Modelling and optimisation of oxidative desulphurization process for model sulphur compounds and heavy gas oil. Determination of Rate of Reaction and Partition Coefficient via Pilot Plant Experiment; Modelling of Oxidation and Solvent Extraction Processes; Heat Integration of Oxidation Process; Economic Evaluation of the Total Process.
AuthorKhalfalla, Hamza Abdulmagid
SupervisorMujtaba, Iqbal M.
Model sulphur compounds
Heavy gas oil
The University of Bradford theses are licenced under a Creative Commons Licence.
InstitutionUniversity of Bradford
DepartmentSchool of Engineering, Design and Technology
MetadataShow full item record
AbstractHeightened concerns for cleaner air and increasingly more stringent regulations on sulphur content in transportation fuels will make desulphurization more and more important. The sulphur problem is becoming more serious in general, particularly for diesel fuels as the regulated sulphur content is getting an order of magnitude lower, while the sulphur contents of crude oils are becoming higher. This thesis aimed to develop a desulphurisation process (based on oxidation followed by extraction) with high efficiency, selectivity and minimum energy consumption leading to minimum environmental impact via laboratory batch experiments, mathematical modelling and optimisation. Deep desulphurization of model sulphur compounds (di-n-butyl sulphide, dimethyl sulfoxide and dibenzothiophene) and heavy gas oils (HGO) derived from Libyan crude oil were conducted. A series of batch experiments were carried out using a small reactor operating at various temperatures (40 ¿ 100 0C) with hydrogen peroxide (H2O2) as oxidant and formic acid (HCOOH) as catalyst. Kinetic models for the oxidation process are then developed based on `total sulphur approach¿. Extraction of unoxidised and oxidised gas oils was also investigated using methanol, dimethylformamide (DMF) and N-methyl pyrolidone (NMP) as solvents. For each solvent, the `measures¿ such as: the partition coefficient (KP), effectiveness factor (Kf) and extractor factor (Ef) are used to select the best/effective solvent and to find the effective heavy gas oil/solvent ratios. A CSTR model is then developed for the process for evaluating viability of the large scale operation. It is noted that while the energy consumption and recovery issues could be ignored for batch experiments these could not be ignored for large scale operation. Large amount of heating is necessary even to carry out the reaction at 30-40 0C, the recovery of which is very important for maximising the profitability of operation and also to minimise environmental impact by reducing net CO2 release. Here the heat integration of the oxidation process is considered to recover most of the external energy input. However, this leads to putting a number of heat exchangers in the oxidation process requiring capital investment. Optimisation problem is formulated using gPROMS modelling tool to optimise some of the design and operating parameters (such as reaction temperature, residence time and splitter ratio) of integrated process while minimising an objective function which is a coupled function of capital and operating costs involving design and operating parameters. Two cases are studied: where (i) HGO and catalyst are fed as one feed stream and (ii) HGO and catalyst are treated as two feed streams. A liquid-liquid extraction model is then developed for the extraction of sulphur compounds from the oxidised heavy gas oil. With the experimentally determined KP multi stage liquid-liquid extraction process is modelled using gPROMS software and the process is simulated for three different solvents at different oil/solvent ratios to select the best solvent, and to obtain the best heavy gas oil to solvent ratio and number of extraction stages to reduce the sulphur content to less than 10 ppm. Finally, an integrated oxidation and extraction steps of ODS process is developed based on the batch experiments and modelling. The recovery of oxidant, catalyst and solvent are considered and preliminary economic analysis for the integrated ODS process is presented.
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Efficient Processing of Corneal Confocal Microscopy Images. Development of a computer system for the pre-processing, feature extraction, classification, enhancement and registration of a sequence of corneal images.Ipson, Stanley S.; Qahwaji, Rami S.R.; Ghanchi, Faruque; Elbita, Abdulhakim M. (University of BradfordCentre for Visual Computing, School of Engineering and Informatics, 2014-10-17)Corneal diseases are one of the major causes of visual impairment and blindness worldwide. Used for diagnoses, a laser confocal microscope provides a sequence of images, at incremental depths, of the various corneal layers and structures. From these, ophthalmologists can extract clinical information on the state of health of a patient’s cornea. However, many factors impede ophthalmologists in forming diagnoses starting with the large number and variable quality of the individual images (blurring, non-uniform illumination within images, variable illumination between images and noise), and there are also difficulties posed for automatic processing caused by eye movements in both lateral and axial directions during the scanning process. Aiding ophthalmologists working with long sequences of corneal image requires the development of new algorithms which enhance, correctly order and register the corneal images within a sequence. The novel algorithms devised for this purpose and presented in this thesis are divided into four main categories. The first is enhancement to reduce the problems within individual images. The second is automatic image classification to identify which part of the cornea each image belongs to, when they may not be in the correct sequence. The third is automatic reordering of the images to place the images in the right sequence. The fourth is automatic registration of the images with each other. A flexible application called CORNEASYS has been developed and implemented using MATLAB and the C language to provide and run all the algorithms and methods presented in this thesis. CORNEASYS offers users a collection of all the proposed approaches and algorithms in this thesis in one platform package. CORNEASYS also provides a facility to help the research team and Ophthalmologists, who are in discussions to determine future system requirements which meet clinicians’ needs.
