Modeling of Primary Reformer Tube Metal Temperature (TMT)

This report discusses the research done on the chosen topic, which is Modeling of
Primary Reformer Tube Metal Temperature (TMT). The objective of the project is to
develop a model that can predict the temperature of the reformer tubes. The scope of
study focused on the modeling of the primary reformer TMT of PETRONAS Ammonia
Sdn. Bhd. (PASB) plant. The primary reformer in PASB plant is used to crack
hydrocarbons such as natural gas into its constituents which are carbon dioxide, carbon
monoxide and hydrogen. Pressurized feed (30barg) of hydrocarbon and steam is fed into
the reformer tubes and heated by the burners at about 800-1 000°C to facilitate the
hydrocarbon conversion. The temperature of the tubes is an important parameter to
determine the life-time of the tubes. Operating the reformer beyond the TMT design
limits can cause premature failures on the tubes which lead to production losses and
higher downtime. Based on the literature survey, it shows that mathematical modeling
and simulation approaches are used to determine the behavior of the reformer tubes. For
this project, empirical model developed by integrating the process variable will be used
to predict the reformer tubes temperature. Empirical model is developed based on the
real-time data obtained from P ASB plant. There is none journals or papers that have used
this approach of modeling in predicting the primary reformer tubes temperature. Robust
Quality Estimator (RQE) and MATLAB (System Identification Toolbox and Neural
Network Toolbox) software are being used in developing models. Four types of model
are developed and compared; those are RQE Linear model, RQE RBF model, MATLAB
ARX model and MATLAB Neural Network model. Proper modeling techniques are
discussed and being implemented in developing each models. Neural Network model is
the best model developed in predicting the reformer TMT.