571 research outputs found

    Acoustic sources and far-field noise of chevron and round jets

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    This paper investigates numerically the acoustic sources and far-field noise of chevron and round jets. The acoustic sources are described by the fourth-order space–time velocity cross correlations, which are calculated based on a large-eddy simulation flowfield. Gaussian functions are found to fit the axial, radial, and azimuthal cross correlations reasonably well. The axial length scales are three to four times the radial and azimuthal length scales. For the chevron jet, the cross-correlation scales vary with azimuthal angle up to six jet diameters downstream; beyond that, they become axisymmetric like those for a round jet. The fourth-order space–time cross correlation of the axial velocity R_1111 is the dominant source component, and there are considerable contributions from other source components such as R_2222, R_3333, R_1212, R_1313, and R_2323 cross correlations where 1, 2, and 3 represent axial, radial, and azimuthal directions, respectively. For the chevron jet, these cross correlations decay rapidly with axial distance whereas for the round jet, they remain roughly constant over the first 10 jet diameters. The chevron jet intensifies both the R_2222 and R_3333 cross correlations within two jet diameters of the jet exit. The amplitude, length, and time scales of the cross-correlations of a large-eddy simulation velocity field are investigated as functions of position and are found to be proportional to the turbulence amplitude, length, and time scales that are determined from a Reynolds-averaged Navier–Stokes calculation. The constants of proportionality are found to be independent of position within the jet, and they are quite close for chevron and round jets. The scales derived from Reynolds-averaged Navier–Stokes are used for source description, and an acoustic analogy is used for sound propagation. There is an excellent agreement between the far-field noise predictions and measurements. At low frequencies, the chevron nozzle significantly reduces the far-field noise by 5–6 dB at 30 deg and 2–3 dB at 90 deg to the jet axis. However, the chevron nozzle slightly increases high-frequency noise. It was found that R_1212 and R_1313 cross correlations have the largest contribution to the jet noise at 30 deg to the jet axis, whereas the R_2323 cross correlation has the largest contribution to the jet noise at 90 deg to the jet axis. The Reynolds-averaged Navier–Stokes calculations are repeated with different turbulence models, and the noise prediction is found to be almost insensitive to the turbulence model. The results indicate that the modeling approach is capable of assessing advanced noise-reduction concepts.Depuru Mohan expresses his sincere gratitude to St John’s College, University of Cambridge, for the award of a Manmohan Singh Scholarship; as well as Cambridge Commonwealth, European, and International Trust for the award of an Honorary Cambridge International Scholarship. S. A. Karabasov wishes to thank the Royal Society of London for the award of a University Research Fellowship. H. Xia acknowledges the computational time on the European High Performance Computing systems, Partnership for Advanced Computing in Europe, under project 2010PA0649. The authors are grateful to J. Bridges, C. Brown, N. Georgiadis, and J. DeBonis of the NASA John H. Glenn Research Center for providing the experimental data

    Prediction of combustion noise for an aeroengine combustor

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    Combustion noise may become an important noise source for lean-burn gas turbine engines, and this noise is usually associated with highly unsteady flames. This work aims to compute the broadband combustion noise spectrum for a realistic aeroengine combustor, and to compare with available measured noise data on a demonstrator aeroengine. A low-order linear network model is applied to a demonstrator engine combustor to obtain the transfer function that relates to unsteadiness in the rate of heat release, acoustic, entropic and vortical fluctuations. A spectral model is used for the heat release rate fluctuation, which is the source of the noise. The mean flow of the aeroengine combustor required as input data to this spectral model is obtained from RANS simulations. The computed acoustic field for a low-medium power setting indicates that the models used in this study capture the main characteristics of the broadband spectral shape of combustion noise. Reasonable agreement with the measured spectral level is achieved.The current research has been conducted under UK Technology Strategy Board contract TP11/HVM/6/I/AB201K.This is the accepted manuscript. The final published version is available from ARC at http://arc.aiaa.org/doi/abs/10.2514/1.B34857. Copyright © 2013 by the authors. Published by the American Institute of Aeronautics and Astronautics, Inc., with permission

    Assessment of the Contribution of Surface Roughness to Airframe Noise

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    The generation of sound by turbulent boundary-layer flow at low Mach number over a rough wall is investigated by applying a theoretical model that describes the scattering of the turbulence near field into sound by roughness elements. Attention is focused on the numerical method to approximately quantify the absolute level of far-field radiated roughness noise. Models for the source statistics are obtained by scaling smooth-wall data by the increased skin friction velocity and boundary-layer thickness for a rough surface. Numerical integration is performed to determine the roughness noise, and it reproduces the spectral characteristics of the available empirical formula and experimental data. Experiments are conducted to measure the radiated sound from two rough plates in an open jet. The measured noise spectra of the rough plates are above that of a smooth plate in 1–2.5 kHz frequency and exhibit reasonable agreement with the predicted level. Estimates of the roughness noise for a Boeing 757 sized aircraft wing with idealized levels of surface roughness show that in the high-frequency region the sound radiated from surface roughness may exceed that from the trailing edge, and higher overall sound pressure levels are observed for the roughness noise. The trailing edge noise is also enhanced by surface roughness somewhat. A parametric study indicates that roughness height and roughness density significantly affect the roughness noise with roughness height having the dominant effect. The roughness noise directivity varies with different levels of surface roughness

