Several Reaction Engineering Problems On Horizontal Stirred Bed Reactor (HSBR) For Polypropylene

Horizontal stirred bed reactor (HSBR) for polypropylene production is one of the rapid developing gas-phase reactors. The flow pattern of catalysts is close to plug flow because of the special horizontal design of reactor and catalyst with excellent efficiency. Many high quality polypropylene products, including homo-polymers, random and impact copolymers, have been manufactured by HSBR. However, the reactor couldn't keep in high productivity and produce agglomeration frequently for this special plug flow characteristic. These problems affect the equipment a lot, including safety, stability, continuity, high quatity and quality. So it is imperative to make researches on operating characteristics of HSBR to realize the multiphase flow property of the reactor, and then optimize its action, increase the production rate and the capacity of the industry plant. Power consumption, distribution of bed level and flow pattern are the three essential operating characteristics in process design and engineering scale-up. Mastering those basic characteristics of HSBR is of great significance for equipment scale-up and process design. Therefore, it is not only very challenging but also of profound theoretical and practical significance to make research about these operating characteristics in HSBR.This thesis focuses on the following aspects: power consumption, distribution of bed level and flow pattern through experiment and theoretical analysis. In addition, two new detection methods by acoustic emission measurement have also been applied to the industry equipments. The main results in this article can be summarized as followed:(1) The researches about property of power consumption have been investigated and the models for predicting the stirring power consumption have been established, which shows good applicability for the selection of stirring motor in the industry instrument. Besides, some type-selecting suggestions about motor have also been thrown out.Three types of paddle have been chosen to investigate the influence of feeding coefficient, stirring speed, ventilation volume, powder properties and paddle structures on power consumption of the stirring paddle. The results show that power consumption is directly proportional to feeding coefficient and stirring speed respectively. It decreases by less than 10 % when ventilation is introduced into the reactor bottom. In addition, power consumption is closely related to particle bulk density and flow properties, and it decreases as the powder fluidity gets better. Based on the above discoveries, empirical correlations are established by introducing dimensionless variables of feeding coefficient, dimensionless speed, dimensionless feed, etc. and combining the powder property parameters. The relative deviation between prediction and industrial data is below 7 %. Therefore, the correlations can provide reliable predictions for power consumption of paddle in HSBR and they provide basis for the selection of stirring motor.(2) The characteristics of distribution of bed level have been studied and the models for calculating acclivitous angle of bed level have been found, which have good application for forecasting the acclivitous angle of bed level in HSBR.The relations between distribution of bed level in HSBR and feeding coefficient, stirring speed, powder properties, ventilation have been investigated based on three different paddles. It is found that, feeding coefficient, stirring speed and powder properties not only affect but also determine the acclivitous angle of bed level. The bed level basically remains the same when ventilation is introduced. Based on these discoveries, the model for predicting acclivitous angle of bed level is established by introducing dimensionless variables, including feeding coefficient, dimensionless speed, dimensionless feed, etc. The relative deviation between model prediction and industrial data is below 5%. Therefore, it can be applied to the calculation of acclivitous angle of bed level in HSBR.(3) Influences of operation conditions, particle fluidity and paddle type on RTD of HSBR have been experimented, and the RTD curves have been analyzed by adopting the model of n-CSTR in series and the back-mixing model.The researches about flow pattern of HSBR under different operating condition and particle fluidity have been worked out based on three different paddles. Study results show that, operation conditions, including feeding coefficient, stirring speed and rate of feeding and discharging, have influence on flow pattern in HSBR. Particle fluidity can also affect the flow pattern. Flow pattern of powder with poor fluidity is closer to plug flow. The back-mixing rate is the lowest for doorframe paddle and highest for blade paddle under the same operation condition.Meanwhile, the influence of inclination angle of baffle on RTD has also been investigated by taking doorframe paddle as an example. It is found that the average residential time of particles increases when baffle is introduced. The flow pattern of powder is closest to plug flow when the inclination angle of baffle is 18°.(4) Based on the principle that acoustic emission (AE) signal would be generated during collision of particles onto the wall, AE measurement has been adopted for detection of bed level with the analysis of mean-square deviation and agglomeration on the basis of power spectrum about auto-regression (AR) model in HSBR.Based on the principle that AE signal would be generated during collision of particles onto the wall, higher and lower bed level have been detected by multiple probes AE technology, and online detection of industrial plant has also been carried out. It is found that, the error produced by multiple probes AE method is less than 10%, and both of the distribution of high and low bed level can also be detected.At the same time, combining AR model and calculation of AR power spectrum of AE signal, the accurate agglomeration alarming and online fault diagnosis have been realized by comparing with spectrum under normal conditions and variance calculation, on basis of the mechanism that AE signals with different characteristic frequency band energy emitted when different sizes of particle impacted with the wall. Therefore, the convenient and non-violation real-time detection method for bed level measurement and the effective agglomeration detection method are invented.