To overcome the disadvantages of the rotating bed available in open literature, a novel kind of high gravity device-rotating zigzag bed (RZB) was developed, which exhibits many superior features owing to its unique rotor combining a rotational part with a stationary one. The outstanding characteristics of RZB are its capability of middle-feed and easily realizing multirotor configuration in one unit by simply installing multiple rotors along the same axis. Thus one unit of RZB can be applied to continuous distillation processes with a higher mass transfer capacity. A preliminary test of mass transfer performance of the RZB in a pilot-scale system using methanol-water was carried out in this study. Experimental results show its excellent mass transfer behavior with an acceptable pressure drop. Comparison with rotating packing bed (RPB) shows that RZB provides equivalent mass transfer efficiency to RPB but exhibits excellent operability with a higher turndown ratio than that of RPB. Comparison with valve tray indicates that the baffle efficiency of RZB is slightly lower than the plate efficiency of valve tray. But if the difference between the tray space and baffle space is taken into consideration, RZB provides much higher efficiency than that of valve tray. Therefore the RZB is a kind of high efficiency gas-liquid contactor and a promising alternative in chemical process industries.
A new kinetic model for commercial unit of toluene disproportionation and C 9-armatiocs transalkylation is developed based on the reported reaction scheme. A time based catalyst deactivation function taking weight hourly space velocity (WHSV) into account is incorporated into the model, which reasonably accounts for the loss in activity because of coke deposition on the surface of catalyst during long-term operation. The kinetic parameters are benchmarked with several sets of balanced plant data and estimated by the differential variable metric optimization method. Sets of plant data at different operating conditions are applied to make sure validation of the model and the results show a good agreement between the model predictions and plant observations. The simulation analysis of key variables such as temperature and WHSV affecting process performance is discussed in detail, giving the guidance to select suitable operating conditions.
To investigate time-variant and nonlinear characteristics in industrial processes, a soft sensor modelling method based on time difference moving-window recursive partial least square (PLS) and adaptive model updating is proposed. In this method, time difference values of input and output variables are used as training samples to construct the model, which can reduce the effects of the nonlinear characteristic on modelling accuracy and retain the advantages of recursive PLS algorithm. To solve the high updating frequency of the model, a confidence value is introduced, which can be updated adaptively according to the results of the model performance assessment. Once the confidence value is updated, the model can be updated. The proposed method has been used to predict the 4-CBA (i.e. carboxy-benz-aldehyde) content in the PTA (i.e. purified terephthalic acid) oxidation reaction process. The results show that the proposed soft sensor modelling method can reduce computation effectively, improve prediction accuracy by making use of process information and reflects the process characteristics accurately.
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