Simulation of interaction phenomena between ultrasonic waves and metallic microstructures for imaging and characterization
The interaction of waves with matter strongly depends on the frequency of these waves and on the scale of their wavelengths relative to the properties of the medium under consideration. In the context of ultrasonic imaging applications that are of interest to us, the relevant length scales for metals are generally on the order of millimeters (from tenths to several tens of millimeters). Depending on the manufacturing processes used, metallic media—often anisotropic—may also exhibit microstructures with heterogeneities of similar characteristic dimensions. As a result, ultrasonic waves propagating through metals can, under certain circumstances, be significantly affected by these microstructures. This may hinder some ultrasonic techniques (due to attenuation or structural noise), or conversely, offer an opportunity to estimate local properties of the inspected metal.
The general objective of the proposed PhD thesis is to deepen the understanding of the relationship between microstructure and ultrasonic wave behavior for broad classes of materials, leveraging the combined expertise of LEM3 in virtual microstructure generation and CEA in ultrasonic wave propagation simulation.
The proposed work will combine the acquisition and analysis of experimental data (both material and ultrasonic), the use of simulation tools, and statistical data processing. This will enable an analysis of wave behavior across material classes, and possibly the development of inversion procedures to characterize a microstructure based on ultrasonic datasets. The combination of these methods will support a holistic approach, contributing to significant advancements in the field.
Development of new strategies for robotic computed tomography with variable magnification
The Department of Numerical Instrumentation joins expertise on different research fields through experimental and software platforms. In the Monitoring, Control and Diagnostic Unit, one of the important research areas is the industrial inspection with X-ray methods. Within this framework, a robotic inspection facility is being employed for innovative research and validation of new algorithms and on instrumentation aspects.
One of the most important features of robotic inspection is the possibility to scan large samples. In most application cases, region-of-interest areas are defined, for which a higher spatial resolution is targeted. In this context, a research program covering several topics is proposed, with the main objective of facilitating the setup and the use of the robotic inspection configuration for industrial application cases. A focus can be set on one or two research topics, depending on the background and on personal R&D interests and initiatives of the candidate.
A first topic will consist of developing CT reconstruction algorithms for a scan configuration using a variable magnification ratio, in a first phase with analytical algorithms such as the one proposed by Dennerlein [1] and then to adapt iterative reconstruction algorithms of SART type.
A second topic will consist on a work related to adapt the algorithms towards a multi-resolution representation of the reconstructed volumes, through octree or wavelet decomposition. An approach involving the correlation of experimental data to the CAD model of the sample will allow a better implementation in order to improve the VOI (volume of interest) tomography.
A third topic focused on instrumentation will deal with the experimental validation and additionally it will aim to develop a system capable to verify the accurate positioning of the scene elements with the help of precision distance sensors. A simultaneous measure of the distance source - to part surface together with the radiographic image will allow implementing corrections for positioning errors for every scan point and in a second phase to use this additional information directly in the reconstruction process.
High mobility mobile manipulator control in a dynamic context
The development of mobile manipulators capable of adapting to new conditions is a major step forward in the development of new means of production, whether for industrial or agricultural applications. Such technologies enable repetitive tasks to be carried out with precision and without the constraints of limited workspace. Nevertheless, the efficiency of such robots depends on their adaptation to the variability of the evolutionary context and the task to be performed. This thesis therefore proposes to design mechanisms for adapting the sensory-motor behaviors of this type of robot, in order to ensure that their actions are appropriate to the situation. It envisages extending the reconfiguration capabilities of perception and control approaches through the contribution of Artificial Intelligence, here understood in the sense of deep learning. The aim is to develop new decision-making architectures capable of optimizing robotic behaviors for mobile handling in changing contexts (notably indoor-outdoor), and for carrying out a range of precision tasks.
Giant magnetoresistance resistors for local characterization of surface magnetic state: towards Non-Destructive Testing (NDT) applications
CIFRE thesis in the field of non-destructive testing using magnetic sensors in collaboration with 3 partners:
Laboratoire de Nanomagnétisme et Oxyde (SPEC/LNO) du CEA Paris-Saclay
Laboratoire de Génie Electrique et Ferroélectricité (LGEF) de l’INSA Lyon
Entreprise CmPhy
3D ultrasound imaging using orthogonal row and column addressing of the matrix array for ultrasonic NDT
This thesis is part of the activities of the Digital Instrumentation Department (DIN) in Non-Destructive Testing (NDT), and aims to design a new, fast and advanced 3D ultrasound imaging method using matrix arrays. The aim will be to produce three-dimensional ultrasound images of the internal volume of a structure that may contain defects (e.g. cracks), as realistically as possible, with improved performance in terms of data acquisition and 3D image computation time. The proposed method will be based on an approach developed in medical imaging based on Row and Column Addressed (RCA) arrays. The first part will focus on the development of new data acquisition strategies for matrix arrays and associated ultrafast 3D imaging using RCA approach in order to deal with conventional NDT inspection configurations. In the second part, developed methods will be validated on simulated data and evaluated on experimental data acquired with a conventional matrix array of 16x16 elements operating in RCA mode. Finally, a real-time proof of concept will be demonstrated by implementing the new 3D imaging methods in a laboratory acquisition system.