Julien de Rosny

Elastic wave generated by granular impact on rough and erodible surfaces

The elastic waves generated by impactors hitting rough and erodible surfaces are studied. For this purpose, beads of variable materials, diameters, and velocities are dropped on (i) a smooth PMMA plate, (ii) stuck glass beads on the PMMA plate to create roughness, and (iii) the rough plate covered with layers of free particles to investigate erodible beds. The Hertz model validity to describe impacts on a smooth surface is confirmed. For rough and erodible surfaces, an empirical scaling law that relates the elastic energy to the radius Rb and normal velocity Vz of the impactor is deduced from experimental data. In addition, the radiated elastic energy is found to decrease exponentially with respect to the bed thickness. Lastly, we show that the variability of the elastic energy among shocks increases from some percents to 70% between smooth and erodible surfaces. This work is a first step to better quantify seismic emissions of rock impacts in natural environment, in particular on unconsolidated soils.

Link Between the Dynamics of Granular Flows and the Generated Seismic Signal: Insights From Laboratory Experiments

Granular column collapse experiments have been conducted on a flat rough surface tilted at various angles with synchronous measurements of the flow dynamics and the emitted seismic signal. Our results show that the ratio of radiated seismic energy to potential energy lost by the granular flows decreases slightly from 0.033% to 0.017% with increasing slope angle on a poly(methyl methacrylate) (acrylic) plate. This is about 90 times lower than for the impact of a single particle of the same diameter. The experimental granular flows generated signals with frequencies lower than 20 kHz, with a mean value around 5 kHz, which are shown to be similar to the frequencies emitted by a single-particle impact. The rise phase and maxima of the amplitude and frequencies of the seismic signals generated by our experimental granular flows are mostly controlled by flow motion in the direction normal to the slope, while their decay phase depends on downslope particle speeds. The granular flow regime changes from dense to more agitated flows above a critical slope angle that is about half the friction angle of the granular material. This change is reflected in (1) the shape of the temporal variation of the seismic amplitude and frequencies, with a decay phase lasting much longer and (2) the shape of the cumulative radiated seismic energy, which changes above the same critical slope angle. Implications of these results for the interpretation of seismic emissions from experimental and natural granular flows are discussed.

Green's function retrieval and fluctuations of cross density of states in multiple-scattering media

In this work we derive the average and the variance of the cross-correlation of a noise wavefield. The noise cross-correlation function (NCF) is widely used to passively estimate the Greens function between two probes and is proportional to the cross density of states (CDOS) in photonic and plasmonic systems. We first explain from the ladder approximation how the diffusion halo plays the role of secondary sources to reconstruct the mean Greens function. We then show that fluctuations of NCF are governed by several non-Gaussian correlations. An infinite-range correlation term dominates fluctuations of NCF-CDOS and proves that NCF is not a self-averaging quantity with respect to the plurality of noise sources. The link between these correlations and the intensity ones is highlighted. These results are supported by numerical simulations and are of importance for passive imaging applications and material science.

Noise correlation in a metamaterial: From laboratory to field data

In the METAFORET experiment, a seismic survey is conducted in a 120 m×120 m flat area, partly occupied by a relatively regular grid of tall pine trees, and partly by a canola field. We study the scattering effects of trees on cross correlations of ambient signal. A wave field is generated by several arrays of sources and recorded at a dense array of receivers within the area of interest. In parallel, we conduct a lab experiment, where the Earths subsurface and the trees (resonators) are idealized by a thin elastic (aluminum) plate and an array of rods, respectively. The Lamb waves propagating in plate are inherently 2-D and dispersive; thus, a good analogue of seismic surface waves observed in field data. Based on the reciprocity theorem, we can treat receivers as sources and vice-versa, resulting in a virtually uniform source distribution. We auto-correlate recordings corresponding to each virtual source-receiver pair, and visualize the auto-correlation maximum as a function of virtual-source location: this provides a map of energy contributed by virtual sources, inside and outside the region of resonators. From that, we identify the metamaterial position as well as bandgap and propagation band. Results from field and laboratory data are compared. In the METAFORET experiment, a seismic survey is conducted in a 120 m×120 m flat area, partly occupied by a relatively regular grid of tall pine trees, and partly by a canola field. We study the scattering effects of trees on cross correlations of ambient signal. A wave field is generated by several arrays of sources and recorded at a dense array of receivers within the area of interest. In parallel, we conduct a lab experiment, where the Earths subsurface and the trees (resonators) are idealized by a thin elastic (aluminum) plate and an array of rods, respectively. The Lamb waves propagating in plate are inherently 2-D and dispersive; thus, a good analogue of seismic surface waves observed in field data. Based on the reciprocity theorem, we can treat receivers as sources and vice-versa, resulting in a virtually uniform source distribution. We auto-correlate recordings corresponding to each virtual source-receiver pair, and visualize the auto-correlation maximum as a function of virtual-source locatio...

