There is a growing need for secure, flexible and inexpensive energy across the world, however there is also a need to simultaneously curb emissions of greenhouse gasses and toxic pollutants. Fossil fuel combustion is expected to meet a significant portion the world's growing energy demand, however CO2 emissions need to be mitigated to avoid potentially catastrophic effects caused by global warming. Carbon capture and storage (CCS) technologies have been developed to permit the use of fossil fuel combustion in a future with strict controls over greenhouse gas emissions. CCS technologies are still yet to be deployed at large industrial scales, and it is necessary to reduce the efficiency overheads associated with CCS before the technology is economically feasible. Computational modelling can play a significant role in designing and optimising CCS technologies for power generation due to its flexibility and comparatively low costs. The work in this thesis develops and validates models for predicting mercury oxidation and thermal radiation under oxyfuel combustion conditions, which is a promising CCS technology that is competitively placed for large-scale implementation. The oxidation of mercury is a key chemical process in mitigating emissions of the toxic metal, and predicting the principal oxidation pathways will improve the design of control technologies. Thermal radiation, which is the most significant mode of heat transfer at combustion temperatures, is a very important physical mechanism for predicting many properties of combustion, such as gas temperatures, chemical reaction rates and heat fluxes, and thermal radiation models must accurately account for changes in the combustion environment. The models developed and validated in this thesis provide new approaches to predict mercury oxidation and thermal radiation under oxyfuel conditions. The results and conclusions from this work offer clear guidance on methods to model thermal radiation in oxyfuel conditions, and provide new insight on the mercury oxidation mechanism.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:684539 |
| Date | January 2016 |
| Creators | Clements, Alastair Greenman |
| Contributors | Pourkashanian, Mohamed ; Hughes, Kevin J. ; Ingham, Derek B. ; Gale, William F. ; Fairweather, Michael |
| Publisher | University of Leeds |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://etheses.whiterose.ac.uk/12594/ |
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