Synthesis of the Markov model of the thermochemical degradation of a polymer in solution

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The paper deals with the problem of mathematical modeling of thermochemical destruction process. The apparatus of Markov's chains is used to synthesize a mathematical model. The authors of the study suggest to consider the destruction process as a random one, where the system state changes, which is characterized by the proportion of macromolecules in each fraction of the molecular- and weight distribution. The intensities of transitions from one state to another characterize the corresponding rates of destruction processes for each fraction of the molecular- and weight distribution. The processes of crosslinking and polymerization in this work were neglected, and it was accepted that there is a probability of transition from any state with a lower order index (corresponding to fractions with higher molecular weights) to any state with a higher index (corresponding to fractions with lower molecular weights). Markov's chain with discrete states and continuous time was taken as the mathematical model basis. Interactive graphical simulation environment MathWorksSimulink was used as a simulation environment. Experimental studies of polybutadiene destruction in solution were carried out to evaluate the mathematical model parameters. The GPC (gel-penetration chromatography) data of the polybutadiene solution were used as the initial (starting) data for estimating the polymer WMD (molecular weight distribution). Mean-square deviation of the calculated data from the experimental data for each fraction and at specified times was minimized for the numerical search of parameter values. The results of comparison of experimental and calculated on mathematical model data showed an error of calculations on the average about 5%, which indicates an acceptable error in estimating of polymer fractions proportions change during the process of destruction for the process under consideration and conditions.

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Thermochemical destruction, markov chain, mathematical modeling

Короткий адрес: https://sciup.org/140229881

IDR: 140229881   |   DOI: 10.20914/2310-1202-2017-3-57-64

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