This proposal is concerned with the development of novel methodologies (including identification and validation strategies), stochastic representations and numerical methods in stochastic micromechanical modeling of nonlinear microstructures and imperfect interfaces. For the sake of feasibility, the applications will specifically focus on the modeling of hyperelastic microstructures and materials exhibiting surface effects and containing nano-inhomogeneities (such as nanoreinforcements and nanopores). For the case of nonlinear microstructures, the project aims at developing relevant probabilistic models for quantities of interests at both the microscale and mesoscale. The consideration of the latter turns out to be especially suitable for random nonlinear microstructures (such as living tissues) for which the scale separation, which is usually assumed in nonlinear homogenization, cannot be stated. Random variable and random field models for strain-energy functions will be constructed by invoking the maximum entropy principle and propagated through stochastic nonlinear homogenization techniques. A complete methodology for identifying the proposed representations will be further introduced and validated on a simulated database. Concerning the imperfect interface modeling, one may note that surface effects are usually taken into account by retaining an interface model (such as the widely used membrane-type model) involving several assumptions such as those related to the mechanical description of the membrane. Such arbitrary choices certainly generate model uncertainties which may be critical while propagated to coarsest scales and which may therefore penalize the predictive capabilities of the associated multiscale approaches. In this project, we propose to tackle the issue of model uncertainties in multiscale analysis of random microstructures with nano-heterogeneities by constructing nonparametric probabilistic representations for the homogenized properties. A complementary aspect is the construction of robust random generators, able to simulate random variables taking their values in given subspaces defined by inequality constraints and non-Gaussian random fields. Whereas such random fields can typically be generated making use of point-wise polynomial chaos expansions, the preservation of the statistical dependence is hardly achievable with the currently available techniques. In this proposal, we will subsequently address the construction of new random generators relying on the definition of families of Itô stochastic differential equations. Such generators are intended to depend on a limited number of parameters (independent of the probabilistic dimension), for which tuning guidelines will be provided. The proposed models will clearly go a step beyond what is currently done in deterministic mechanics for such materials and the expected results are in the forefront of the ongoing developments within the scopes of uncertainty quantification and material science. In addition, it worth pointing out that such theoretical derivations are absolutely required in order to support the current new developments of 3D-fields measurements and image processing at the microscale of complex materials.

The prediction of damage caused by blast waves, generated by large scale explosions or industrial hazards (accidents in industrial systems or storage units) is an important technological and research problem that needs further understanding from disaster prevention point of view. The ERANE project has two main important goals: (1) to understand the complex physical phenomena induced by blast and shock waves that pass through complex media (buildings, industrial plants, topographic reliefs, slopes, river valley, etc.) and (2) to help designing new devices for protection against shock and blast loading in an urban agglomeration.

At the heart of bioprocesses the activity and the physiological state of microorganisms are variables still difficult to assess. Most of the information is obtained from delayed off-line measurements and remains insufficient for the development of real time control strategies to optimize the potential of micro-organisms and design high performance processes. On-line quantification of the physiological state of cells is paramount for the understanding and improvement of cell metabolism and thus to control pathways of interest. The main objective of SPECTRE is to develop an on-line system able to monitor the physiological state of microorganisms during fermentation or cell cultures. SPECTRE is partly in continuity with the work developped during the previous ANR FASST program (Programme ANR-06-BIOE-003-01-FASST : Fermentation Alcoolique d'hydrolysats lingo-cellulosiques et obtention de Souches adaptées aux Stress Technologiques). During FASST, advanced methods for the determination of yeast strain viability state were developed. In association with off-line data, on-line dielectric spectroscopy was able to track variations of cell cytoplasm conductivity and microscopy image analysis showed that cell size distribution and cell optical properties were strongly correlated with yeast cell viability. The results of the program have been positively evaluated by the ANR and ADEME expert boards. Dielectric spectroscopy (DS) has been operational for the last ten years. This technique is now routinely used in a number of cell culture and fermentation processes for the determination of biomass concentration. However, it can also give access to informations dependent on the biomass state, but has to be completed by additional techniques to access the value of biologically significant variables. The determination of total cell volume, viability, and cell size are required to calculate the membrane capacitance Cm, representative of the cell enveloppe state, and the cytoplasmic conductivity si, a marker of water and ion exchanges between cells and their environment. Off-line measurements, on samples taken during fermentation or cell cultures, give a differed access to the information provided by the DS and are not suitable for online control. The proposed SPECTRE project is based primarily on : - the study of a coupling of two innovative technologies - spatially resolved optical spectroscopy (SRS) and dielectric spectroscopy (DS) - for the online determination of cell physiological marker variables (size, membrane capacitance, intracellular conductivity...). - the implementation of associated measurement (quantitative microscopy, flow cytometry, optical density, fluorescence, ...) which will allow - the validation of the information collected by DS and SRS, and - the selection of the most relevant additional physical variables (and their associated measurement techniques) eventually able to further improve the robustness of the physiological state evaluation of the cultivated populations. The project will lead to the development of generic tools allowing the real-time control of the physiological state of microbial populations. SPECTRE connects six academic teams expert in Bioprocess Engineering and an SME, leader in the SRS domain and in the associated data analysis techniques. Each team will use cell models chosen both for their established academic and industrial interest.

