Real-Time Prediction of Lean Blowout using Chemical Reactor Network

Abstract

The lean blow-out (LBO) of gas turbine combustors is a concern that can limit the rate of descent for an aircraft, the maneuverability of military jets, and cause a costly and time-intensive reignition of land-based gas turbines. This work explores the feasibility of a model-based combustor monitoring for the real-time prediction of combustion system proximity to LBO. The approach makes use of (1) real-time temperature measurements in the reactor, coupled with (2) the use of a real-time chemical reactor network (CRN) model to interpret the data as it is collected. The approach is tested using a laboratory jet-stirred reactor (JSR), operating on methane at near atmospheric pressure. The CRN represents the reactor as three perfectly stirred reactors (PSRs) in series with a recirculation pathway, the model inputs include real-time reactor temperature measurements and mass flows of fuel and air. The goal of the CRN is to provide a computationally fast means of interpreting measurements in real time with regard to blowout proximity. The free radical concentrations and their trends and ratios are studied in each reactor zone. The results indicate that the hydroxyl radical maximum concentration moves downstream as the reactor approaches LBO. The ratio of hydroxyl radical concentrations in the jet region versus the recirculation region is proposed as a criterion for the LBO proximity. This real-time, model-based monitoring methodology sheds insight into combustion processes in aerodynamically stabilized combustors as they approach LBO.