Abstract

Increased global demand for cleaner energy production and growing concern about using fossil fuels have urged many researchers to focus their work on developing more efficient and flexible combustion processes. In this regard, a FLOX®-based liquid fuel single-nozzle burner is investigated for use in a Capstone C30 micro gas turbine (MGT). The main advantages of FLOX®-based combustor systems are their decreased NOx emissions and increased fuel flexibility. An atmospheric test rig is set up to investigate the behavior of the FLOX®-based liquid fuel burner under the influence of the hot gas. The circulating gas in the C30 annular combustion chamber is emulated by hot cross-flow gas generated by a 20-nozzle FLOX®-based natural gas burner operated on a separate horizontal test rig. The variation and combination of the process parameters of both burners are done systematically according to Design of Experiments (DOE) as a statistical design methodology. DOE methodology is adopted rather than the conventional one-factor-at-a-time (OFAT) strategy, as DOE considers any possible interaction between the factors and reduces the number of experiments. Employing statistical design of experiments allows determining which input variables are responsible for the observed changes in the response, developing a model relating the response to the important input variables, and using this model for improving the combustor system. The results are subsequently run through the Analysis of Variance (ANOVA) in order to allow for an objective conclusion about the effect of the factors on the selected responses, which include mass flow rate (·fuel) and global air equivalence ratio (λ) of both of the liquid and natural gas burners. The hot gas cross-flow interaction with the liquid fuel burner is assessed through analyzing exhaust gas emissions and averaged flame OH*-chemiluminescence images. The models developed by the DOE method can be used to estimate the emissions and the flame geometrical properties of any other operating points that are not explicitly tested.

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