The market introduction of high temperature wide bandgap power semiconductor devices with junction temperature exceeding 200°C significantly accelerates the trend towards high power density and severe ambient temperature electronics applications. Such evolution may have a great impact in aeronautics applications, especially with the development of More Electric Aircraft (MEA), since it can allow to reduce the mass and volume of power electronics systems. As a consequence, the aircraft operating cost can decrease. However, for electronics used under such harsh conditions, the package reliability and the heat evacuation are very critical issues. The goal of this project is to design and fabricate high performance double sided cooled power electronics modules with optimized thermomechanical properties. The assembly is based on copper joints and a copper heat sink and integrates several technological breakthroughs. Three main technological bricks will be deeply addressed in order to reach the target: 1) Synthesis of nanoporous copper films, either freestanding or directly deposited on metallized substrates with controlled microstructure: In order to limit the risks, three independent strategies will be investigated during the project: the synthesis of nanoporous copper free standing films using melt-spinning and chemical dealloying techniques, the direct on-substrate electroforming of copper-alloy followed by anodic dealloying, and the direct growth of nanoporous structures without any additional treatment by tuning electrolyte formulation and plating parameters. 2) Thermocompression of the nanoporous copper films for die attach: Conventional heating will be achieved at low pressure and in inert/reductive atmosphere. An alternative method based on laser induced fast heating will also be evaluated to thermocompress the nanoporous copper in air. Both solutions allow to limit the oxidation copper issues. The underlying physical mechanisms taking place during the thermocompression of the various morphologies and microstructures of nanoporous copper films will be in-depth investigated. The joint stability under electro-thermo-mechanical aging conditions will be evaluated. 3) Deposition of thick copper layers for substrate/heatsink assembly using electroforming process: A thick dense metal layer will be deposited on a designed sacrificial polymer preform allowing to create a wide range of complex shapes directly on the metallized substrate with low residual stresses. This technology combined to virtual prototyping will allow us to fabricate high performance heat sink patterns (liquid forced convection without phase change) in terms of high local heat transfer coefficient and low pressure drop. The thermal-hydraulic performances of the heat sinks will be analyzed with an experimental setup. The robustness of the assembly (substrate/heat-sink) under repetitive temperature variations will be also evaluated. Silicon Carbide (SiC) devices based power modules (inverter phase leg) using the aforementioned technological bricks will be realized and evaluated in the project. Electrical, thermal and robustness tests are planned to estimate the module performances. The COPPERPACK project will contribute to validate and push our concept from Technology Readiness Level (TRL) 2 up to a TRL 3-4 with a functional technological demonstrator.

Nitrogen protoxide (N2O) is a powerful greenhouse gas (GHG), with an impact 300 times higher than carbon dioxide, contributing significantly to global warming. Microbial processes (nitrification or denitrification) in soils or water contribute significantly to the production of N2O. To date, the contribution of wastewater management is still controversial as N2O emissions were poorly measured in wastewater treatment plants. Recent campaigns demonstrated however that the values assumed by the IPPC are much lower than reality. Moreover intensification of nitrogen removal in wastewater treatment and innovation for minimizing energy consumption can potentially increase the N2O emissions if nitrification and denitrification are insufficiently controlled with appropriate tools. This project aims to quantify, model and reduce N2O emissions from wastewater treatment facilities. The ambition of the project is to evaluate solutions in intensive processes receiving domestic wastewater which are used for nutrient removal. The project is divided in different tasks: (1) monitoring of full scale systems during long term campaigns, (2) tracking the main microbial pathways by innovative techniques (isotopes signature and NO:N2O ratio), (3) validation of a multiple pathway model for simulation and evaluation of mitigation strategies, (4) demonstration of innovative sensors and control tools for energy reduction and N2O mitigation. N2OTRACK will provide representative and objective information on direct greenhouse gas emissions from depollution systems. The contribution of these systems to the national anthropogenic N2O emissions will be estimated. Special effort will be deployed on biofilters at full scale, systems poorly characterized so far. The aim is also to provide an N2O modelling framework validated by lab-scale data with isotopic signature measurements and calibrated by full scale campaigns. Finally innovative control tools based on well-known and new sensors will be developed for both activated sludge processes and biofilters. The project involves six partners: three academic laboratories (LISBP-INSA, IEES-UPMC, RBPE-ECOBIO), one applied research institute (IRSTEA), a large WWTP facility (SIAAP-Paris) and a private company SME (BIOTRADE).