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2003•Chemical Engineering EducationRequires access

INTRODUCING THE STOCHASTIC SIMULATION OF CHEMICAL REACTIONS Using the Gillespie Algorithm and MATLAB

Joaquín Martínez Urreaga, José Mira, Camino Gonzáles-Fernández

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Abstract

This paper illustrates the numerical (stochastic and deterministic) simulation of the AB equilibrium process as a suitable tool for introducing the stochastic modeling of chemical reactions. The Gillespie algorithm was selected for the stochastic simulation. Students can develop their own MATLAB programs to simulate the process and then use the results to discover the main differences between the stochastic and deterministic simulation. Two free commercial simulation programs are also proposed as an auxiliary tool for extending the stochastic simulation to other reactions.

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What this paper is about

This paper illustrates the numerical (stochastic and deterministic) simulation of the AB equilibrium process as a suitable tool for introducing the stochastic modeling of chemical reactions. The Gillespie algorithm was selected for the stochastic simulation. Students can develop their own MATLAB programs to simulate the process and then use the results to discover the main differences between the stochastic and deterministic simulation. Two free commercial simulation programs are also proposed as an auxiliary tool for extending the stochastic simulation to other reactions.

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OpenAlex reports 5 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

This paper illustrates the numerical (stochastic and deterministic) simulation of the AB equilibrium process as a suitable tool for introducing the stochastic modeling of chemical reactions. The Gillespie algorithm was selected for the stochastic simulation. Students can develop their own MATLAB programs to simulate the process and then use the results to discover the main differences between the stochastic and deterministic simulation. Two free commercial simulation programs are also proposed as an auxiliary tool for extending the stochastic simulation to other reactions.

Key concepts: Stochastic simulation, MATLAB, Computer science, Process (computing), Deterministic simulation, Stochastic process, Algorithm, Stochastic modelling

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