Combustion studies of poultry litter alone or mixed with peat by 50% on weight basis were undertaken in an atmospheric bubbling fluidised bed. Because of high moisture content of poultry litter, there was some uncertainty whether the combustion could be sustained on 100% poultry litter and as peat is very available in Ireland; its presence was considered to help to improve the combustion. However, the results showed that, as long as the moisture content of poultry litter was kept below 25%, the combustion did not need the addition of peat. The main parameters that were investigated are (i) moisture content, (ii) air staging, and (iii) variations in excess air levels along the freeboard. The main conclusions of the results are (i) combustion was influenced very much by the conditions of the fuel supply, (ii) the steady fuel supply was strongly dependent on the moisture content of the poultry litter, (iii) temperature appeared to be still very influential in reducing the levels of unburned carbon and hydrocarbons released from residues, (iv) the air staging in the freeboard improved combustion efficiency by enhancing the combustion of volatiles released from residues in the riser and (vi) NOx emissions were influenced by air staging in the freeboard. Particles collected from the bed and the two cyclones were analysed to determine the levels of heavy metals and the leachability tests were carried out with ashes collected to verify whether or not they could safely be used in agricultural lands.
Combustion in a boiler is too complex to be analytically described with mathematical models. To meet the needs of operation optimization, on-site experiments guided by the statistical optimization methods are often necessary to achieve the optimum operating conditions. This study proposes a new constrained optimization procedure using artificial neural networks as models for target processes. Information analysis based on random search, fuzzy c-mean clustering, and minimization of information free energy is performed iteratively in the procedure to suggest the location of future experiments, which can greatly reduce the number of experiments needed. The effectiveness of the proposed procedure in searching optima is demonstrated by three case studies: a bench-mark problem, namely minimization of the modified Himmelblau function under a circle constraint; both minimization of NOx and CO emissions and maximization of thermal efficiency for a simulated combustion process of a boiler; (3) maximization of thermal efficiency within NOxand CO emission limits for the same combustion process. The simulated combustion process is based on a commercial software package CHEMKIN, where 78 chemical species and 467 chemical reactions related to the combustion mechanism are incorporated and a plug-flow model and a load-correlated temperature distribution for the combustion tunnel of a boiler are used.
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