The present project aims first of all to continue the maturation and the TRL increase (from TRL 4 to TRL 5-6) of MEMS micro-sensors and micro-actuators disruptive technologies, associated electronics and integration solutions, developed in the initial project ANR Astrid CAMELOTT [10 / 2014-01 / 2018]. The main focus will be particularly placed on: 1. increasing the robustness of the transduction, encapsulation and conditioning electronic elements of the solutions developed to satisfy more realistic environment constraints of the targeted applications, 2. the search for weakly (or non-invasive) integration solutions for the modules developed to facilitate their implementation on real terrestrial or flying vehicles, 3. the addition of specific functionalities to embedded electronics (data storage, real-time radio transmissions) in the perspective of a real vehicle test. Secondly, the project aims to highlight wind tunnel tests of maturity demonstrations of the above solutions on three representative and easily declining application configurations highlighting their strengths: 1. an in-situ characterization and control-command of a macroscopic (pulsed or synthetic jet) actuator conventionally used for detachment control and which will have been instrumented using MEMS micro-sensors implanted in the jet expulsion slot, 2. the demonstration of a reactive flow control using MEMS solutions on a motorized shutter without slot, 3. the wind tunnel demonstration of a cavity instability control by MEMS micro-actuators In addition, the project finally plans to implement a MEMS micro-sensor network with all embedded electronics, storage and radio transmissions, on a real flying machine of modest size (ULM or aircraft type CESSNA 337 or a drone with fixed wings) to test their operability in real flight conditions. In this case, the objective is to bring the credibility of the breakthrough developed technologies to potential customers in the targeted application fields. Depending on the results of these tests in real flight conditions, it will be considered an integration for a flight test on a "military"-type plane MB339. Finally, the final phase of the project will focus on the valuation of results from the prime contractors, integrators and "end-users" potentially interested in the solutions developed. A "spin-off" creation for the provision of technologies is also envisaged.

This project is aligned with the "fluid, structures" axis along with "fluid dynamics" and "propulsion and energy flow" sub-axes’ themes of the DGA. Its principal aim is to assess the pressure and force in the near and far fields from non-intrusive volumetric measurements of velocity. Despite the substantial progress made by numerical simulation in fluid mechanics in the last two decades, the study of these complex phenomena by experimental approaches remains essential to the understanding of the underlying physical mechanisms and the study of problems of industrial interest. While different tools exist for flow measurements, one of the most commonly used today remains PIV (particle image velocimetry), which is applied in almost all areas of fluid mechanics. This technique offers the double advantage of simultaneously providing non-intrusive flow visualization and quantitative measurements of velocity. Recently, the development of Tomographic-PIV has demonstrated the ability to obtain three-dimensional measurements of velocity fields in a volume of significant size. Although some limitations of this measurement technique remain today, such as the sensitivity of the reconstruction calibration and the need to have sufficient optical access to the measurement domain from multiple cameras, the resulting three velocity components that are measured in volume is a major asset. This allows the evaluation of quantities such as pressure fields and forces in aerodynamic or hydrodynamic flows. In the framework of this project, the collaborating partners, having benefitted from the experience of a European project on a related problematic, propose novel approaches for 3D pressure assessment. These approaches will be compared to the state of the art and the forces in the near field and far field will be evaluated. This work will be decomposed into three stages. The first stage will be the development of pressure and force evaluation tools that will be validated with the results obtained by numerical simulation. The resolved pressure from a standard integration of the Poisson equation will be compared to methods that either integrate the pressure gradient calculated from the projection of the velocity field on a polynomial basis or that solve a coupled Poisson – boundary condition integral equation. For the calculation of forces, near field approaches based on the momentum equation or on the concept of impulse vorticity and far field approaches based on the calculation of the generating pressure from the speed and the static pressure will be developed and compared with direct measurements of forces using mass balances. The remaining two stages of the project will be the application of these methods on a flow around a flexible hydrodynamic foil, that presents the difficulty of non-stationary and variable surfaces, and the flow around a generic UCAV model in an aerodynamic wind tunnel, which approaches industrial applications. The final objective of this project is to compare the developed methods on these two types of flow and make the tools sufficiently simple and flexible in order to disseminate and apply them in industry.

