Dynamic sensing of blowout in turbulent CNG inverse jet flame

The present work focuses on the dynamic blowout sensing of compressed natural gas (CNG) turbulent inverse jet flame (IJF) based on the temporal CH∗ chemiluminescence signal acquired from the flame zone. The time varying CH∗ chemiluminescence signal exhibits lower fluctuation level for stable IJF. However, higher level of fluctuation in the temporal CH∗ intensity is observed as the IJF approaches blowout. In addition, the characterization of CH∗ chemiluminescence signature from IJF based on histogram and power spectral density are performed for delineating the stable and unstable IJF. Furthermore, a statistical parameter called normalized root mean square (NRMS), computed from the statistical analysis of CH∗ intensity signal is found to be effective in predicting the onset of blowout in CNG IJF. Apart from this, a methodology for sensing the proximity of blowout in CNG IJF is proposed based on NRMS which can be helpful in averting the unexpected blowout in IJF based combustion systems.