Industrial Methanol Reactor Dynamic Modeling and Optimization: Hybrid and Mechanistic Modeling and Optimal Control Dynamic Optimization

Considering higher price of oil converting natural gas to light petroleum products has been of great interest. This book tries to discuss converging natural gas to methanol in industrial scale reactor. The research focuses on mechanistic and grey box ( hybrid neural network model) modeling of reactor. Dynamic operation conditions of reactor have been obtained for indusial applications. The works first focuses on catalyst and tries to investigate different operating condition on catalyst performance using neural network modeling. The proposed method has great potential as a means to compensate for lack of the phenomenological kinetic modeling techniques. Next based on accurate neural network rate a hybrid model of industrial scale reactor is developed. In order to dynamic optimization of the reactor heterogeneous model of industrial reactor has been built. For the first time 2D, optimization of the industrial scale reactor has been presented. Optimum values for inlet temperature, composition and shell temperature as a function of time have been obtained based on dynamic optimization.