Multivariate Testing for Mechanistic Insight in a Model Industrial Natural Gas Fired Burner

A statistical design methodology, commonly referred to as multivariate optimization or design of experiments, is applied to optimize the NOx and CO emissions from a model industrial, natural gas-fired burner. The multivariate approach incorporates testing of several input variables, or factors, at two levels (high and low) to determine the effect on the selected emissions, or responses. The factors for this optimization are the fuel jet injection velocity, number of fuel jets, air cross-flow velocity, air swirl intensity, and fuel jet axial location. The measured responses are NOx and CO emissions. In order to keep the dilution rate constant, all of the experiments were conducted at a constant excess air level of 10%. The results indicate that NOx emissions are predominantly affected by the cross-flow velocity, premixing distance, and swirl intensity. The CO emissions are affected by an interaction between the cross-flow velocity and swirl intensity. In this study, the jet velocity did not show a statistical affect on either the NOx or CO emissions.