Open AccessComplex modeling of installation for thermal processing of organic compounds
Author(s) -
N. A. Zroychikov,
С. А. Фадеев,
А. А. Каверин
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1370/1/012040
Subject(s) - combustion , pyrolysis , decomposition , process engineering , process (computing) , thermal decomposition , heat exchanger , thermal , environmental science , fluent , mechanical engineering , computer science , waste management , nuclear engineering , materials science , computer simulation , engineering , simulation , chemistry , thermodynamics , physics , organic chemistry , operating system
This paper presents the results of a numerical study of an installation for the thermal decomposition of organic substances by pyrolysis. Unlike with combustion, pyrolysis allows the processing of toxic and infected substances with high environmental safety. However, at the pre-project phase, difficulties often arise due to the lack of preliminary data relating to the decomposition process, the combustion of pyrolysis products, the intensity of heat exchange in the reactor and the combustion chamber. A possible solution to the problem may be pre-project computer simulation. In this paper, the ANSYS Fluent software program was used to simulate the installation of pyrolysis of moistened plastic, in which heat is supplied to the material through a heating wall. To maintain the process, the heat of combustion of its decomposition products is used. An approach of reducing the two-phase problem to a single-phase one is proposed, which allows minimizing the calculation time and increasing the convergence of the solution. Based on calculation results, the distribution of velocity fields, temperatures, heat fluxes and concentrations of substances in the installation was obtained. Calculation results allow to optimize the installation design and predict its capacity.