On the Application of CAA-Methods for the Simulation of Indirect Combustion Noise

Richter, Christoph; Panek, Łukasz; Thiele, Frank

doi:10.2514/6.2005-2919

Cited by 12 publications

(8 citation statements)

References 16 publications

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“…The time marching is performed by the alternating five/six-stage low dissipation, low dispersion Runge-Kutta (LDDRK) method [18] implemented in 2N storage form [19]. An 11-point-stencil central Taylor filter (FIR) of the tenth order is used to eliminate parasite waves [20]. At the boundaries, central filters of lower orders are applied.…”

Section: Mathematical Model and Numerical Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Comparison of Time-Domain Impedance Boundary Conditions for Lined Duct Flows

Richter¹,

Thiele²,

et al. 2007

AIAA Journal

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Two time-domain impedance models developed recently have been examined and tested numerically. One is based on the three-parameter model of Tam and Auriault augmented by a method to evaluate the effective impedance under flow conditions for a harmonic source. The other is Rienstra's extended Helmholtz resonator model. Its timedomain representation is fully based on the idea of Özyörük and Long to use a z transformation for an impedance function with periodic frequency response. The implementation of the models in a numerical simulation tool with the dispersion relation preserving scheme is discussed in detail. A filtering approach guarantees the stability of the Myers boundary condition. The results from both of the two models agree notably well with each other. The validation and verification of both models are carried out for the latest NASA impedance tube experiment. The adaptability to realistic inlet configurations is shown using a generic aeroengine geometry with available numerical results. Overall, both models give a similar physical behavior if limitations are carefully considered. The extended Helmholtz resonator is used as termination impedance. A broadband impedance eduction is successfully carried out, resulting in an extended Helmholtz resonator representation for a ceramic tubular liner. Nomenclature A, B, C, D = coefficient matrices (LEE) F 0 = flux vector (LEE) i = imaginary unit, e i!t convention m = face reactance (EHR) n = radial mode number n = wall normal vector p = pressure amplitude p 0 = pressure perturbation p 0 = mean pressure R = face resistance (EHR) R 0 0 = effective resistance parameter (EFI) s p = auxiliary variable (EFI and EHR) T l = period time (EHR) u n = normal velocity amplitude u 0 = mean velocity vector u 0 n = normal velocity perturbation u 0 = velocity perturbation X 0 1 = effective reactance parameter (EFI) X 0 1 = effective reactance parameter (EFI) Z= complex impedance = cavity reactance (EHR) = ratio of the specific heats "= cavity resistance (EHR) = correction coefficient (EFI and EHR) t = Myers term (EHR) = azimuthal mode number x = damping coefficient 0 = perturbation state vector ! = angular frequency % 0 = mean density % 0 = density perturbation

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Section: Mathematical Model and Numerical Methodsmentioning

confidence: 99%

“…A constrained nonlinear MATLAB optimization fits the five parameters for the EHR of Eq. (20) to the given frequency response of the termination impedance. To keep the impedance physical, all five parameters are restricted to be positive during the optimization.…”

Section: Fitting Of Impedances By Ehrmentioning

confidence: 98%

Comparison of Time-Domain Impedance Boundary Conditions for Lined Duct Flows

Richter¹,

Thiele²,

et al. 2007

AIAA Journal

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“…In combination with a1 0 th order spatial lowp ass filtering it allows to model the transport of perturbations down to about 7g rid points per wavelength (PPW). Classical first order CFD methods would require about 50 PPWwith the same restriction to the dissipation and dispersion error.The basic numerical method is adopted [14,20,15] from the description of fant one noise in the aeroengine inlet [17,21,22]. However, in combustion noise the time domain approach can exhibit its full potential.…”

Section: Methodsmentioning

confidence: 99%

CAA Simulation and Intensity Based Evaluation of a Model Experiment for Indirect Combustion Noise

