A LES-Langevin model for turbulence

We propose a new model of turbulence for use in large-eddy simulations (LES). The turbulent force, represented here by the turbulent Lamb vector, is divided in two contributions. The contribution including only subfilter fields is deterministically modeled through a classical eddy-viscosity. The other contribution including both filtered and subfilter scales is dynamically computed as solution of a generalized (stochastic) Langevin equation. This equation is derived using Rapid Distortion Theory (RDT) applied to the subfilter scales. The general friction operator therefore includes both advection and stretching by the resolved scale. The stochastic noise is derived as the sum of a contribution from the energy cascade and a contribution from the pressure. The LES model is thus made of an equation for the resolved scale, including the turbulent force, and a generalized Langevin equation integrated on a twice-finer grid. The model is validated by comparison to DNS and is tested against classical LES models for isotropic homogeneous turbulence, based on eddy viscosity. We show that even in this situation, where no walls are present, our inclusion of backscatter through the Langevin equation results in a better description of the flow.Comment: 18 pages, 14 figures, to appear in Eur. Phys. J.

Blind MultiChannel Identification and Equalization for Dereverberation and Noise Reduction based on Convolutive Transfer Function

This paper addresses the problems of blind channel identification and multichannel equalization for speech dereverberation and noise reduction. The time-domain cross-relation method is not suitable for blind room impulse response identification, due to the near-common zeros of the long impulse responses. We extend the cross-relation method to the short-time Fourier transform (STFT) domain, in which the time-domain impulse responses are approximately represented by the convolutive transfer functions (CTFs) with much less coefficients. The CTFs suffer from the common zeros caused by the oversampled STFT. We propose to identify CTFs based on the STFT with the oversampled signals and the critical sampled CTFs, which is a good compromise between the frequency aliasing of the signals and the common zeros problem of CTFs. In addition, a normalization of the CTFs is proposed to remove the gain ambiguity across sub-bands. In the STFT domain, the identified CTFs is used for multichannel equalization, in which the sparsity of speech signals is exploited. We propose to perform inverse filtering by minimizing the $\ell_1$-norm of the source signal with the relaxed $\ell_2$-norm fitting error between the micophone signals and the convolution of the estimated source signal and the CTFs used as a constraint. This method is advantageous in that the noise can be reduced by relaxing the $\ell_2$-norm to a tolerance corresponding to the noise power, and the tolerance can be automatically set. The experiments confirm the efficiency of the proposed method even under conditions with high reverberation levels and intense noise.Comment: 13 pages, 5 figures, 5 table

Complete Algebraic Reconstruction of Piecewise-Smooth Functions from Fourier Data

In this paper we provide a reconstruction algorithm for piecewise-smooth functions with a-priori known smoothness and number of discontinuities, from their Fourier coefficients, posessing the maximal possible asymptotic rate of convergence -- including the positions of the discontinuities and the pointwise values of the function. This algorithm is a modification of our earlier method, which is in turn based on the algebraic method of K.Eckhoff proposed in the 1990s. The key ingredient of the new algorithm is to use a different set of Eckhoff's equations for reconstructing the location of each discontinuity. Instead of consecutive Fourier samples, we propose to use a "decimated" set which is evenly spread throughout the spectrum

Decimative Spectral Estimation with Unconstrained Model Order

This paper presents a new state-space method for spectral estimation that performs decimation by any factor, it makes use of the full set of data and brings further apart the poles under consideration, while imposing almost no constraints to the size of the Hankel matrix (model order), as decimation increases. It is compared against two previously proposed techniques for spectral estimation (along with derived decimative versions), that lie among the most promising methods in the field of spectroscopy, where accuracy of parameter estimation is of utmost importance. Moreover, it is compared against a state-of-the-art purely decimative method proposed in literature. Experiments performed on simulated NMR signals prove the new method to be more robust, especially for low signal-to-noise ratio

Laser doppler vibrometer for efficient structural health monitoring

The research effort in this thesis is devoted to develop techniques to accurately and rapidly identify the location, orientation, and magnitude of the defects by using structural health monitoring concepts that use Laser Doppler Vibrometer as a non-contact sensor with multi-point sensing capability. The first research area addresses the formulation and validation of an innovative Damage Measure that is based on the ratios of the strain energy distributions of the damaged and undamaged structure. The innovations include use of a single set of actuator/sensor pair to excite and detect the responses of a structure for low frequency vibrations as well as guided wave propagation studies. A second new capability is the estimation of the Damage Measure without requiring any knowledge of the undamaged baseline structure. This method is made possible because of the development of these new technologies: Spatial Decimation and Wavenumber/Frequency filtering. The third contribution is to develop analytical models for the structural dynamics of damaged structure and seek solutions that use perturbation methods to detect damage in a plate structure. The fourth contribution is the development of a comprehensive damage detection technique over a wide frequency dynamic range. The fifth topic of research involves automation in Structural Health Monitoring based on the comprehensive Damage Measure formulation. Under the control of software the Scanning Laser Doppler Vibrometer is used to acquire the low frequency vibration mode data for a coarse identification of all the suspect regions of damage using a threshold criterion on the Damage Measure. Each suspect region of damage is further investigated using the high frequency elastic wave propagation to clearly identify the location, orientation, and extent of the damage. The computer control of the Laser Doppler Vibrometer and a quantitative assessment of the damage provide the enabling technologies for the automation proof of concept. Finally the developed techniques of damage detection are successfully demonstrated on practical structures such as a turbine blade in the laboratory and an F-15 vertical tail in field maintenance conditionsPh.D.Committee Chair: Hanagud, Sathya; Committee Member: Apetre, Nicole; Committee Member: Engelstad, Steve; Committee Member: Glass, Brian; Committee Member: Kardomateas, George; Committee Member: Ruzzene, Massim

Sidescan Sonar Image Enchancement Using a Decomposition Based on Orthogonal Functions. Applications with Chebyshev Polynomials

A method is presented to remove from sidescan sonar images of the seafloor, artifacts that are clearly unrelated to the backscattering properties of the seafloor. A spectral analysis performed on a ping by ping basis proved to be well suited to the problem. The technique relies on a decomposition using Chebyshev polynomials. This stochastic method does not require a priori knowledge of deterministic parameters. It deals with the low spatial frequency components of the image whose wavelengths are not very small compared to the swath width. Applications to sidescan sonar images obtained with the SeaMARC LI system are presented