Damage localization based on the reconstructed Green’s function from a diffuse noise field on a thin rectangular aluminum plate

2017 ◽  
Vol 142 (4) ◽  
pp. 2644-2644
Author(s):  
Sun Ah Jung ◽  
Keunhwa Lee ◽  
Woojae Seong
Keyword(s):  
Green’S Function ◽  
Green's Function ◽  
Aluminum Plate ◽  
Damage Localization ◽  
Noise Field ◽  
Diffuse Noise

On surface-generated ambient noise in an upward refracting ocean

1994 ◽  
Vol 346 (1680) ◽  
pp. 321-352 ◽  
Keyword(s):  
Spectral Density ◽  
Green’S Function ◽  
Normal Mode ◽  
Green's Function ◽  
Sound Speed ◽  
Ambient Noise ◽  
Direct Path ◽  
Noise Field ◽  
Cross Spectral Density ◽  
The Cross

Naturally generated ambient noise in the ocean is created by breaking waves, spray and precipitation. Each of these mechanisms produces a pulse of sound that propagates down into the depths of the ocean, and the superposition of all such pulses from across the whole sea surface constitutes the ambient noise field. Since the noise is a stochastic phenomenon, its properties are described in terms of statistical quantities, the most useful being the power spectral density at a point and the cross-spectral density between two points in the field. If these second-order statistical measures are independent of absolute position, the noise field is said to be spatially homogeneous. In the rare case of an isovelocity, deep ocean, the noise field at depths greater than a wavelength or so beneath the surface is spatially homogeneous, consisting of a random superposition of plane waves. A non-uniform sound speed profile, however, introduces wave-front curvature which modifies the situation significantly. the noise exhibits strong spatial homogeneity over length scales that are comparable with the apertures of typical acoustic arrays. Apart from the implications with regard to array performance, this is important in connection with certain aspects of acoustical oceanography, whereby information on the oceanographic environment is extracted from the noise field (Buckingham et al. 1992). Such information is accessible only if the structure of the noise field is well understood. The problem lies in determining the spatial and spectral properties of the noise in a profile. Fundamental to the noise analysis is the Green’s function for the channel, which characterizes the propagation conditions; and yet for most non-uniform sound speed profiles the analysis of the Green's function is intractable. However, there is one profile, designated the inverse-square profile, for which a complete, exact solution for the field has been developed (Buckingham 1991). The inverse-square profile is monotonic increasing with depth, giving rise to upward refractive propagation. Such a profile is found in several ocean environments: the polar oceans, where the temperature and hence the sound speed show a minimum at the surface; the mixed surface layer, extending to a depth of order 100 m in the open ocean; and the ocean-surface bubble layer, occupying the first ten metres or so beneath the surface. An analysis of the noise field in the presence of an inverse square profile, based on the solution for the Green’s function, shows that the cross-spectral density of the noise in the vertical consists of three components: a normal mode sum, representing noise originating largely in distant sources; a direct path contribution, from sources that are more or less overhead; and a near-surface term that is negligible at depths greater than a wavelength. In the theoretical noise spectrum , the normal mode and direct path components are prominent, dominating, respectively, at low and high frequencies. The cross-over frequency depends on the parameters of the profile and attenuation in the medium, but for polar oceans is in the region of several hundred hertz. At a much lower frequency, around 10 Hz, where the polar profile ceases to support normal mode propagation, a minimum appears in the theoretical spectrum . This is the result of a very rapid fall off in the normal mode component of the noise and a slow rise of the direct path component with decreasing frequency. Each of the three components of the vertical cross-spectral density exhibits strong spatial inhomogeneity. This is exemplified by the dramatic dependence of the cross-spectrum on both the mean depth of the sensors and frequency. Although such behaviour adds complexity to the structure of the noise field, this could be advantageous since it allows the possibility of performing inversions on noise cross-spectral data to determine properties of the medium. Recent measurements of low-frequency (50-2000 Hz) and very low-frequency (5-200 Hz) ambient noise spectra in the marginal ice zone of the Greenland Sea, where the sound speed profile is of the inverse-square form, have been compared with the predictions of the new noise theory. There is evidence in the measured spectra that both the normal mode and direct path components of the noise are present with the predicted relative levels. A minimum around 10 Hz is a ubiquitous feature of the VLF spectra, and the LF spectra show a change of slope close to 400 Hz, both of which are in accord with the theory. Along the ice edge a highly non-uniform (spatial) distribution of energetic sources is known to be present, whose effects in the observed spectra are consistent with arguments developed from the inverse-square noise analysis.