Richter¹,

Morgenweck²,

Thiele³

2009

Acta Acustica united with Acustica

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The efficient prediction of combustion noise by azonal approach is discussed. Forthe so called propagation zone an optimized finite difference method adopted from fantone noise propagation is applied together with alinear perturbation approach based on the Euler equations. Special attention is payed to the indirect noise generation in the propagation zone, where initially quiet perturbations of the fluid state radiate noise when accelerated or decelerated in av arying base flowregime. Anon-isentropic mathematical model is chosen. The approach is compared with apreviously published experiment for the assessment of indirect combustion noise. The numerical results showthe strong influence of reflections from the inflowboundary of the plenum on the resulting pressure response in the outlet duct. By assuming reasonable reflections from the plenum, the observed time signal of the pressure reaches ar easonable agreement between numerical simulation and experiment. Furthermore, the acoustic intensity is used to showthe good quality of the numerical solution. Finally,the intensity based source location identifies the nozzle as adominant source of sound, with large magnitudes of generation and annihilation of acoustic energy.The source power found in the heated volume is more than twoorders of magnitude smaller than in the nozzle. This result again underlines the importance of indirect combustion noise. PACS no. 43.20.Mv,43.28.Kt, 43.60.Jn ACTA ACUSTICA UNITED WITH ACUSTICA Richter et al.:M odel experiment forindirect combustion noise Vol. 95 (2009)

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“…The method revealed delay times from the internal combustor sensor to the far-field microphone, even though the correlated signal contained both periodic and random components. In addition, indirect combustion noise has been investigated numerically and with model-scale experiments by Schemel et al [32], Richter et al [33], and Bake et al [34][35][36].…”

mentioning

confidence: 98%

Core Noise Diagnostics of Turbofan Engine Noise Using Correlation and Coherence Functions

Miles

2010

Journal of Propulsion and Power

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Cross-correlation and coherence functions are used to look for periodic acoustic components in turbofan engine combustor time histories, to investigate direct and indirect combustion noise source separation based on signal propagation time delays, and to provide information on combustor acoustics. This investigation uses a combustor pressure sensor and a far-field microphone at 130 to study the change in propagation time to the far field of the direct and indirect combustion noise signal using a generalized cross-correlation function. Results are presented as a function of the cutoff frequency of the low-pass filter used to create the generalized cross-correlation function and engine operating condition. The filtering procedure used produces no phase distortion. As the low-pass-filter frequency is decreased, the travel time increases. The indirect combustion noise signal travels more slowly, because the entropy in the combustor moves with the flow, which has a low velocity. The indirect combustion noise signal travels at acoustic velocities after reaching the turbine and being converted into an acoustic signal. The direct combustion noise is always propagating at acoustic velocities. This is in agreement with previous investigations of delay times using a cross-spectrum phase-angle method with unfiltered signals that found indirect combustion noise to be in the 0-200 Hz frequency range and the direct combustion noise to be in the 200-400 Hz frequency range. Similar results obtained using the cross-spectrum phase-angle method with filtered signals are also shown. These results show that the low-pass filtering can be used with the cross-correlation function to separate this type of dependent source and confirm the cross-spectrum results. Although the results are based on a set of static engine tests conducted for one specific dual-spool turbofan engine configuration, they may lead to a better idea about the acoustics in the combustor turbine-tailpipe system and may help develop and validate improved reduced-order physics-based methods for predicting turbofan engine core noise. NomenclatureB e = resolution bandwidth, Hz, 1=T d r s =N 2 Hz c c = combustor-region speed of sound, m=s c o = ambient speed of sound, m=s D = propagation time delay or lag, s f c = upper frequency limit, 1=2t r s =2, Hz (32,768 Hz) f L = cutoff frequency of low-pass filter L c = combustor-region length, m L y = number of frequencies, f c =f N=2 (16,384) M c = combustor-region Mach number N = segment length, number of data points per segment (32,768) n o = number of overlapped data segments/blocks n s = number of disjoint (independent) data segments/ blocks, B e T total 128 P I = confidence-interval percent value used to calculate coherence threshold < = gas constant, 8314 J=k mol K R x = autocorrelation function R xy = cross-correlation function r = microphone radial location, m (30.48 m) r s = sample rate, samples/s (65,536) T c = temperature in combustor, K T d i = record length of segment i, N=r s , 0.5 s T total = total record length, s ...

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On the Application of CAA-Methods for the Simulation of Indirect Combustion Noise

Cited by 12 publications

References 16 publications

Comparison of Time-Domain Impedance Boundary Conditions for Lined Duct Flows

Comparison of Time-Domain Impedance Boundary Conditions for Lined Duct Flows

CAA Simulation and Intensity Based Evaluation of a Model Experiment for Indirect Combustion Noise

Core Noise Diagnostics of Turbofan Engine Noise Using Correlation and Coherence Functions

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