Based on the reported reaction networks,a novel six-component hydroisomerization reaction net-work with a new lumped species including C_(8)-naphthenes and C_(8)-paraffins is proposed and a kinetic model for a commerc...Based on the reported reaction networks,a novel six-component hydroisomerization reaction net-work with a new lumped species including C_(8)-naphthenes and C_(8)-paraffins is proposed and a kinetic model for a commercial unit is also developed.An empirical catalyst deactivation function is incorporated into the model accounting for the loss in activity because of coke forma-tion on the catalyst surface during the long-term opera-tion.The Runge-Kutta method is used to solve the ordinary differential equations of the model.The reaction kinetic parameters are benchmarked with several sets of balanced plant data and estimated by the differential vari-able metric optimization method(BFGS).The kinetic model is validated by an industrial unit with sets of plant data under different operating conditions and simulation results show a good agreement between the model predic-tions and the plant observations.展开更多
基金This work was supportedby the NationalCreative Research Groups Science Foundation of China(No.60421002)Priority supported financially by the“New Century 151 Talent Project”of Zhejiang Province.
文摘Based on the reported reaction networks,a novel six-component hydroisomerization reaction net-work with a new lumped species including C_(8)-naphthenes and C_(8)-paraffins is proposed and a kinetic model for a commercial unit is also developed.An empirical catalyst deactivation function is incorporated into the model accounting for the loss in activity because of coke forma-tion on the catalyst surface during the long-term opera-tion.The Runge-Kutta method is used to solve the ordinary differential equations of the model.The reaction kinetic parameters are benchmarked with several sets of balanced plant data and estimated by the differential vari-able metric optimization method(BFGS).The kinetic model is validated by an industrial unit with sets of plant data under different operating conditions and simulation results show a good agreement between the model predic-tions and the plant observations.
