This thesis explores the application of an advanced on line measurement technique in the control of a chemical process. The research explores emulsion fonnulation in an Oscillatory Baffied Reactor (OBR) by measurement using Electrical Impedance Tomography (EIT) technique. The research demonstrates new tools allowing emulsification methods for the precision manufacture of emulsions in the OBR through advanced online monitoring instrumentation. Experimental work demonstrated the production of water-in-oilJoil-in-water emulsions whilst simultaneously monitoring the process in the OBR using EIT. The development of a non intrusive method to visualise the evolution of the emulsion in the OBR using EIT is described. Experimental work demonstrated the capability to relate quantitatively the data obtained from the EIT measurement with . . the characteristic flow pattern in the OBR and the degree ofmixing of the emulsion. The use of cross correlation method is discussed to obtain average velocity profiles of the flow in applications using EIT as a measurement technique. A CFD simulation of the process was developed to compare~and validate the results from the . EIT measurement and the cross correlation application. The results indicated a good agreement between the results obtained from the different methods was achieved. The analysis of the distribution of droplet size in the OBR was carried out. The decreasing evolution of the droplet size and the standard deviation of droplets in the OBR were modelled. The results of the fitted correlation' demonstrated a precise fitting ofthe experimental values (R2= 0.8865 in the worst case). A statistical method is applied to reduce and select the most relevant data from the EIT measurement. The application of principal component analysis (PCA) to the EIT data demonstrated the capability to represent accurately 90% of the variability of the conductivity values of316 pixels with only 10 values (principal components). A neural network was developed using the data obtained from the PCA as input. The simulation of a feed forward neural network based on the PCA in order to obtain the coefficient of variance (CV) of the droplet size distribution showed good results. The average error found for the simulated average droplet size was less than 10%. This guaranteed a good level of accuracy and robustness of the neural network developed. . The research in this thesis demonstrates successfully a novel methodology of advanced on line measurement and analysis of the characteristics of an emulsion in the OBR. This research facilitates the formulation and monitoring of new emulsion products in the OBR and its statistical analysis on a continuous basis using EIT. The methods developed could have applications for monitoring the production of other and more complex multiphase formulations, using semi-continuous reactors.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:490849 |
| Date | January 2008 |
| Creators | Uso, Gregorio Vilar |
| Publisher | University of Leeds |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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