Development of a model for auto-ignition delays and its use for the prediction of premix combustion reliability

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TitreDevelopment of a model for auto-ignition delays and its use for the prediction of premix combustion reliability
Type de publicationConference Paper
Year of Publication2016
AuteursBounaceur R, Glaude P-A, Sirjean B, Fournet R, Montagne P, Vierling M, Moliere M
Conference NamePROCEEDINGS OF THE ASME TURBO EXPO: TURBINE TECHNICAL CONFERENCE AND EXPOSITION, 2016, VOL 4B
PublisherInt Gas Turbine Inst
Conference LocationTHREE PARK AVENUE, NEW YORK, NY 10016-5990 USA
ISBN Number978-0-7918-4976-7
Résumé

Except in diesel engine applications, auto-ignition is an unwanted event from a general safety and reliability standpoint. It is especially undesirable in the premixing process involved in most low NOx combustion technologies. Therefore, in addition to auto-ignition temperature, auto ignition delay (AID) is a key data for the design of modern combustors including gas turbine ones. The authors have investigated the detailed kinetic mechanisms leading to auto ignition and established practical AID correlations involving the fuel composition, its temperature, pressure and equivalence ratio. The correlations brought about during this program offer a good reconciliation between calculated and experimental AID through a wide range of fuel composition, initial temperature and pressure. Validations were mainly done against data acquired with experimental setups consisting in shock tubes and rapid compression machines. The auto-ignition delay times of methane, pure light alkanes and various blends representative of several natural gas and process-derived fuels have been reviewed. For each fuel mixture, this study procures a simple equation linking the auto-ignition delay time to the temperature, pressure and equivalence ratio. As a direct application of this work, the authors have evaluated the risk of auto ignition in the premixing zone of a combustor characterized by a residence time and an associated probability density function. The results of this simulation stress the key role of larger hydrocarbon in the risk of flash-back events.