Characteristics of surface wave Green’s function for anisotropic ambient seismic noise field — a case study in Limburg, The Netherlands

First Break ◽  
2019 ◽  
Vol 37 (4) ◽  
pp. 83-90
Author(s):  
Soumen Koley ◽  
Henk Jan Bulten ◽  
Jo van den Brand ◽  
Maria Bader ◽  
Frank Linde ◽  
...  
Keyword(s):  
Surface Wave ◽  
The Netherlands ◽  
Green’S Function ◽  
Green's Function ◽  
Seismic Noise ◽  
Ambient Seismic Noise ◽  
Noise Field

GREEN'S FUNCTION MATCHING METHOD FOR REALISTIC CALCULATIONS OF INTERFACES

1985 ◽  
Vol 46 (C4) ◽  
pp. C4-321-C4-329 ◽  
Author(s):  
E. Molinari ◽  
G. B. Bachelet ◽  
M. Altarelli
Keyword(s):  
Green’S Function ◽  
Green's Function ◽  
Matching Method

THE ATOMISTIC GREEN'S FUNCTION METHOD FOR INTERFACIAL PHONON TRANSPORT

2014 ◽  
Vol 17 (N/A) ◽  
pp. 89-145 ◽  
Author(s):  
Sridhar Sadasivam ◽  
Yuhang Che ◽  
Zhen Huang ◽  
Liang Chen ◽  
Satish Kumar ◽  
...  
Keyword(s):  
Green’S Function ◽  
Green's Function ◽  
Function Method ◽  
Phonon Transport ◽  
Green’S Function Method

THE EMPIRICAL GREEN’S FUNCTION TECHNIQUE MODIFICATION FOR ACCELEROGRAM SYNTHESIS IN LOWSEISMICITY REGIONS

2018 ◽  
Vol 12 (5-6) ◽  
pp. 72-80
Author(s):  
A. A. Krylov
Keyword(s):  
Green’S Function ◽  
Green's Function ◽  
Main Shock ◽  
Amplitude Spectrum ◽  
Strong Motion ◽  
Function Technique ◽  
Focal Region ◽  
Empirical Green’S Function ◽  
Epicentral Zone ◽  
Empirical Green's Function

In the absence of strong motion records at the future construction sites, different theoretical and semi-empirical approaches are used to estimate the initial seismic vibrations of the soil. If there are records of weak earthquakes on the site and the parameters of the fault that generates the calculated earthquake are known, then the empirical Green’s function can be used. Initially, the empirical Green’s function method in the formulation of Irikura was applied for main shock record modelling using its aftershocks under the following conditions: the magnitude of the weak event is only 1–2 units smaller than the magnitude of the main shock; the focus of the weak event is localized in the focal region of a strong event, hearth, and it should be the same for both events. However, short-termed local instrumental seismological investigation, especially on seafloor, results usually with weak microearthquakes recordings. The magnitude of the observed micro-earthquakes is much lower than of the modeling event (more than 2). To test whether the method of the empirical Green’s function can be applied under these conditions, the accelerograms of the main shock of the earthquake in L'Aquila (6.04.09) with a magnitude Mw = 6.3 were modelled. The microearthquake with ML = 3,3 (21.05.2011) and unknown origin mechanism located in mainshock’s epicentral zone was used as the empirical Green’s function. It was concluded that the empirical Green’s function is to be preprocessed. The complex Fourier spectrum smoothing by moving average was suggested. After the smoothing the inverses Fourier transform results with new Green’s function. Thus, not only the amplitude spectrum is smoothed out, but also the phase spectrum. After such preliminary processing, the spectra of the calculated accelerograms and recorded correspond to each other much better. The modelling demonstrate good results within frequency range 0,1–10 Hz, considered usually for engineering seismological studies.

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