    Acoustic and entropy waves in nozzles in combustion noise framework

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    A low-order model is presented to study the propagation and interaction of acoustic and entropic perturbations through a convergent-divergent nozzle. The calculations deal with choked, unchoked, as well as compact and noncompact nozzles. In the choked case, a normal shock exists in the divergent section of the nozzle. First, for circumferential waves and for a compact choked nozzle, it is shown that the pressure, entropy, and vorticity perturbations at the nozzle outlet can be obtained directly from the perturbations at the nozzle inlet. Thus, for the choked case, there is no need to model either the linear waves or the mean flow within the nozzle. Then, to validate the models developed, cylindrical configurations corresponding to the so-called Entropy Wave Generator and Hot Acoustic Testrig are studied. For the Entropy Wave Generator, an entropy wave is generated upstream of a nozzle by an electrical heating device, and for the Hot Acoustic Testrig, a speaker is used to generate pressure waves. In these two configurations and for the choked case, the supersonic region between the nozzle throat and the normal shock is assumed to be acoustically compact. The results of the low-order model are found to give excellent agreement with the experimental results of the Entropy Wave Generator and Hot Acoustic Testrig. To give insight into the physics, the model is used to undertake a parametric study for a range of nozzle lengths and shock strengths. The low-order model is finally used to calculate the direct to indirect (entropy and vorticity) combustion noise ratio for an idealized thin annular combustor. For this model combustor, the direct acoustic noise is found to dominate within the combustor, whereas the entropy indirect noise is found to be the main source of noise downstream of the choked nozzle. The indirect vorticity noise has a negligible contribution

    Low-Order Modeling of Combustion Noise in an Aero-Engine: The Effect of Entropy Dispersion

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    The present work studies the effect of entropy dispersion on the level of combustion noise at the turbine outlet of the Rolls-Royce ANTLE aero-engine. A new model for the decay of entropy waves, based on modeling dispersion effects, is developed and utilized in a low-order network model of the combustor (i.e., LOTAN code that solves the unsteady Euler equations). The proposed model for the dispersion of entropy waves only requires the mean velocity field as an input, obtained by Reynolds-averaged Navier–Stokes (RANS) computations of the demonstrator combustor. LOTAN is then coupled with a low-order model code (LINEARB) based on the semi-actuator disk model that studies propagation of combustion noise through turbine blades. Thus, by combining LOTAN and LINERAB, the combustion noise and its counterparts, direct and indirect noise, generated at the turbine exit are predicted. In comparison with experimental data, it is found that without the inclusion of entropy dispersion, the level of combustion noise at the turbine exit is overpredicted by almost 2 orders of magnitude. The introduction of entropy dispersion in LOTAN results in a much better agreement with the experimental data, highlighting the importance of entropy wave dispersion for the prediction of combustion noise in real engines. In more detail, the agreement with the experiment for high and low frequencies was very good. At intermediate frequencies, the experimental measurements are still overpredicted; however, the predicted noise is much smaller compared to the case without entropy dispersion. This discrepancy is attributed to (i) the role of turbulent mixing in the overall decay of the entropy fluctuations inside the combustor, not considered in the model developed for the decay of entropy waves, and (ii) the absence of a proper model in LINEARB for the decay of entropy waves as they pass through the turbine blade rows. These are areas that still need further development to improve the prediction of low-order network codes.</jats:p

    G-equation modelling of thermo-acoustic oscillations of partially-premixed flames

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    Numerical simulations aid combustor design to avoid and reduce thermo-acoustic oscillations. Non-linear heat release rate estimation and its modelling are essential for the prediction of saturation amplitudes of limit cycles. The heat release dynamics of flames can be approximated by a Flame Describing Function (FDF). To calculate an FDF, a wide range of forcing amplitudes and frequencies needs to be considered. For this reason, we present a computationally inexpensive level-set approach, which accounts for equivalence ratio perturbations on flames with arbitrarily-complex shapes. The influence of flame parameters and modelling approaches on flame describing functions and time delay coefficient distributions are discussed in detail. The numerically-obtained flame describing functions are compared with experimental data and used in an acoustic network model for limit cycle prediction. A reasonable agreement of the heat release gain and limit cycle frequency is achieved even with a simplistic, analytical velocity fluctuation model. However, the phase decay is over-predicted. For sophisticated flame shapes, only the realistic modelling of large-scale flow structures allows the correct phase decay predictions of the heat release rate response.This work was conducted within the EU 7th Framework Project Joint Technology Initiatives - Clean Sky (AMEL- Advanced Methods for the Prediction of Lean-burn Combustor Unsteady Phenomena), project number: JTI-CS-2013-3-SAGE- 06-009 / 641453. This work was performed using the Darwin Supercomputer of the University of Cambridge High Performance Computing Service (http://www.hpc.cam.ac.uk/), provided by Dell Inc. using Strategic Research Infrastructure Funding from the Higher Education Funding Council for England and funding from the Science and Technology Facilities Council
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