Research Papers: Gas Turbines: Turbomachinery

Sensitivity Analysis of Auto-Ignition Simulation at Gas Turbine Operating Conditions

[+] Author and Article Information
Juliane Prause

Institute of Combustion Technology,
German Aerospace Center (DLR),
Pfaffenwaldring 38-40,
Stuttgart 70569, Germany
e-mail: juliane.prause@dlr.de

Berthold Noll, Manfred Aigner

Institute of Combustion Technology,
German Aerospace Center (DLR),
Pfaffenwaldring 38-40,
Stuttgart 70569, Germany

Khawar Syed

Alstom (Switzerland) Ltd.,
Zentralstrasse 40,
Birr 5242, Switzerland

Contributed by the Turbomachinery Committee of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received December 4, 2014; final manuscript received January 21, 2015; published online March 31, 2015. Editor: David Wisler.

J. Eng. Gas Turbines Power 137(10), 102601 (Oct 01, 2015) (7 pages) Paper No: GTP-14-1646; doi: 10.1115/1.4029930 History: Received December 04, 2014; Revised January 21, 2015; Online March 31, 2015

The demand to reduce CO2 emissions favors the use of alternative hydrogen-rich fuels, which can stem from precombustion carbon capture or power-to-gas technologies. These fuels are characterized by a higher reactivity and reduced ignition delay time compared to natural gas. Therefore, current combustor designs need to be adapted to the new requirements. Numerical modeling greatly assists the further development of such systems. The present study aims to determine how far a sophisticated computational fluid dynamics (CFD) combustion method is able to predict auto-ignition at real engine conditions. Scale-resolving computations of auto-ignition were performed at elevated pressure (15 bar) and intermediate temperatures (>1000 K). The conditions are similar to those occurring in premixing ducts of reheat combustors. A nitrogen-diluted hydrogen jet is injected perpendicularly into a stream of hot vitiated air. The scale-adaptive simulation (SAS) method as proposed by Menter and coworkers has been applied. The chemistry is captured by direct inclusion of detailed kinetics. Subgrid fluctuations of temperature and species are considered by an assumed probability density function (PDF) approach. The results are compared with appropriate experimental reference data. The focus of the present work is set on the identification of the major sources of uncertainty in the simulation of auto-ignition. Despite the very challenging operating conditions, satisfactory agreements could be obtained within experimental uncertainties.

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Fig. 1

Alstom GT24/GT26 gas turbine [2]

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Fig. 2

Experimental setup [10]

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Fig. 3

Luminescence signal of auto-ignition events [10], left: nonstabilizing ignition kernel, right: stabilizing ignition kernel

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Fig. 4

Position of ignition kernels [10]

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Fig. 5

Instantaneous temperature distribution for baseline hot gas temperature Thg/Tref = 1.00

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Fig. 6

Instantaneous temperature distribution for baseline hot gas temperature Thg/Tref = 1.10

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Fig. 7

Instantaneous temperature distribution for baseline hot gas temperature Thg/Tref = 1.14

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Fig. 8

Averaged temperature distribution for Thg/Tref = 1.10 with flame front on the coarse grid

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Fig. 9

Averaged temperature distribution for Thg/Tref = 1.10 on the medium grid

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Fig. 10

Averaged temperature distribution for Thg/Tref = 1.10 on the fine grid

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Fig. 11

Eddy viscosity ratio

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Fig. 12

Kinetic mechanisms

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Fig. 13

Measured temperature signal [10]

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Fig. 14

Instantaneous temperature distribution for extended domain

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Fig. 15

Computed temperature signal at position of temperature probe

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Fig. 16

Computation of ignition kernel evolution in the mixing duct with inclusion of hot gas temperature fluctuations




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