0
Research Papers: Gas Turbines: Combustion, Fuels, and Emissions

Dynamical Properties of Combustion Instability in a Laboratory-Scale Gas-Turbine Model Combustor

[+] Author and Article Information
Hiroshi Gotoda

Department of Mechanical Engineering,
Tokyo University of Science,
6-3-1 Niijuku,
Katsushika, Tokyo 125-8585, Japan
e-mail: gotoda@rs.tus.ac.jp

Kenta Hayashi, Ryosuke Tsujimoto, Shohei Domen

Department of Mechanical Engineering,
Ritsumeikan University,
1-1-1 Nojihigashi,
Kusatsu, Shiga 525-8577, Japan

Shigeru Tachibana

Aeronautical Technology Directorate,
Japan Aerospace Exploration Agency,
7-44-1 Jindaiji-Higashi,
Chofu, Tokyo 182-8522, Japan

Contributed by the Combustion and Fuels Committee of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received June 30, 2016; final manuscript received August 11, 2016; published online November 8, 2016. Editor: David Wisler.

J. Eng. Gas Turbines Power 139(4), 041509 (Nov 08, 2016) (6 pages) Paper No: GTP-16-1294; doi: 10.1115/1.4034700 History: Received June 30, 2016; Revised August 11, 2016

We present an experimental study on the nonlinear dynamics of combustion instability in a lean premixed gas-turbine model combustor with a swirl-stabilized turbulent flame. Intermittent combustion oscillations switching irregularly back and forth between burst and pseudo-periodic oscillations exhibit the deterministic nature of chaos. This is clearly demonstrated by considering two nonlinear forecasting methods: an extended version (Gotoda et al., 2015, “Nonlinear Forecasting of the Generalized Kuramoto-Sivashinsky Equation,” Int. J. Bifurcation Chaos, 25, p. 1530015) of the Sugihara and May algorithm (Sugihara and May, 1990, “Nonlinear Forecasting as a Way of Distinguishing Chaos From Measurement Error in Time Series,” Nature, 344, pp. 734–741) as a local predictor, and a generalized radial basis function (GRBF) network as a global predictor (Gotoda et al., 2012, “Characterization of Complexities in Combustion Instability in a Lean Premixed Gas-Turbine Model Combustor,” Chaos, 22, p. 043128; Gotoda et al., 2016 (unpublished)). The former enables us to extract the short-term predictability and long-term unpredictability of chaos, while the latter can produce surrogate data to test for determinism by a free-running approach. The permutation entropy based on a symbolic sequence approach is estimated for the surrogate data to test for determinism and is also used as an online detector to prevent lean blowout.

FIGURES IN THIS ARTICLE
<>
Copyright © 2017 by ASME
Your Session has timed out. Please sign back in to continue.

References

Figures

Grahic Jump Location
Fig. 1

Temporal evolution of OH* chemiluminescence intensity fluctuations I′ for different equivalence ratios ϕ

Grahic Jump Location
Fig. 2

Power spectra of OH* chemiluminescence intensity fluctuations I′ for different equivalence ratios ϕ

Grahic Jump Location
Fig. 3

Variations in permutation entropy hp for the original and surrogate time-series data of intermittent combustion oscillations. Note that 20 sets of surrogate time-series data are obtained by the radial basis function network.

Grahic Jump Location
Fig. 4

Variations in correlation coefficient C obtained by the local predictor for the intermittent combustion oscillations as a function of prediction time tP. Variations in C for increments of ΔI′(=I′(ti+1)−I′(ti)) are also shown as a function of tP.

Grahic Jump Location
Fig. 5

Variations in permutation entropy hp of OH* chemiluminescence fluctuations I′ as a function of equivalence ratio ϕ

Grahic Jump Location
Fig. 6

Temporal variations in volume flow rate of secondary fuel Qsecondary and equivalence ratio ϕ with decreasing volume flow rate of main fuel Qmain

Grahic Jump Location
Fig. 7

Temporal variations in volume flow rate of secondary fuel Qsecondary and equivalence ratio ϕ with decreasing and increasing volume flow rate of main fuel Qmain

Tables

Errata

Discussions

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In