Steam methane reformers are used in industry to convert natural gas and steam into hydrogen, carbon dioxide and carbon monoxide. In order to operate a reformer efficiently and safely its behaviour needs to be understood. A numerical model has been developed in Python to replicate the reformer behaviour. The model considers reaction kinetics, pressure drop heat transfer and diffusion limitations within the catalysts. Data from industrial reformers will be used to regress model parameters.

Carbon can form on the catalyst surface at some operating conditions which can cause the catalyst to be less active and the whole reformer to run less efficiently. This process is known as coking. If the carbon is concentrated in one location in the reformer tubes a hot spot can develop which can be a safety concern. While some carbon can be removed with steam, the catalysts need to be replaced once there is too much carbon build-up. Carbon formation is predicted in the Python model using both thermodynamic and kinetic methods. The impact of catalyst deactivation will be replicated in the model to demonstrate the effect on reformer performance.