Impact of fuel supply impedance and fuel staging on gas turbine ...

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System Identification 1 0.9 Quality Q/Q 0 0.8 0.7 0.6 0.5 20 40 60 80 100 Length <strong>of</strong> time series [x M] Figure 5.17: Quality Q/Q 0 <strong>of</strong> identification as a function <strong>of</strong> time series length (-+ W/O NOISE, -o S/N = 10, -∗ S/N = 4) degree. In the present case the correlation amounted to 50%. In the presence <strong>of</strong> noise it becomes apparent that the discrete r<strong>and</strong>om binary signal showed the best performance compared to broadb<strong>and</strong> white noise or a sine overlay. Therefore the DRBS is used in the following to apply the identification method to the measured signals <strong>and</strong> responses, which are obtained by a transient CFD simulation. As the method itself has proven to work properly, the physical quality <strong>of</strong> the identification just depends on the numerical models (turbulence, combustion) used in the CFD simulation <strong>and</strong> the amount <strong>of</strong> noise in the signals. 104
6 Numerical simulation MISO model identification is now applied to a generic practical premixed swirl burner with a multi-stage <strong>fuel</strong> injection system. The purpose is to show that the method proposed can be applied successfully to complex configurations, like the turbulent reacting flow <strong>of</strong> a practical premixed combustor, <strong>and</strong> to demonstrate that relevant information on flame dynamics can be deduced from unit impulse <strong>and</strong> frequency responses. In the next section the combustor configurations with two stage <strong>and</strong> three stage <strong>fuel</strong> injection will be described in more detail, followed by a summary <strong>of</strong> the CFD model setup. Then the results <strong>of</strong> steady-state <strong>and</strong> transient simulations are presented, including a physics-based interpretation <strong>of</strong> the flame dynamics. As the acoustic characteristics <strong>of</strong> the axial swirler are not known <strong>and</strong> can not be derived analytically, the transfer matrix <strong>of</strong> the swirler is identified in addition to the flame transfer functions. The results obtained are implemented into an acoustic network model <strong>of</strong> the combustion system, as described in chapter 7. 6.1 Practical premixed combustor configuration The configuration investigated in this study is representative <strong>of</strong> a combustor with practical premixing. The layout is similar to a combustion test rig investigated by Komarek et al. [56, 57] <strong>and</strong> comprises a plenum, an axial swirler <strong>and</strong> bluff-body flame holder mounted in an annular duct, <strong>and</strong> the combustion chamber. The axial swirler comprises in total eight blades with an angle <strong>of</strong> attack <strong>of</strong> 45 ◦ . The theoretical swirl number <strong>of</strong> the flow is 0.74. The plenum has a length <strong>of</strong> L = 0.095 m with a cross-section area <strong>of</strong> A= 0.0312 m 2 . The length <strong>of</strong> the combustion chamber is equal to L = 0.3 m, with a cross-section <strong>of</strong> A = 105
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Technische Universität München In
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und ihre Geduld besonders für die
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Contents 1 Introduction 1 1.1 Techn
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CONTENTS 7.2.2 Impact</stro
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Nomenclature G stretch factor [-] h
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Nomenclature λ air-fuel</s
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1 Introduction 1.1 Technology backg
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1.2 Thermo-acoustic instabilities 1
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1.2 Thermo-acoustic instabilities d
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1.3 Control of the
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1.3 Control of the
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1.4 Intention and
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1.5 Terminology and</strong
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1.5 Terminology and</strong
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2 Numerical analysis of</st
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2.1 Overview of me
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2.1 Overview of me
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2.1 Overview of me
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2.2 Flame dynamics of</stro
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2.3 Identification of</stro
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3 Acoustics Before analyzing the ac
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3.1 Basic acoustic equations as a f
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3.2 Linear acoustic equations Here,
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3.2 Linear acoustic equations p ′
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3.3 Acoustic network model p ′ (x
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Page 69 and 70: 3.3 Acoustic network model The <str
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Page 77 and 78: 3.3 Acoustic network model pressure
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Page 83 and 84: 4 Modeling of turb
Page 85 and 86: 4.1 Theory and num
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Page 95 and 96: 5 System Identification Flame trans
Page 97 and 98: 5.1 Model structures and</s
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Page 101 and 102: 5.3 Excitation signals the zero mea
Page 103 and 104: 5.4 A posteriori validation <strong
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Page 107 and 108: 5.5 Proof
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Page 133 and 134: 6.3 Identifiction of</stron
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Page 153 and 154: 7 Acoustic analysis Once the acoust
Page 155 and 156: 7.1 Setup of the a
Page 157 and 158: 7.2 Acoustic network model results
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7.2 Acoustic network model results
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8 Summary and Conc
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The flame element of</stron
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Bibliography [1] Verband</s
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BIBLIOGRAPHY [18] L. Crocco. Theore
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BIBLIOGRAPHY [36] A. Giauque, L. Se
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BIBLIOGRAPHY [54] J.J. Keller, W. E
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BIBLIOGRAPHY [72] T. Lieuwen <stron
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BIBLIOGRAPHY Number 98-GT-269 in In
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BIBLIOGRAPHY [112] T. Sattelmayer.
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BIBLIOGRAPHY [130] A. Widenhorn. pr
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A.2 Estimation of
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A.3 Main flow parameters an
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