Diseases affecting small vessels (less than 150µm diameter) are important causes of morbidity and mortality from cardiovascular and cerebrovascular causes, alone or in association with diseases of large arteries. Predictive biomarkers are obtained from vascular imaging for large vessels. Research on these biomarkers has increased considerably in recent years, because they are more predictive of cardiovascular events than traditional risk factors such as blood pressure. However, at present, these biomarkers are mainly dedicated to the study of large arteries (carotid, aorta). There is indeed no procedure allowing quantitative imaging of small vessels which had proved its interest in the care of patients, due to limitations of imaging technology at this scale. The issue is nevertheless important because high blood pressure and diabetes mainly affects small vessels. In recent years, adaptive optics (AO) imaging of the retina has demonstrated its ability to document retinal structures at the micrometer scale in humans. This technology has now reached sufficient technical maturity to enter clinical routine in a short delay. In continuation of a multidisciplinary collaborative project involving ophthalmologists, engineers, researchers and the manufacturer of an AO camera (the iPhot project, funded by ANR TecSan 2009), we incidentally observed that the latest version of the prototype allowed to document the structure of small arteries, so far inaccessible by other imaging methods. This opens the possibility to develop one or more quantitative biomarkers of the microcirculation. The objective of the ReVeal project is to make vascular imaging by AO simple, efficient and medically useful. For this, we will aim at validating technically and medically new biomarkers measured from small vessel images of OA, in an integrated approach combining an interactive technological developments and medical evaluation. This industrial development project includes four workpackages to be undertaken in parallel: 1- transverse and longitudinal evaluation of vascular imaging in controls and well characterized patients through a multidisciplinary medical network (Head: Clinical Investigation Center 503); 2-implementation of new technology solutions dedicated to vascular imaging (responsible: Imagine Eyes, with Onera-DOTA) 3-Development of software for image processing (co-leaders: Onera-DTIM and L2TI), and 4 - Development of software for data analysis (co-leaders: Telecom ParisTech and ISEP). Eventually it is expected that vascular imaging by OA will play a pivotal role in assessing and monitoring treatment against hypertension and diabetes.

In this project, we propose to set up a surface biological decontamination system based on an innovative atmospheric pressure cold plasma jet technique (called plasma bullets) and to study its effect on microbiological targets for military and civilian purposes: bacilli, spores, and cocci. The first step is to conceive and to build a discharge reactor and a high voltage pulses generator that will be used for surface decontamination experiments and for characterization of plasma bullets physical and chemical properties. A parametric study will be performed in order to optimize plasma bullets biocidal effects and to highlight plasma characteristics related to these effects. Finally, we will focus on plasma/surface interaction phenomena as a function of surface and plasma bullets properties. The consortium is composed of biologists, plasma physicists, high voltage power supply specialists, and a plasma decontamination firm.

The past decade has witnessed a tremendous interest in the concept of sparse representations in signal and image processing. One of the main reasons explaining this enthusiasm stands in the discovery of compressive sensing, a new sampling paradigm defying the theoretical limits established sixty years before by Shannon. Compressive sensing led many researchers to focus on inverse problems involving fairly-well conditioned dictionaries as those arising from random, independent measurements. Yet in many applications, the dictionaries relating the observations to the sought sparse signal are deterministic and ill-conditioned. In these scenarios, many classical algorithms and theoretical analyses are likely to fail. The BECOSE project aims to extend the scope of sparsity techniques much beyond the academic setting of random and well-conditioned dictionaries. 1. Conception of new algorithms Inverse problems exploiting the sparse nature of the solution rely on the minimization of the counting function, referred to as the L0-"norm". This problem being intractable in most practical settings, many suboptimal resolutions have been suggested. The conception of algorithms dedicated to ill-conditioned inverse problems will revolve around three lines of thought. First, we will step back from the popular L1-convexification of the sparse representation problem and consider more involved nonconvex formulations. Recent works indeed demonstrate their relevance for difficult inverse problems. However, designing effective and computationally efficient algorithms remains a challenge for problems of large dimension. Second, we will study the benefit of working with continuous dictionaries in contrast with the classical discrete approach. Third, we will investigate the exploitation of additional sources of structural information (on top of sparsity) such as non-negativity constraints. 2. Theoretical analysis of algorithms The theoretical analysis aims at characterizing the performance of heuristic sparse algorithms. The traditional worst-case exact recovery guarantees are acknowledged to be rather pessimistic because they may not reflect the average behavior of algorithms. It is noticeable, though, that sharp worst-case exact recovery conditions are not even available for a number of popular L0 algorithms. We will focus on stepwise orthogonal greedy search algorithms, which are very well-suited to the ill-conditioned context. We foresee that they will enjoy much weaker recovery guarantees than simpler L0 algorithms. We further propose to elaborate an average analysis of greedy algorithms for deterministic dictionaries, which is a major open issue. To do so, several intermediate steps will be carried out including a guaranteed failure analysis and the derivation of weakened guarantees of success by taking into account other constraints on top of sparsity such as prior knowledge on the signs, coefficient values, and partial support information. 3. From theory to practice The proposed algorithms will be assessed in the context of tomographic Particle Image Velocimetry (PIV), a rapidly growing imaging technique in fluid mechanics that will have strong impact in several industrial sectors including environment, automotive and aeronautical industries. This flow measurement technique aims to determine the 3D displacement of tracer particles that passively follow the flow, based on the acquisition of a limited number of 2D camera images. The resulting inverse problem involves high-dimensional data as a time sequence of highly resolved 3D volumes must be reconstructed. Presently available methods for 3D reconstruction and flow tracking are still restricted to small volumes, which is the main bottleneck together with accuracy and resolution limits. The sparse approach is the key methodological tool to handle problems of larger dimension. The proposed solutions will be validated using both realistic simulators and real experimental data.