Monte Carlo methods are heuristic algorithms that use probabilities to select an outcome among several possible events in a given process. Monte Carlo methods are useful in polymer reaction engineering because they can predict the molecular architecture of polymers with details that cannot be easily captured by any other modeling technique. One of the advantages of Monte Carlo simulation is that one does not need to solve differential or algebraic equations to predict the microstructures of polymers. This article reviews the literature on steady‐state and dynamic Monte Carlo methods in polymer reaction engineering. We hope to convince the readers that playing dice regularly can be a great asset to polymer reactors engineers.
The steam reforming of methane is the main route for industrial production of hydrogen, used afterward for energy generation and production of chemicals. However, modeling of industrial methane reformers is not an easy task, due to the complex geometries of the employed catalyst pellets. The complex geometries are required to improve the contact between the gas phase and the solid catalyst. In this work a one-dimensional pseudohomogeneous model with axial mass and heat dispersion is used to model the tubular industrial reactors. The effect of the complex catalyst geometry of the pellets is considered with the help of empirical metamodels developed a priori for the effectiveness factors, based on CFD modeling of heat and mass balances inside pellets with different shapes and subject to distinct reactions conditions. It is shown that the proposed model can be successfully applied for simulation and design of industrial reformers, allowing for analysis of the effects introduced by distinct catalyst geometries on the performances of industrial operations.
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