Improving conversion and selectivity of catalytic reactions in bubbling gas-solid fluidized bed reactors by control of the nonlinear bubble dynamics

In this paper a model is presented that is a dynamic extension of the class ic two-phase reactor models used to predict conversion and selectivity of f luidized reactors. The most important part of the model is a dynamic discre te bubble model that can correctly predict bubble sizes and also exhibits c haotic dynamics. This bubble model is based on the discrete bubble models p resented by Clift and Grace [AlChE Symp. Ser. 66 (105) (1970) 14; 67 (116) (1971) 23; in: J.F Davidson, R. Clift, D. Harrison (Eds.), Fluidization, Ac ademic Press, London, 1985, p. 73] and Daw and Halow [AlChE Symp. Ser. 88 ( 289) (1992) 61]. The latter showed that this type of models can exhibit cha otic behavior. By application of an extended Version of Pyragas' control al gorithm [K. Pyragas, Phys. Lett. A 170 (1992) 421] the bubble dynamics can be changed from chaotic to periodic in a 'flow'-regime in which the model o therwise would predict chaotic behavior. Pyragas' control algorithm is used to synchronize a chaotic system with one of its periodic solutions using a feedback control loop. This results in smaller bubbles, thus enhancing mas s transfer of the reactant gas in the bubbles to the catalyst particles. Th e model is used to predict the effect of the changed bubble dynamics on a c atalytic reaction of industrial importance, viz. the ammoxidation of propyl ene to acrilnitril (Sohio process). It is shown that both conversion and se lectivity are appreciably enhanced. (C) 1999 Elsevier Science B.V. All righ ts reserved.