Use this URL to cite or link to this record in EThOS:
Title: Development of a prediction tool for utility boiler performance
Author: Rees-Gralton, Thomas Michael
ISNI:       0000 0004 2750 6781
Awarding Body: Cardiff University
Current Institution: Cardiff University
Date of Award: 2007
Availability of Full Text:
Access from EThOS:
Access from Institution:
Coal combustion looks set to continue in the near future, however, with the pressure being put on power generators, by the UK government, to reduce carbon emissions, ways of reducing CO2 emissions are constantly being sought Co-firing of biomass in pulverised coal-fired boilers is one possible solution. An investigation into this technology has been carried out with particular attention being paid to combustion modelling techniques. Following a comprehensive review of related literature two tasks were carried out the simulation of a 500kW downfired furnace using the FLUENT CFD code, and the development of a universal boiler performance prediction tool. During the CFD task, blends of 5%* and 10%th sewage sludge and pure coal were simulated. Particle impaction rates were predicted on two deposition probes however, the task highlighted the need to produce a high quality computational grid as part of the modelling process. In the second task empirical correlations, later to be replaced by artificial neural networks, were derived, which could predict the temperature profile, deposition performance and corrosion performance of a full-scale boiler. These models were tested using predictions for the 618MWth Langerlo boiler and the 1316MWth Cottham boiler, producing consistent results. These results were found to satisfy what was expected from the literature.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available