Dynamical Properties of Combustion Instability in a Laboratory-Scale Gas-Turbine Model CombustorSource: Journal of Engineering for Gas Turbines and Power:;2017:;volume( 139 ):;issue: 004::page 41509DOI: 10.1115/1.4034700Publisher: The American Society of Mechanical Engineers (ASME)
Abstract: 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in Combustion Instability in a Lean Premixed Gas-Turbine Model Combustor,” Chaos, 22, p. 043128; Gotoda et al., 2016 (unpublished)).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.
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contributor author | Gotoda, Hiroshi | |
contributor author | Hayashi, Kenta | |
contributor author | Tsujimoto, Ryosuke | |
contributor author | Domen, Shohei | |
contributor author | Tachibana, Shigeru | |
date accessioned | 2017-11-25T07:15:46Z | |
date available | 2017-11-25T07:15:46Z | |
date copyright | 2016/8/11 | |
date issued | 2017 | |
identifier issn | 0742-4795 | |
identifier other | gtp_139_04_041509.pdf | |
identifier uri | http://138.201.223.254:8080/yetl1/handle/yetl/4233663 | |
description abstract | 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. | |
publisher | The American Society of Mechanical Engineers (ASME) | |
title | Dynamical Properties of Combustion Instability in a Laboratory-Scale Gas-Turbine Model Combustor | |
type | Journal Paper | |
journal volume | 139 | |
journal issue | 4 | |
journal title | Journal of Engineering for Gas Turbines and Power | |
identifier doi | 10.1115/1.4034700 | |
journal fristpage | 41509 | |
journal lastpage | 041509-6 | |
tree | Journal of Engineering for Gas Turbines and Power:;2017:;volume( 139 ):;issue: 004 | |
contenttype | Fulltext |