scholarly journals Detection of lean blowout in a premixed gas-turbine model combustor based on nonlinear dynamics

2012 ◽  
Author(s):  
Y. Shinoda ◽  
M. Kobayashi ◽  
H. Gotoda ◽  
S. Tachibana
Keyword(s):  
Nonlinear Dynamics ◽  
Gas Turbine ◽  
Lean Blowout ◽  
Turbine Model

scholarly journals Influence of Single-Component Fuels on Gas-Turbine Model Combustor Lean Blowout

2018 ◽  
Vol 34 (1) ◽  
pp. 97-107 ◽  
Author(s):  
J. Grohmann ◽  
B. Rauch ◽  
T. Kathrotia ◽  
W. Meier ◽  
M. Aigner
Keyword(s):  
Gas Turbine ◽  
Single Component ◽  
Lean Blowout ◽  
Turbine Model

scholarly journals Dynamics of lean blowout of a swirl-stabilized flame in a gas turbine model combustor

2011 ◽  
Vol 33 (2) ◽  
pp. 2953-2960 ◽  
Author(s):  
M. Stöhr ◽  
I. Boxx ◽  
C. Carter ◽  
W. Meier
Keyword(s):  
Gas Turbine ◽  
Lean Blowout ◽  
Turbine Model

Investigation of differences in lean blowout of liquid single-component fuels in a gas turbine model combustor

2016 ◽  
Author(s):  
Jasper Grohmann ◽  
Bastian Rauch ◽  
Trupti Kathrotia ◽  
Wolfgang Meier ◽  
Manfred Aigner
Keyword(s):  
Gas Turbine ◽  
Single Component ◽  
Lean Blowout ◽  
Turbine Model

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

2016 ◽  
Vol 139 (4) ◽  
Author(s):  
Hiroshi Gotoda ◽  
Kenta Hayashi ◽  
Ryosuke Tsujimoto ◽  
Shohei Domen ◽  
Shigeru Tachibana
Keyword(s):  
Gas Turbine ◽  
Combustion Instability ◽  
Turbulent Flame ◽  
Surrogate Data ◽  
Permutation Entropy ◽  
Lean Blowout ◽  
Lean Premixed ◽  
Free Running ◽  
Nonlinear Forecasting ◽  
Turbine Model

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.

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

2016 ◽  
Author(s):  
Hiroshi Gotoda ◽  
Kenta Hayashi ◽  
Ryosuke Tsujimoto ◽  
Shohei Domen ◽  
Shigeru Tachibana
Keyword(s):  
Gas Turbine ◽  
Radial Basis Function Network ◽  
Combustion Instability ◽  
Turbulent Flame ◽  
Surrogate Data ◽  
Permutation Entropy ◽  
Lean Blowout ◽  
Free Running ◽  
Turbine Model

We present an experimental study on 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 a burst and pseudo-periodic oscillations exhibit the deterministic nature of chaos. This is clearly demonstrated by considering two nonlinear forecasting methods: the extended version [1] of the Sugihara & May algorithm [2] as a local predictor, and the generalized radial basis function network as a global predictor [3], [4]. The former enables us to extract the short-term predictability and long-term unpredictability nature of chaos, while the latter can produce surrogate data to test for determinism as a free running approach. Permutation entropy is estimated by a symbolic sequence approach for the surrogate data to test for determinism and is also used as an online detector to prevent lean blowout.

scholarly journals Investigation of turbulent premixed methane/air and hydrogen-enriched methane/air flames in a laboratory-scale gas turbine model combustor

2021 ◽  
Author(s):  
Xin Liu ◽  
Michael Bertsch ◽  
Arman Ahamed Subash ◽  
Senbin Yu ◽  
Robert-Zoltan Szasz ◽  
...  
Keyword(s):  
Gas Turbine ◽  
Laboratory Scale ◽  
Turbine Model ◽  
Turbulent Premixed

Plasma-Assisted Combustor Dynamics Control at Ambient and Realistic Gas Turbine Conditions

2017 ◽  
Author(s):  
Wookyung Kim ◽  
Jeffrey Cohen
Keyword(s):  
Gas Turbine ◽  
Ambient Pressure ◽  
Plasma Discharge ◽  
Inlet Temperature ◽  
Pulsed Plasma ◽  
Plasma Power ◽  
Lean Blowout ◽  
Wide Range ◽  
Baseline Temperature ◽  
Increasing Temperature

The central objective of this study is to investigate the effectiveness of implementing a plasma discharge to improve combustor dynamics and flame stability. Specifically, a nano-second pulsed plasma discharge (NSPD) was applied to a premixed gaseous fuel/air dump combustor for mitigation of dynamic combustion instabilities with a minimal NOX penalty. This paper addresses the scaling of this technology from ambient pressure and temperature conditions to more realistic gas turbine combustor conditions. A model combustor operating at representative conditions of O (102) m/s flow velocity, ∼ 580 K combustor inlet temperature, and ∼ 5 atm in-combustor pressure was selected to simulate a typical low-power environment of future aero engine gas turbine combustors. Fully premixed methane or propane was utilized as a fuel. Similar to a previous ambient-pressure study, a significant reduction of pressure fluctuation level was observed, by a factor of 2X to 4X over a wide range of velocity at the baseline temperature and pressure. The plasma power required for the reduction increased linearly with increasing velocity. The change of fuel from methane to propane showed that propane requires significantly (2X) higher plasma power to achieve a similar level of noise reduction. It was also observed that the lean blowout (LBO) limit was significantly extended in the presence of the plasma, however, substantial incomplete combustion occurs in the extended regime. NOX measurements showed that the incremental NOX production due to the presence of the plasma was low (∼ < 1EINOX) in general, however, it increased with decreasing velocity and pressure, and increasing temperature.

scholarly journals The Effect of Discrete Pilot Hydrogen Dopant Injection on the Lean Blowout Performance of a Model Gas Turbine Combustor

1999 ◽  
Author(s):  
Oanh Nguyen ◽  
Scott Samuelsen
Keyword(s):  
Gas Turbine ◽  
Atmospheric Pressure ◽  
Gas Turbines ◽  
Nox Emissions ◽  
Gas Turbine Combustor ◽  
Lean Blowout ◽  
Lean Combustion ◽  
Attractive Option ◽  
Overall Performance ◽  
Model Gas Turbine Combustor

In view of increasingly stringent NOx emissions regulations on stationary gas turbines, lean combustion offers an attractive option to reduce reaction temperatures and thereby decrease NOx production. Under lean operation, however, the reaction is vulnerable to blowout. It is herein postulated that pilot hydrogen dopant injection, discretely located, can enhance the lean blowout performance without sacrificing overall performance. The present study addresses this hypothesis in a research combustor assembly, operated at atmospheric pressure, and fired on natural gas using rapid mixing injection, typical of commercial units. Five hydrogen injector scenarios are investigated. The results show that (1) pilot hydrogen dopant injection, discretely located, leads to improved lean blowout performance and (2) the location of discrete injection has a significant impact on the effectiveness of the doping strategy.

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