Modeling, Simulation and Optimization of Dry Reforming of Methane Process by Using Artificial Neural Network and Genetic Algorithm

Dry reforming of methane is one of the main ways to produce syngas. A proper Kinetic model was employed for modeling of dry reforming reaction over Ni/Al2O3 in a fixed-bed catalytic reactor. In the simulation of the reactor, a one dimensional model is applied. After modeling and simulation, more than 100 data were obtained, these data used in Artificial Neural Network then a net was made and finally the optimization of H2/CO ratio by Genetic Algorithm was done. The flow rates which optimized by GA was used in the modeling that causes H2/CO ratio about one.