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Knowledge for Ignition, Acoustics and Instabilities


For the time being, the European engine industry does not have at its disposal methodologies adapted to predict the unsteady behaviour of low NOx combustors. Consequently and in order to be able to set up the development of low NOx technologies, KIAI will deliver reliable unstationary CFD tools which will allow a deep comprehension of unsteady phenomena. The main objective of the KIAI project is to provide reliable methodologies to predict the stability of industrial low NOx combustors, as well as their ignition process from spark to annular combustion. When used at an early stage in the conception cycle of low NOx combustors, KIAI CFD methodologies will play a key role and considerably accelerate the delivery process of lean combustion technology with a proven capability to reach the 80% NOx emissions reduction required for introduction into service before 2020 with the necessary reliability, safety and economical viability. As already demonstrated by past and ongoing studies and European projects, low NOx technologies lead to crucial unsteady phenomena that are neither controlled nor predictable at the moment. The scientific objectives of KIAI are directly linked to a better understanding and prediction of these unsteady phenomena: 1) Predict the coupling between the acoustics and the flame. 2) Determine the acoustic boundary conditions of multiperforated plates surrounding the combustion chamber; 3) Account for non-premixed spray flows in the combustion process; 4) Explore aerodynamic unsteadiness in strutted pre-diffusers adapted to high mass flow injectors and develop a liquid film break-up model for an injector; 5) Evaluate the sensitivity of LES predictions to small technological variations of geometry

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Bvd du general martial valin 2
75015 Paris

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Ile-de-France Ile-de-France Paris
Type d’activité
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Contact administratif
Patrick Houel (Mr.)
Contribution de l’UE
Aucune donnée

Participants (17)