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  5. Numerical study assessing various ammonia/methane reaction models for use under gas turbine conditions

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Article
English
2017

Numerical study assessing various ammonia/methane reaction models for use under gas turbine conditions

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English
2017
Fuel
Vol 196
DOI: 10.1016/j.fuel.2017.01.095

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Agustin Valera Medina
Agustin Valera Medina

Cardiff University

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Hua Xiao
Agustin Valera Medina
Richard Marsh
+1 more

Abstract

Ammonia as an alternative fuel and hydrogen carrier has received increased attention in recent years. To explore the potential of co-firing ammonia with methane for power generation, studies involving robust mathematical analyses are required to progress towards industrial implementation. To explore a best suited mechanism for ammonia/methane combustion in gas turbines, five different detailed mechanisms were compared to identify their accuracy to represent the reaction kinetics under real gas turbine combustor conditions. Ignition delay time was compared with recent literature showing that the mechanisms of Tian and Teresa exhibit the best accuracy over a large range of conditions. A 1D simulation was also conducted using a Chemical Reactor Network (CRN) model, thus providing a relatively quick estimation of the combustion mechanisms under swirling combustion conditions. The simulation of NOx emissions indicates that Tian mechanism has better performance than the others compared. Hence, the Tian mechanism was selected as the most appropriate for further studies of ammonia/methane combustion through a set of experiments carried out at various equivalence ratios and pressure conditions. Finally, sensitivity and pathway analyses were also performed to identify important reactions and species under high pressurized conditions, areas that need more attention for model development and emission control in future studies.

How to cite this publication

Hua Xiao, Agustin Valera Medina, Richard Marsh, Philip John Bowen (2017). Numerical study assessing various ammonia/methane reaction models for use under gas turbine conditions. Fuel, 196, pp. 344-351, DOI: 10.1016/j.fuel.2017.01.095.

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Publication Details

Type

Article

Year

2017

Authors

4

Datasets

0

Total Files

0

Language

English

Journal

Fuel

DOI

10.1016/j.fuel.2017.01.095

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