Introduction
This project focuses on developing a kinetic model for a complex chemical reaction using parallel optimization methods. The model design involves finding kinetic parameters that cannot be calculated analytically. Since the chemical reaction includes multiple stages, the optimization problem is multi-dimensional. The studied reaction is the catalytic isomerization of pentane-hexane fractions, which is now significant due to the shift in the oil refining industry towards gasoline production.
Process Description
The design of the kinetic model involves determining kinetic parameters that are not analytically computable. Given the multiple stages of the chemical reaction, the optimization problem has several extremum points. The reaction under consideration is the catalytic isomerization of the pentane-hexane fraction. Using existing industrial data on component concentrations and reactor outlet temperatures, activation energies and pre-exponential factors for each reaction stage have been calculated.
To solve the optimization problem, a parallel global search algorithm and a Lipschitz-based optimization program have been developed. The derived kinetic parameters enable the formulation of a mathematical model of the process that aligns well with industrial data.
Conclusion
This study presents a method for determining the kinetic parameters of a complex chemical reaction, specifically the catalytic isomerization of pentane-hexane fractions. The approach is based on a parallel optimization algorithm, and the results yield a suitable mathematical model for predicting the system’s behavior.
Simulation of Pentane-Hexane Isomerization Reactors in ACM Software
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