coefficients if they are given by slowly varying functions. In the case when the coefficients of the equations are determined in the interval form, the technique allows obtaining their solution also in the interval form and does not require the creation of special software.