Kinetic modeling of oxidative dehydrogenation of propane (ODHP) over a vanadium–graphene catalyst: Application of the DOE and ANN methodologies

摘要: Abstract In this research the application of design experiment (DOE) coupled with artificial neural networks (ANN) in kinetic study oxidative dehydrogenation propane (ODHP) over a vanadium–graphene catalyst at 400–500 °C and method data collection/fitting for experiments were presented. The proposed reaction network composed consecutive simultaneous reactions kinetics expressed by simple power law equations involving total 20 unknown parameters (10 orders 5 rate constants each terms pre-exponential factors activation energies) determined through non-linear regression analysis. Because complex nature system, employed as an efficient accurate tool to model behavior system. Response surface methodology (RSM) ANN methods constructed based upon DOE's points then utilized generating extra-simulated data. three sets including original experimental data, those simulated RSM subsequently used fit expressions main ODHP side reactions. results modeling from models compared collected Both able satisfactorily which set showed best fitting amongst them all.