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Since its creation in 2013, Sivienn explores the frontier between theoretical and applied mathematics.

Originally, Sivienn proposed original imaging strategies, using a correlation-based approach and fitting it to noise signals recorded by passive sensor arrays. Based on applied probability, its techniques are particularly relevant for measured noise signals. In the course of its decade of industrial experience, Sivienn's know-how has extended from non-destructive testing, to neutron noise analysis, or the study of the sound environment under the sea. Recently, Sivienn has turned its attention to mechanical issues such as buckling, friction, and fatigue.

Sivienn calls on the most advanced mathematicians, physicists, and chemists to provide services, from models and scripts to technological bricks, specifically adapted to the use of the data.

Advancing Knowledge

Whether acoustic, elastic, or electromagnetic, waves can be used to probe for information about an unknown medium. In the first step of the probe, transducers in acoustics, seismographs in geophysics, or antennas in electromagnetics generate waves, and an array of receivers records them. In the second numerical step, the recorded data is processed in order to estimate some relevant features of the medium : source or reflector locations and shapes.


When only rough forward models, and limited and noisy data are available, the challenge is to estimate parts of the unknown structure. The whole process consists in detecting and localizing sources and reflectors in order to reconstruct small inclusions and shape deformations.


A breakthrough by the introduction of cross correlations in the noughties have led to a distinctive approach to imaging. This finding originated from unexpected consequences observed in time reversal experiments. Recording waves by a network of receivers and regenerating them into the medium after time reversal, made it possible to focus the waves on the original sources, or on reflectors. Surprisingly, refocusing the waves in a randomly perturbed medium worked much better than it did in a homogeneous one.

Expanding Applications

In multistatic imaging, the central issue is to quantify and understand the trade-offs between data size, computational complexity, signal-to-noise ratio, and resolution. The trade-off between resolution and stability is critical when the data are noisy. Noise may appear in different forms in multistatic imaging. The receivers may be responsible for measurement noise, meaning the recorded data are corrupted by additive and uncorrelated noise. This type of noise is well understood and can be mitigated by classical imaging functions, such as least-square imaging (or full waveform inversion), reverse-time migration or travel-time migration.


The medium can be responsible for noise. The background medium can be heterogeneous, and scattering then produces clutter noise in the data. Clutter noise has a very different structure compared to measurement noise because of its nontrivial correlation properties. Sivienn analyzes the correlations of the recorded signals that carry information about the medium.


The sources can be responsible for noise. They may be imperfectly controlled. Nevertheless, uncontrolled or even ambient noise sources can generate waves that carry information about the medium in their correlations. Sivienn's original approach is to analyze the correlations of the recorded signals and to extract the information contained in them.

Developing Operations

Cross-correlation techniques are used on data from deep seas, oil reservoirs and oil wells. Used to determine signals emitted by more-or-less controlled sources found at the surface, sensor arrays record ambient noise. The cross-correlation techniques make it possible to transform the passive sensors situated in wells into virtual sources.
In seismology, large sensor arrays can be put in place, although emitting sources are generally rare and uncontrolled. Cross-correlation techniques transform data issued from these passive arrays into results equivalent to those issued from active networks. In particular, passive imaging of ambient noise makes it possible to survey volcanoes. The surveillance consists in estimating the functions of the wave equation between pairs of receivers, by cross correlating the signals recorded by a passive receiver.
The underwater environment can be monitored by passive correlation-based acoustics. Cross correlations of the signals recorded by a receiver array can be processed to localize a distant source emitting through a complex environment, such as an oceanic waveguide. Reflectors or anomalies may also be detected using the correlations of signals emitted by ambient noise sources.
The internal mechanical structure in the core of a nuclear reactor can be monitored by a correlation-based analysis of ex-core neutron flux, aiming at characterizing the core's modes of vibration.
Measurements of these modes can be compared to the original calculations of the manufacturer and an anomaly in the modal frequencies and/or mode shapes can be the manifestation of an anomaly in the mechanical structure.
Non destructive testing and structural health monitoring aim at estimating the properties of a material or a structure to detect damage or anomalies. Strategies are available using active and controlled sources, such as ultrasound echography. Sivienn uses signals recorded on a permanent network of passive sensors generated by ambient noise sources.
Sivienn has determined the fields (range of frequencies, size of the antennas, level of heterogeneity of the medium) in which the cross-correlation imaging method is better than conventional methods and which calibration parameters (on the window sizes used in the cross-correlation method) must be chosen.
Our research aims to establish and mathematically understand how the results obtained by Sivienn for scalar waves (pressure waves for example) can be extended for other types of vector waves, by targeting more particularly elastic waves (which contain, besides pressure waves, shear waves and surface waves).

THE OPERATORS

Basile AUDOLY

Basile AUDOLY

Chercheur

BASILE
Corrado MAURINI

Corrado MAURINI

Researcher

CORRADO
Jean-Philippe TOUFFUT

Jean-Philippe TOUFFUT

President

JEAN-PHILIPPE
Josselin GARNIER

Josselin GARNIER

Head of research

JOSSELIN
Laure DUMAZ

Laure DUMAZ

Researcher

LAURE
Vincent Clerc

Vincent CLERC

Researcher

VINCENT

Recruiting

In order to advance the original imaging and signal processing techniques, which it has been developing for the past eleven years, Sivienn is looking for mathematicians who want to develop their scientific skills.
Sivienn's work has successfully focused on the monitoring of buildings, using passive sensors for anomaly detection, on non-destructive testing using ultrasound in concrete, and on monitoring the vibratory modes of uranium rods in reactor cores using neutron flux measurements. Underwater acoustics has been another successful domain, where Sivienn's algorithms made major contributions.
To investigate other fields such as seismic wave communications, Sivienn is recruiting trainees or full-time researchers with a PhD or post-doctoral profile in applied mathematics, with skills in probability/statistics or signal processing and who are familiar with Python programming.

CONTACT

Address
73, rue Léon Bourgeois
91120 Palaiseau

SIVIENN BOOKLET

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