Stochastic Simulation and Single Events Kinetic Modeling: Application to Olefin Oligomerization

Abstract

In order to handle a tractable network for complex reaction systems such as oligomerization, stochastic tools are applied to reduce the reaction mechanism. The particularity of this work is that quantitative single event kinetic modeling constants are used to generate a network which correctly describes the dynamic behavior of the studied reacting system. By using the stochastic method, which is based on a probabilistic approach, we can avoid the generation of improbable reaction paths in order to reduce the network expansion. Comparison with a classical limited network shows that the proposed network generation technique can be more reliable. Alongside, the stochastic simulation algorithm can be used as a method of simulation instead of the deterministic method because of the huge size of the oligomerization network.