345 resultados para noise filtering


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The work in this paper forms part of a project on the use of large eddy simulation (LES) for broadband rotor-stator interaction noise prediction. Here we focus on LES of the flow field near a fan blade trailing edge. The first part of the paper aims to evaluate LES suitability for predicting the near-field velocity field for a blunt NACA-0012 airfoil at moderate Reynolds numbers (2× 10 5 and 4× 10 5). Preliminary computations of turbulent mean and root-mean-square velocities, as well as energy spectra at the trailing edge, are compared with those from a recent experiment.1 The second part of the paper describes preliminary progress on an LES calculation of the fan wakes on a fan rig. 2 The CFD code uses a mixed element unstructured mesh with a median dual control volume. A wall-adapting local eddy-viscosity sub-grid scale model is employed. A very small amount of numerical dissipation is added in the numerical scheme to keep the compressible solver stable. Further results for the fan turbulentmean and RMS velocity, and especially the aeroacoustics field will be presented at a later stage. Copyright © 2008 by Qinling LI, Nigel Peake & Mark Savill.

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This work forms part of a project on the use of large eddy simulation (LES) for broadband rotor-stator interaction noise prediction. In this paper, we focus on LES calculations of noise sources on and close to a blade trailing edge. We consider two test cases; one an isolated NACA0012 airfoil in flow, and the other an industry-standard rotating fan. In the first case, turbulent mean and RMS velocities and energy spectra at different locations are compared with those from experiment. 1,2The sound generated by the unsteady pressure fluctuations on the airfoil surface and by the flow turbulence will be predicted using a Ffowcs Williams Hawkings (FW-H) surface. In the second case, unsteady flow and acoustic fields around the blade passage 3 are presented for a refined mesh, and the rotor-stator tonal noise will be predicted by using the rotor-wake mean velocity profile and the methodology described in Lloyd & Peake 4. Copyright © 2009 by Qinling Li, Nigel Peake & Mark Savill.

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Turbulence, as naturally occurs in the atmosphere, is known to become highly anisotropic in the presence of the flow induced by a propeller. This turbulent distortion, caused by the streamtube contraction, significantly affects the tonal content of the radiated noise due to turbulence ingestion. We present here an analytic framework in which turbulent distortion may be assessed for any irrotational mean flow which approaches uniform axial flow far upstream. Sound spectra are presented for the case of two rotors in close proximity, for which the distortion is asymmetric. Quantities such as the turbulence spectrum at the rotor face and sound directivity then vary with azimuthal angle φ. © 2010 by Rosalyn A.V. Robison & N. Peake.

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A method for modelling and predicting the noise generated by the interaction between the unsteady wake shed from the rotor and a downstream row of stators in a modern ultra-high bypass ducted turbofan engine is described. An analytically-based model is developed to account for three main features of the problem. First, the way in which a typical unsteady wake disturbance from the rotor interacts and is distorted by the mean swirling flow as it propagates downstream. The analysis allows for the inclusion of mean entropy gradients and entropy perturbations. Second, the effects of real stator-blade geometry and proper representation of the genuinely three-dimensional nature of the problem. Third, to model the propagation of the resulting noise back upstream in mean swirling flow. The analytical nature of the problem allows for the inclusion of all wake harmonics and enables the response at all blade passing frequencies to be determined. Example results are presented for an initial wake distribution corresponding to a genuine rotor configuration. Comparisons between numerical data and the asymptotic model for the wake evolution are made. Copyright © 2004 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

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Statistical model-based methods are presented for the reconstruction of autocorrelated signals in impulsive plus continuous noise environments. Signals are modelled as autoregressive and noise sources as discrete and continuous mixtures of Gaussians, allowing for robustness in highly impulsive and non-Gaussian environments. Markov Chain Monte Carlo methods are used for reconstruction of the corrupted waveforms within a Bayesian probabilistic framework and results are presented for contaminated voice and audio signals.

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In this paper a semi analytic model for rotor - stator broadband noise is presented. The work can be split into two sections. The first examines the distortion of the rotor wake in mean swirling flow, downstream of the fan. Previous work by Cooper and Peake4 is extended to include dissipative effects. In the second section we consider the interaction of this gust with the downstream stator row. We examine the way in which an unsteady pressure field is generated by the interaction of this wake flow with the stator blades and obtain estimates for the radiated noise. A new method is presented to extend the well known LINSUB code to the third dimension to capture the effect of the spanwise wavenumber and stator lean and sweep. Copyright © 2008 by Adrian Lloyd and Nigel Peake.

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We compare experimental results showing stable dissipative-soliton solutions exist in mode-locked lasers with ultra-large normal dispersion (as large as 21.5 ps2), with both the analytic framework provided by Haus' master-equation and full numerical simulations. © 2010 Optical Society of America.

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We investigate how sensitive Gallager's codes are, when decoded by the sum-product algorithm, to the assumed noise level. We have found a remarkably simple function that fits the empirical results as a function of the actual noise level at both high and low noise levels. © 2004 Elsevier B.V.

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We investigate how sensitive Gallager's codes are, when decoded by the sum-product algorithm, to the assumed noise level. We have found a remarkably simple function that fits the empirical results as a function of the actual noise level at both high and low noise levels. ©2003 Published by Elsevier Science B. V.

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Approximate Bayesian computation (ABC) has become a popular technique to facilitate Bayesian inference from complex models. In this article we present an ABC approximation designed to perform biased filtering for a Hidden Markov Model when the likelihood function is intractable. We use a sequential Monte Carlo (SMC) algorithm to both fit and sample from our ABC approximation of the target probability density. This approach is shown to, empirically, be more accurate w.r.t.~the original filter than competing methods. The theoretical bias of our method is investigated; it is shown that the bias goes to zero at the expense of increased computational effort. Our approach is illustrated on a constrained sequential lasso for portfolio allocation to 15 constituents of the FTSE 100 share index.