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Research Papers

Uncertainty Quantification of NOx Emission Due to Operating Conditions and Chemical Kinetic Parameters in a Premixed Burner

[+] Author and Article Information
Sajjad Yousefian

Mechanical Engineering, Combustion Chemistry
Centre, and Ryan Institute,
National University of Ireland,
Galway, Ireland;
Research Centre for Marine and
Renewable Energy,
Galway, Ireland
e-mail: s.yousefian2@nuigalway.ie

Gilles Bourque

Siemens Canada Ltd,
9545 Cote de Liesse Road,
Montreal QC H9P 1A5, Canada;
Department of Mechanical Engineering,
McGill University,
Montréal, QC H3A 0C3, Canada

Rory F. D. Monaghan

Mechanical Engineering, Combustion Chemistry
Centre, and Ryan Institute,
National University of Ireland,
Galway, Ireland;
Research Centre for Marine and
Renewable Energy,
Galway, Ireland

1Corresponding author.

Manuscript received June 21, 2018; final manuscript received July 2, 2018; published online October 1, 2018. Editor: Jerzy T. Sawicki.

J. Eng. Gas Turbines Power 140(12), 121005 (Oct 01, 2018) (11 pages) Paper No: GTP-18-1269; doi: 10.1115/1.4040897 History: Received June 21, 2018; Revised July 02, 2018

Many sources of uncertainty exist when emissions are modeled for a gas turbine combustion system. They originate from uncertain inputs, boundary conditions, calibration, or lack of sufficient fidelity in a model. In this paper, a nonintrusive polynomial chaos expansion (NIPCE) method is coupled with a chemical reactor network (CRN) model using Python to quantify uncertainties of NOx emission in a premixed burner. The first objective of uncertainty quantification (UQ) in this study is development of a global sensitivity analysis method based on the NIPCE method to capture aleatory uncertainty on NOx emission due to variation of operating conditions. The second objective is uncertainty analysis (UA) of NOx emission due to uncertain Arrhenius parameters in a chemical kinetic mechanism to study epistemic uncertainty in emission modeling. A two-reactor CRN consisting of a perfectly stirred reactor (PSR) and a plug flow reactor (PFR) is constructed in this study using Cantera to model NOx emission in a benchmark premixed burner under gas turbine operating conditions. The results of uncertainty and sensitivity analysis (SA) using NIPCE based on point collocation method (PCM) are then compared with the results of advanced Monte Carlo simulation (MCS). A set of surrogate models is also developed based on the NIPCE approach and compared with the forward model in Cantera to predict NOx emissions. The results show the capability of NIPCE approach for UQ using a limited number of evaluations to develop a UQ-enabled emission prediction tool for gas turbine combustion systems.

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Figures

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Fig. 1

Experimental test rig for a lean premixed high-pressure burner [35]

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Fig. 7

Comparison of NOx predictions between forward and surrogate models. The data points colored by temperature.

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Fig. 8

Comparison of first-order sensitivity indices for different reference conditions using advanced MCS

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Fig. 9

Comparison of first-order sensitivity indices for different reference conditions using NIPCE-PCM

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Fig. 2

Comparison of NOx emission using chemical kinetic mechanisms in this study and experimental and modeling data by Elkady et al. [35]

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Fig. 3

Distribution of 10,000 evaluations by advanced MCS. The markers colored by initial temperature range. Solid line shows the results from Fig. 2 at initial temperature of 688 K, initial pressure of 12.58 atm and air mass flow rate of 0.022 kg/s.

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Fig. 4

Comparison of probability density distribution for NOx emission using advanced MCS and NIPCE-PCM at reference equivalence ratio of 0.5

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Fig. 5

Comparison of probability density distribution for NOx emission using advanced MCS and NIPCE-PCM at reference equivalence ratio of 0.55

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Fig. 6

Comparison of probability density distribution for NOx emission using advanced MCS and NIPCE-PCM at reference equivalence ratio of 0.60

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