Thermal homogeneity and energy efficiency in single screw extrusion of polymers. The use of in-process metrology to quantify the effects of process conditions, polymer rheology, screw geometry and extruder scale on melt temperature and specific energy consumptionKelly, Adrian L.; Brown, Elaine C.; Coates, Philip D.; Vera-Sorroche, Javier (University of BradfordFaculty of Engineering and Informatics, 2014)Polymer extrusion is an energy intensive process whereby the simultaneous action of viscous shear and thermal conduction are used to convert solid polymer to a melt which can be formed into a shape. To optimise efficiency, a homogeneous melt is required with minimum consumption of process energy. In this work, in-process monitoring techniques have been used to characterise the thermal dynamics of the single screw extrusion process with real-time quantification of energy consumption. Thermocouple grid sensors were used to measure radial melt temperatures across the melt flow at the entrance to the extruder die. Moreover, an infrared sensor flush mounted at the end of the extruder barrel was used to measure non-invasive melt temperature profiles across the width of the screw channel in the metering section of the extruder screw. Both techniques were found to provide useful information concerning the thermal dynamics of the extrusion process; in particular this application of infrared thermometry could prove useful for industrial extrusion process monitoring applications. Extruder screw geometry and extrusion variables should ideally be tailored to suit the properties of individual polymers but in practise this is rarely achieved due the lack of understanding. Here, LDPE, LLDPE, three grades of HDPE, PS, PP and PET were extruded using three geometries of extruder screws at several set temperatures and screw rotation speeds. Extrusion data showed that polymer rheology had a significant effect on the thermal efficiency on the extrusion process. In particular, melt viscosity was found to have a significant effect on specific energy consumption and thermal homogeneity of the melt. Extruder screw geometry, set extrusion temperature and screw rotation speed were also found to have a direct effect on energy consumption and melt consistency. Single flighted extruder screws exhibited poorer temperature homogeneity and larger fluctuations than a barrier flighted screw with a spiral mixer. These results highlighted the importance of careful selection of processing conditions and extruder screw geometry on melt homogeneity and process efficiency. Extruder scale was found to have a significant influence on thermal characteristics due to changes in surface area of the screw, barrel and heaters which consequently affect the effectiveness of the melting process and extrusion process energy demand. In this thesis, the thermal and energy characteristics of two single screw extruders were compared to examine the effect of extruder scale and processing conditions on measured melt temperature and energy consumption. Extrusion thermal dynamics were shown to be highly dependent upon extruder scale whilst specific energy consumption compared more favourably, enabling prediction of a process window from lab to industrial scale within which energy efficiency can be optimised. Overall, this detailed experimental study has helped to improve understanding of the single screw extrusion process, in terms of thermal stability and energy consumption. It is hoped that the findings will allow those working in this field to make more informed decisions regarding set conditions, screw geometry and extruder scale, in order to improve the efficiency of the extrusion process.
Novel medical imaging technologies for processing epithelium and endothelium layers in corneal confocal images. Developing automated segmentation and quantification algorithms for processing sub-basal epithelium nerves and endothelial cells for early diagnosis of diabetic neuropathy in corneal confocal microscope imagesQahwaji, Rami S.R.; Ipson, Stanley S.; Hammadi, Shumoos T.H. (University of BradfordSchool of Electrical Engineering and Computer Science, 2018)Diabetic Peripheral Neuropathy (DPN) is one of the most common types of diabetes that can affect the cornea. An accurate analysis of the corneal epithelium nerve structures and the corneal endothelial cell can assist early diagnosis of this disease and other corneal diseases, which can lead to visual impairment and then to blindness. In this thesis, fully-automated segmentation and quantification algorithms for processing and analysing sub-basal epithelium nerves and endothelial cells are proposed for early diagnosis of diabetic neuropathy in Corneal Confocal Microscopy (CCM) images. Firstly, a fully automatic nerve segmentation system for corneal confocal microscope images is proposed. The performance of the proposed system is evaluated against manually traced images with an execution time of the prototype is 13 seconds. Secondly, an automatic corneal nerve registration system is proposed. The main aim of this system is to produce a new informative corneal image that contains structural and functional information. Thirdly, an automated real-time system, termed the Corneal Endothelium Analysis System (CEAS) is developed and applied for the segmentation of endothelial cells in images of human cornea obtained by In Vivo CCM. The performance of the proposed CEAS system was tested against manually traced images with an execution time of only 6 seconds per image. Finally, the results obtained from all the proposed approaches have been evaluated and validated by an expert advisory board from two institutes, they are the Division of Medicine, Weill Cornell Medicine-Qatar, Doha, Qatar and the Manchester Royal Eye Hospital, Centre for Endocrinology and Diabetes, UK.