The influence of the degree of back-mixing on hydrogen production in an anaerobic fixed-bed reactor

This paper reports on results obtained from experiments carried out in an acidogenic anaerobic reactor aiming at the optimization of hydrogen production by altering the degree of back-mixing. It was hypothesized that there is an optimum operating point that maximizes the hydrogen yield. Experiments were performed in a packed-bed bioreactor by covering a broad range of recycle ratios (R) and the optimum point was obtained for an R value of 0.6. In this operating condition the reactor behaved as 8 continuous stirred-tank reactors in series and the maximum yield was 4.22 mol H-2 mol sucrose(-1). Such optimum point was estimated by deriving a polynomial function fitted to experimental data and it was obtained as the conjugation of three factors related to the various degrees of back-mixing applied to the reactor: mass transfer from the bulk liquid to the biocatalyst, liquid-to-gas mass transfer and the kinetic behavior of irreversible reactions in series. Copyright (C) 2012, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.

OPTIMIZATION AND CONTROL OF A CONTINUOUS POLYMERIZATION REACTOR

This work studies the optimization and control of a styrene polymerization reactor. The proposed strategy deals with the case where, because of market conditions and equipment deterioration, the optimal operating point of the continuous reactor is modified significantly along the operation time and the control system has to search for this optimum point, besides keeping the reactor system stable at any possible point. The approach considered here consists of three layers: the Real Time Optimization (RTO), the Model Predictive Control (MPC) and a Target Calculation (TC) that coordinates the communication between the two other layers and guarantees the stability of the whole structure. The proposed algorithm is simulated with the phenomenological model of a styrene polymerization reactor, which has been widely used as a benchmark for process control. The complete optimization structure for the styrene process including disturbances rejection is developed. The simulation results show the robustness of the proposed strategy and the capability to deal with disturbances while the economic objective is optimized.

Optimization and control of a continuous polymerization reactor

This work studies the optimization and control of a styrene polymerization reactor. The proposed strategy deals with the case where, because of market conditions and equipment deterioration, the optimal operating point of the continuous reactor is modified significantly along the operation time and the control system has to search for this optimum point, besides keeping the reactor system stable at any possible point. The approach considered here consists of three layers: the Real Time Optimization (RTO), the Model Predictive Control (MPC) and a Target Calculation (TC) that coordinates the communication between the two other layers and guarantees the stability of the whole structure. The proposed algorithm is simulated with the phenomenological model of a styrene polymerization reactor, which has been widely used as a benchmark for process control. The complete optimization structure for the styrene process including disturbances rejection is developed. The simulation results show the robustness of the proposed strategy and the capability to deal with disturbances while the economic objective is optimized.