The large-scale use of renewable energy, in particular solar energy, requires the development of energy storage technologies to compensate for the intermittent availability of solar radiation. Among all storage methods, the thermochemical storage of energy appears to be particularly interesting due to its high storage density and its potential ability to avoid energy losses. A charge reaction stores the solar energy whereas the reverse discharge reaction gives back this energy whenever it is needed the most. Among the different reactors allowing one to do this for Concentrated Solar Power (CSP), Solar Rotary Kilns (SRK) appear to be particularly promising as they can potentially allow the continuous and uninterrupted storage of energy unlike batch and semi-batch reactors. There are, however, two main aspects that need to be further explored. On the one hand, the modelling of solar rotary kilns is still at its infancy and a realistic understanding of the interaction between granular flow, heat transfer and chemical kinetics has yet to be reached. On the other hand, the construction of a directly irradiated SRK with the possibility of adjusting the solid flow rate to the fluctuating radiance of the sun would be highly beneficial. The purpose of the project MULTITHERMO will be to develop a realistic and physically and chemically sound multiphysics model describing all aspects of heat storage in a rotary kiln and to validate it based on the data from a new prototype of SRK and from an already existing electrical rotary kiln and an already existing rotary drum. It will be mainly based on the reduction of BaO2(s) as a promising heat-storing reaction. This reaction will be also studied during the projetc in order to master its chemical kinetics.

A WDM flexible grid for Spectrally Flexible Optical Networks (SFONs) was standardized in 2012. FLEXOPTIM aims to develop efficient Routing and Spectrum Assignment (RSA) algorithms able to optimize in a tractable way the WDM optical spectrum use in SFONs, with arbitrary topologies and large sizes; e.g. several tens of nodes, and several hundreds of connections. RSA addresses two use cases: - A full set of connection requests is known in advance. 0ff-line calculation takes into account the entire set. Connections are then configured from scratch. Such network reset can be carried out periodically to make the best use of transmission resources. - Connection requests arrive on the fly. Calculations are made on-line taking into account existing traffic and connections are configured immediately after. This corresponds to the incremental “local” optimization of the network physical resources. Algorithms have to be compatible with SDN paradigm. Hence, FLEXOPTIM will regularly interact with Orange Labs teams involved in SDN forums and standardization bodies. The key challenge is algorithm scalability. The RSA problem is NP-Hard, much harder than the Routing and Wavelength Assignment problem for fix grid WDM networks. FLEXOPTIM shall explore new mathematical approaches reducing the number of variables to overcome the drawbacks of current methods. FLEXOPTIM involves two teams, from the LIMOS laboratory at University Clermont-Auvergne (including the project coordinator) and IMT Atlantique (Lab-STICC and IRISA), with an in-depth expertise in respectively applied mathematics to optimization and optical network architecture. The project includes a management work package and two technical ones. WP0 is in charge of reporting to ANR and project coordination. It also ensures exploiting and disseminating the results as well as maintaining frequent contacts with external industrial partners and optimization experts thanks to an advisory board. WP1 shall develop new optimization tools for RSA problem. WP2 shall evaluate the developed algorithms and apply them to use cases defined in close relationship with the advisory board. WP2 shall first define Key Performance Indicators. In the first year, WP1 shall introduce new formulations for the off-line RSA problem and deliver a basic version to WP2. During a six month evaluation process, WP1 shall enhance its formulations and use WP2’s feedback to reach a stable version to be evaluated on a dedicated Orange Labs platform. By the beginning of the third year, WP1 shall provide final specifications of the off-line algorithms and WP2 assess their performance. WP1 shall also consider novel heuristics incorporating the previous solution structure analysis and insights from WP2 for the on-line problem. First versions of on-line algorithms will be evaluated by WP2. Stable versions, adapting SDN concepts to SFON functional architecture, will be delivered for evaluation on the Orange Labs testbed and final versions will be fully specified and evaluated at the end of the project. As a PRC project, FLEXOPTIM primarily aims at impacting research and teaching in the areas of expertise of its partners. In particular, its results shall be published in relevant journals and conferences. FLEXOPTIM intends to cross-fertilize both optimization and optical networking fields. In particular, several optimization methods studied in FLEXOPTIM could find other applications, such as dimensioning of other network types or other discrete resource allocation problems. FLEXOPTIM should also have a significant industrial impact. Developed codes and generic data benchmarks for simulations will be made freely available. Contributions to the Open-ROADM Multi-Source Agreement should be a very suitable tool for disseminating the results regarding node control in a SFON. A final workshop will bring together scientists from both academia and industry to present the project achievements and debate on methods and open questions in SFONs.

