An efficient frequency-domain algorithm for wave scattering problems with application to jet noise

This paper presents a pseudo-time-step method to calculate a (vector) Green function for the adjoint linearised Euler equations as a scattering problem in the frequency domain, for use as a jet-noise propagation prediction tool. A method of selecting the acoustics-related solution in a truncated spatial domain while suppressing any possible shear-layer-type instability is presented. Numerical tests for 3-D axisymmetrical parallel mean flows against semi-analytical reference solutions indicate that the new iterative algorithm is capable of producing accurate solutions with modest computational requirements.

Adjoint linearised Euler solver in the frequency domain for jet noise modelling

The paper is devoted to extending the new efficient frequency-domain method of adjoint Green's function calculation to curvilinear multi-block RANS domains for middle and farfield sound computations. Numerical details of the method such as grids, boundary conditions and convergence acceleration are discussed. Two acoustic source models are considered in conjunction with the method and acoustic modelling results are presented for a benchmark low-Reynolds-number jet case.

TOPS (Task optimization in the presence of signal-dependent noise) model

This paper proposes a movement trajectory planning model, which is a maximum task achievement model in which signal-dependent noise is added to the movement command. In the proposed model, two optimization criteria are combined, maximum task achievement and minimum energy consumption. The proposed model has the feature that the end-point boundary conditions for position, velocity, and acceleration need not be prespecified. Consequently, the method can be applied not only to the simple point-to-point movement, but to any task. In the method in this paper, the hand trajectory is derived by a psychophysical experiment and a numerical experiment for the case in which the target is not stationary, but is a moving region. It is shown that the trajectory predicted from the minimum jerk model or the minimum torque change model differs considerably from the results of the psychophysical experiment. But the trajectory predicted from the maximum task achievement model shows good qualitative agreement with the hand trajectory obtained from the psychophysical experiment. © 2004 Wiley Periodicals, Inc.

On computing the physical sources of jet noise

We derive a closed system of equations that relates the acoustically radiating flow variables to the sources of sound for homentropic flows. We use radiating density, momentum density and modified pressure as the dependent variables which leads to simple source terms for the momentum equations. The source terms involve the non-radiating parts of the density and momentum density fields. These non-radiating components are obtained by removing the radiating wavenumbers in the Fourier domain. We demonstrate the usefulness of this new technique on an axi-symmetric jet solution of the Navier-Stokes equations, obtained by direct numerical simulation (DNS). The dominant source term is proportional to the square of the non-radiating part of the axial momentum density. We compare the sound sources to that obtained by an acoustic analogy and find that they have more realistic physical properties. Their frequency content and amplitudes are consistent with. We validate the sources by computing the radiating sound field and comparing it to the DNS solution. © 2010 by S. Sinayoko, A. Agarwal.

Once again on the importance of propagation effects for jet noise modelling

Several turbulent jet noise models starting from the classical Lighthill acoustic analogy to state-of-the art models are considered. No attempt is made to present any complete overview of jet noise theories. Instead, the aim is to emphasise the importance of sound generation and meanflow effects for the understanding and prediction of jet noise. For a recent acoustic analogy model, the consequences of jet flow simplification on the predicted sound spectra shape and the effective noise source location in the jet are discussed. © 2010 by the American Institute of Aeronautics and Astronautics, Inc.

Extended VTS for noise-robust speech recognition

Model compensation is a standard way of improving the robustness of speech recognition systems to noise. A number of popular schemes are based on vector Taylor series (VTS) compensation, which uses a linear approximation to represent the influence of noise on the clean speech. To compensate the dynamic parameters, the continuous time approximation is often used. This approximation uses a point estimate of the gradient, which fails to take into account that dynamic coefficients are a function of a number of consecutive static coefficients. In this paper, the accuracy of dynamic parameter compensation is improved by representing the dynamic features as a linear transformation of a window of static features. A modified version of VTS compensation is applied to the distribution of the window of static features and, importantly, their correlations. These compensated distributions are then transformed to distributions over standard static and dynamic features. With this improved approximation, it is also possible to obtain full-covariance corrupted speech distributions. This addresses the correlation changes that occur in noise. The proposed scheme outperformed the standard VTS scheme by 10% to 20% relative on a range of tasks. © 2006 IEEE.