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Applying Neural Network Technique for prediction of NOx Emission and Combustion Dynamics of an Experimental Turbulent Swirl-stabilized Combustor using flame image processing techniques

Publish place: 17th Fluid Dynamics Conference
Publish Year: 1396
Type: Conference paper
Language: English
View: 602

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Link to this Paper:
https://civilica.com/doc/690927

Document National Code:

CFD17_034

Index date: 12 January 2018

Applying Neural Network Technique for prediction of NOx Emission and Combustion Dynamics of an Experimental Turbulent Swirl-stabilized Combustor using flame image processing techniques abstract

In the present study, direct flame images obtained from an experimental swirl stabilized combustor are used to predict the output parameters of the combustor including the level of NOx emission, amounts of noise and the level of pressure fluctuations in the combustor. For this purpose, different values of overall equivalence ratios in the range of 0.7-0.9 along with various amounts of secondary fuel injection rates between

Applying Neural Network Technique for prediction of NOx Emission and Combustion Dynamics of an Experimental Turbulent Swirl-stabilized Combustor using flame image processing techniques Keywords:

swirl-stabilized combustor , secondary fuel injection , pressure fluctuation , Nox emission , combustion process , artificial neural network

Applying Neural Network Technique for prediction of NOx Emission and Combustion Dynamics of an Experimental Turbulent Swirl-stabilized Combustor using flame image processing techniques authors

Ramin Asadi

M.Sc student at University of Tehran

Rouzbeh Riazi

Associate professor

Maziar Shafaee

Associate professor

Shidvash Vakilipour

Associate professor