Session: 04-22 Combustion - Emissions II

Submission Number: 175930

Comparative Analysis of Gaussian and Burr Equivalence Ratio Distributions on Combustion and Emission Characteristics in a Gas Turbine Combustor 

The uniformity of fuel-air mixing is a key factor that determines the combustion performance and emission characteristics of gas turbine combustors. The mixing process is influenced by airflow patterns, fuel injection behavior, and combustor geometry, which together cause nonuniform distributions of the equivalence ratio. Traditional studies often assume that the probability distribution of the equivalence ratio follows a Gaussian profile to simplify analytical and numerical modeling. However, recent experimental observations show that the actual distribution frequently exhibits significant skewness, making the Gaussian model insufficient to represent real fuel-air mixing. Statistical fitting of reported experimental data indicates that the Burr distribution provides greater flexibility in describing the equivalence ratio distribution. The root-mean-square error (RMSE) of Burr fitting is considerably lower than that of the Gaussian model, demonstrating its potential advantage in representing realistic nonuniform mixing behavior.

In this study, a self-developed chemical equilibrium code based on the equilibrium constant method was employed to analyze combustion and emission characteristics under nonuniform equivalence ratio distributions. The model assumed that the equivalence ratio followed either a Gaussian or a Burr distribution, both having the same mean and standard deviation. To capture the statistical features of the distributions, Gaussian quadrature was applied within the 5th to 95th percentile range to calculate the gas composition and temperature at discrete points. These results were then weighted by their probability densities to obtain the overall combustion properties. The analysis focused on the effects of equivalence ratio, distribution type, standard deviation, and tail index on gas temperature, CO emission index, NOx emission index, and combustion efficiency.

The results show that as the standard deviation (s) of the equivalence ratio distribution increases from 0.05 to 0.30, indicating higher mixing nonuniformity, the CO emission index rises significantly, while the NOx emission index gradually decreases. The magnitude of these changes is closely related to the tail index of the distribution. Under low standard deviation conditions (s = 0.05–0.10), the gas temperature predicted by the Burr distribution is slightly higher than that from the Gaussian distribution, with a maximum difference of 2.48 K. As s increases, the average temperature under the Burr distribution becomes lower than that under the Gaussian distribution, reaching a maximum difference of 31.33 K. In addition, when the equivalence ratio is 0.8, the average gas temperatures from both distributions are relatively close, with a maximum difference of 10.97 K. However, at an equivalence ratio of 0.6, the temperature difference reaches its maximum of 31.33 K. The calculations also indicate that combustion efficiency decreases as the standard deviation increases, and the decline becomes more pronounced with stronger mixing nonuniformity.

This study systematically compares the effects of Gaussian and Burr equivalence ratio distributions on the combustion and emission characteristics of gas turbine combustors. The results reveal the sensitivity of combustion performance predictions to the shape of the equivalence ratio distribution. It is shown that the Burr distribution can more accurately represent the actual statistical characteristics of fuel-air mixing, thereby improving the predictive accuracy of combustion and emission models. The findings provide a theoretical basis for combustor design and optimization and introduce a new approach for evaluating combustion performance based on statistical distribution characteristics. This work offers valuable engineering insight for developing high-efficiency, low-emission constant-pressure combustion systems.

Presenting Author: Dong Ma School of Power and Energy, Northwestern Polytechnical University

Presenting Author Biography: Dong Ma is a PhD candidate at the School of Power and Energy, Northwestern Polytechnical University. His research focuses on high temperature rise combustor and multi-nozzle combustion organization technologies.

Authors:

Dong Ma School of Power and Energy, Northwestern Polytechnical University
Xin Chen School of Power and Energy, Northwestern Polytechnical University
Qiandong Li School of Power and Energy, Northwestern Polytechnical University
Jianqin Suo School of Power and Energy, Northwestern Polytechnical University
Hongxia Liang School of Power and Energy, Northwestern Polytechnical University
Yafeng Wu School of Power and Energy, Northwestern Polytechnical University