Hydrotreating processes play a vital role in petroleum refineries to meet the increasing demand of transportation fuels. The recent trends in processing of heavier crudes with higher sulphur contents and more stringent product specifications for cleaner transportation fuels, such as ultra-low sulphur diesel, are resulting in more severe operating conditions and higher hydrogen consumption of hydrotreating processes. In order to carry out any revamp or design projects for improving the performance and efficiency of hydrotreating units molecular kinetic models of hydrotreating reactions may be required to provide detailed and accurate information of the composition and properties of hydrotreating products. The overall hydrotreating process consisting of the hydrotreater, the separation system and the associated heat recovery system need to be modelled on a consistent basis of detailed characterisation of petroleum fractions and the interactions of these individual subsystems with each other and with the refinery hydrogen network handled simultaneously for overall process optimisation. A molecular pathways level model of diesel hydrotreating reactions using the molecular type and homologous series matrix is employed for prediction of detailed molecular level information of composition and properties of diesel hydrotreating products. The molecular type and homologous series matrix representation of petroleum fractions is a detailed characterisation approach that represents the composition of a stream in a matrix in terms of the carbon number range and compound classes existing in the petroleum fraction. A new strategy is developed for estimation of physical properties of middle distillate and heavy petroleum fractions with molecular type and homologous series matrix representation using group contribution methods.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:498799 |
| Date | January 2009 |
| Creators | Ahmad, Muhammad Imran |
| Contributors | Zhang, Nan : Jobson, Megan |
| Publisher | University of Manchester |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://www.manchester.ac.uk/escholar/uk-ac-man-scw:228852 |
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