Prediction of NOx Emissions of H2/CO/CH4 Syngas in a

Abstract

Recently, the interests for energy depletion and rapid climate change have emerged around the world. To address the problems, the clean coal technology and research have been conducted actively. The business, which gasification accounting for a large proportion of the technology, has been performed in USA, China, Korea, etc. Gasification technology can generate synthetic gas from solid coal through carbon capture and storage technique (CCS). However, the study is not enough to investigate the combustion characteristics still. In this study, combustion experiment was performed to investigate the combustion characteristics for H2/CO/CH4 syngas in the partially premixed model gas turbine combustor equipped GE 7EA nozzle. Chemiluminescence measurements were performed to study the flame structure and characteristics of syngas combustion over equivalence ratio 0.7 to 1.3. Abel inversion method was applied to obtain 2-D chemiluminescence flame images from 3-D accumulated chemiluminescence image. EINOx was measured to investigate the relation with flame structure. EINOx related to the flame length and flame temperature. Artificial neural networks (ANN) process was employed to establish the EINOx prediction modeling. OH*, CH* and C2* overlapped chemiluminescence image was more accurate to estimate the EINOx for H2/CO/CH4 various syngas compositions from the ANN results. As well, most effectiveness of the EINOx concentration was order of flame temperature, flame length and mass flow rate.