Predicting Kinetic Parameters of Acetylene Hydrogenation Reaction Via Optimization Techniques

In this study simulation and optimization of an industrial acetylene hydrogenation reactor was studied. Three well known kinetic models were used for a nearly similar catalyst to predict the industrial data. Due to the complexity of the reactions, none of the offered kinetic models could be considered as an exact kinetic model and it is necessary to determine the kinetic parameters. One of the best methods to determine the kinetic of a process is to simulate the process and then minimize the deviations between industrial data and calculated ones. Thus the hydrogenation reactor was simulated at the industrial operating conditions which were taken from an operational petrochemical plant and the optimum kinetic parameters were determined using optimization technique. Since such problem has many local optima, the genetic algorithm (GA) and simulated annealing (SA) methods were used to optimize the kinetic parameters of the three models. Due to the strong dependency of the GA performance on the GA condition, it was tried to investigate the effect of GA parameters on overall GA performance in detail. For this purpose, different GA parameters were used to solve the problem and results were discussed.