Network-based detection and classification of seismo-volcanic tremors: example from the Klyuchevskoy volcanic group in Kamchatka: NETWORK-BASED CLASSIFICATION OF TREMORS

We develop a network-based method for detecting and classifying seismovolcanic tremors. The proposed approach exploits the coherence of tremor signals across the network that is estimated from the array covariance matrix. The method is applied to four and a half years of continuous seismic data recorded by 19 permanent seismic stations in the vicinity of the Klyuchevskoy volcanic group in Kamchatka (Russia), where five volcanoes were erupting during the considered time period. We compute and analyze daily covariance matrices together with their eigenvalues and eigenvectors. As a first step, most coherent signals corresponding to dominating tremor sources are detected based on the width of the covariance matrix eigenvalues distribution. Thus, volcanic tremors of the two volcanoes known as most active during the considered period, Klyuchevskoy and Tolbachik, are efficiently detected. As a next step, we consider the daily array covariance matrix’s first eigenvector. Our main hypothesis is that these eigenvectors represent the principal components of the daily seismic wavefield and, for days with tremor activity, characterize dominant tremor sources. Those daily first eigenvectors, which can be used as network-based fingerprints of tremor sources, are then grouped into clusters using correlation coefficient as a measure of the vector similarity. As a result, we identify seven clusters associated with different periods of activity of four volcanoes: Tolbachik, Klyuchevskoy, Shiveluch, and Kizimen. The developed method does not require a priori knowledge and is fully automatic; and the database of the network-based tremor fingerprints can be continuously enriched with newly available data.

Modeling of an active terahertz imaging system in brownout conditions

We present a theoretical evaluation of a subterahertz (subTHz) system to image through a scattering medium composed of scatterers of sizes close to the wavelength. We specifically study the case of sand grain clouds created by helicopter rotor airflow during landing in arid areas. The different powers received by one pixel of a matrix made of subTHz sensors are identified. Photometric and antenna-based sensors are considered. Besides the thermal contribution to the noise, we focus our attention on the radiation backscattered by the brownout. It appears that a configuration where the source and the camera are distant is the most promising configuration and is realistic for embedded systems.

Green’s Function Retrieval with Absorbing Probes in Reverberating Cavities

The cross-correlation of a diffuse wave field converges toward the difference between the anticausal and causal Greens functions between two points. This property has paved the way to passive imaging using ambient noise sources. In this Letter, we investigate Greens function retrieval in electromagnetism. Using a model based on the fluctuation dissipation theorem, we demonstrate theoretically that the cross-correlation function strongly depends on the absorption properties of the receivers. This is confirmed in measurements within a reverberation chamber. In contrast to measurements with noninvasive probes, we show that only the anticausal Greens function can be retrieved with a matched antenna. Finally, we interpret this result as an equivalent time-reversal experiment with an electromagnetic sink.

Passive flaw detection and localization in thin plate from ambient noise cross-correlation

Passive structural health monitoring (SHM) is an emerging technology. More than 10 years ago, it has been shown that transient response between two sensors can be passively estimated from cross-correlation of ambient noise. The work presented here is an experimental application of this approach dedicated to detect the occurrence of flaws on a thin aluminum plate. The detection sensitivity is directly related to the fidelity of the estimation of the transient response. Using a laser vibrometer, we show that it strongly depends on the number of uncorrelated noise sources. An artificial damage is detected from the difference between the cross-correlation matrices measured before and after defect appearance. To localize the defect, a beamforming array processing is applied on the matrix. The resolution can be as small as half a wavelength.