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research-article

PREDICTION OF CO AND NOx POLLUTANTS IN A STRATIFIED BLUFF BODY BURNER

[+] Author and Article Information
Pascal Gruhlke

Chair of Fluid Dynamics, Institute for Combustion and Gas Dynamics, University of Duisburg-Essen, Duisburg, 47057, Germany
pascal.gruhlke@uni-due.de

Fabian Proch

Chair of Fluid Dynamics, Institute for Combustion and Gas Dynamics, University of Duisburg-Essen, Duisburg, 47057, Germany
fabian.proch@uni-due.de

Andreas Kempf

Chair of Fluid Dynamics, Institute for Combustion and Gas Dynamics, University of Duisburg-Essen, Duisburg, 47057, Germany
andreas.kempf@uni-due.de

Stefan Dederichs

Siemens AG, Muelheim an der Ruhr, 45473, Germany
stefan.dederichs@siemens.com

Christian Beck

Siemens AG, Muelheim an der Ruhr, 45473, Germany
beckchristian@siemens.com

Enric Illana Mahiques

Queen Mary University of London, London E1 4NS, United Kingdom
e.illanamahiques@qmul.ac.uk

1Corresponding author.

ASME doi:10.1115/1.4039833 History: Received June 08, 2017; Revised July 05, 2017
Article

Abstract

The major exhaust gas pollutants from heavy duty gas turbine engines are CO and NOx. The difficulty of predicting the concentration of these combustion products originates from their wide range of chemical time scales. In this paper, a combustion model that includes the prediction of the carbon monoxide and nitric oxide emissions is tested. Large eddy simulations (LES) are performed using a compressible code (OpenFOAM). A mod ified flamelet generated manifolds (FGM) approach is applied with a thickened flame approach (ATF) to resolve the flame on the numerical grid, with a flame sensor to ensure that the flame is only thickened in the flame region. For the prediction of the CO and NOx emissions, pollutant species transport equations and a second, CO based, progress variable are introduced for the flame burnout zone to account for slow chemistry effects. For the validation of the models, the Cambridge burner of Sweeney and Hochgreb [1, 2] is employed, as both carbon monoxide and nitric oxide [3] data is available.
Siemens AG
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