This project aims to propose a declarative language dedicated to cryptanalytic problems in symmetric key cryptography using constraint programming (CP) to simplify the representation of attacks, to improve existing attacks and to build new cryptographic primitives that withstand these attacks. We also want to compare the different tools that can be used to solve these problems: SAT and MILP where the constraints are homogeneous and CP where the heterogeneous constraints can allow a more complex treatment. One of the challenges of this project will be to define global constraints dedicated to the case of symmetric cryptography. Concerning constraint programming, this project will define new dedicated global constraints, will improve the underlying filtering and solution search algorithms and will propose dedicated explanations generated automatically.

The MOBILES project aims to document, understand and support the spatial and language learning practices of international students.ales hosted in higher education in France. The originality of the project consists in the analysis of the learning process within a long-term and immersion stay, through the angle of the spatial practices using digital tools. The project will (1) analyse the students’ spatial practices, i.e. shed light on the learning opportunities harboured by the context; (2) conceive a mapping of the city as it is practiced, by means of a cartographic interface that allows combining heterogeneous sources of data and exploring them in a quantitative and qualitative manner; (3) examine ways in which recommendation systems based on users’ participation can be set up in order to support the goals of learning.

The project FITS aims at proposing novel mathematical models and solution approaches in order to develop intelligent tools to help optimizing the delivery of services (such as care or maintenance deliveries) to customers located potentially at home. Service providers have human resources (possibly outsourced) with different characteristics. They can have different skills (specialized to versatile), different availabilities and different locations. Customer demands can be erratic, dynamic, stochastic and heterogeneous. The goal of a service provider is to assign customers’ demands to human resources in order to ensure a high quality of service while maintaining good working conditions. For example, in order to satisfy human resources, their activity should be diversified and the driving distance minimized; and in order to satisfy customers, service delivery should be regular and consistent. In order to ensure such an assignment, there exist reservation platforms that aim at putting in touch human resources and customers (servilink, allovoisin, domicalis). That business met recent success stories: Airbnb, Blablacar and Uber. This success shows that an increasing number of customers are web-connected and they require more than responsive services as they expect that some future needs have to be anticipated. The efficiency of these systems strongly depends on the quality of data, and supply and demand matching. Capturing and storing data becomes easier and easier, but extracting knowledge from these data and using these data efficiently remains a difficult task. When both demand and offer reach high volumes, some basic rules may satisfy users. But several cases can make these systems less efficient. Some of these cases are: (1) Low demand density, (2) Low supply offer, (3) Strong constraints, and (4) Strong demand variability. Thus, if smart systems are not available to deal with these problems, some low density population areas and some delicate or strictly constrained activities cannot take advantage of service platforms. So several regions and activities may wonder whether they can or cannot apply these services. In order to ensure a good quality of service while maintaining good working conditions and a profitable system, such platforms need to be optimized. The project FITS is designed to tackle the scientific challenges raised by the optimization of these service provider platforms that need intelligent tools for responsive large scale transportation services. FITS is designed to address those issues by taking profits from available data (real-time information and statistics on large data). FITS has to perform a smart assignment between users in order to find the best balance between satisfying customers and covering constraining or less profitable requests with fair dispatching rules among workers in terms of difficulty and profit. FITS is conducted by a consortium of three complementary teams (CMP, CIS and UCA) in computer sciences, operations research, management science and healthcare engineering. Developed algorithms will be tested on real data extracted from the open living lab #futuremedicine MedTechDesign. All developed algorithms will be prototyped in this living lab.