PLM software editors propose to the manufacturing industries (automotive, aerospace…) a set of tools to simulate the product and the manufacturing processes thanks to numerical models. One of these tools is the simulation of the part assembly or disassembly to validate the final assembly process or the maintainability of a complex product like an automobile or an aircraft. The commercial product, KineoWorks, developed by Kineo C.A.M. is able to automatically generate a collision free motion of a rigid part simulating its assembly (or disassembly) inside the digital mockup. This product is integrated in widely used CAD software like CATIA, DELMIA from Dassault Systèmes and NX, Vizmockup or Process Simulate from Siemens PLM Software. However, the algorithm cannot simulate the flexibility of the components in the digital mockup such as cables. They need to be removed from the study or considered as rigid. Thus, the simulation is not complete due to this lack of realism. Such a flexible component simulation nevertheless begins to be available on the market. In particular, CEA-LIST develops the XDE physics engine that is able to simulate cable deformation in a digital mockup with real time interaction. The project Flecto proposes to bring these two technologies together: path planning and flexible simulation. The goal is to develop an easy-to-use software component that automatically computes collision free extraction path of flexible components in a flexible assembly. We will focus our objectives on the end-user requirements so that the customer-installed base will provide real case scenarios. Moreover, we will integrate the results into an addon of CATIA to facilitate the testing and the validation by the industrial end-users. The project objectives perfectly fit with several thematic axes of the “Modèles Numériques” ANR program. The primary axis is axis 2, Design and Optimization because the result will be integrated in CAD/CAM tools to help the industries to check the assembly process and to optimize the product maintainability. The axis 1, Complex Systems Simulation and Modeling is the secondary axis because of the flexible models complexity. The project also matches with the axes 4 and 5. The consortium is made of the Kineo C.A.M. Company and the laboratories CEA-LIST and LAAS-CNRS. Kineo C.A.M. is an Independent Software Vendor (ISV) SME recognized as the international leader in industrial software solution for path planning and collision detection with more than 150 customers in 20 countries. The company will coordinate the project; it will gather the end-user requirements and it will exploit the final product. CEA-LIST is one of the best laboratories in interactive simulation and virtual reality. It will bring to the project its knowledge in flexible simulation with its XDE physics engine. Finally, the project will benefit from decades of LAAS-CNRS experience in motion planning algorithms. We will gather the end-user requirements and real usecase dataset. From this input, we will adapt the physics engine to match the path planning needs in term of performance and available data. In parallel, we will enhance the path planning algorithm to take into account additional degrees of freedom due to the flexibility of the component. Finally, we will integrate the algorithms into CAD software like CATIA V5 and we will propose to the end-user to test and to validate the solution. Kineo C.A.M. will exploit the result of the project thanks to a planned consortium agreement with integration in its product portfolio. The commercial solution will be proposed to its existing and future customers. The project has thus five main tasks: project management, flexible models, collision detection, path planning and solution deployment. The project is 36 months long. It represents 122 person.months for a total budget of 1310.4 K€ and we apply for a ANR grant of 609.6 K€.

Proteins are essential parts in living organisms. They participate in most of the cellular processes such as gene expression, signal transmission, catalysis of chemical reactions, … Due to their large range of possible functions, the study of proteins interests other fields in addition to biology. Proteins are pharmaceutical targets and drugs, their catalytic properties are widely used in biotechnology, and they are used as components of nano-devises in the rising field of bionanotechnology. Although the properties of natural proteins can be directly exploited, new, designed proteins, with novel functions or improved activities, are of major interest in all these application areas. Protein design may involve the remodeling of a known protein scaffold in order to modify the protein function/activity, or, in the most general case, the complete (de novo) design of new protein structures to fulfill a particular function. The problem is extremely challenging since the number of possible combinations of amino acids to be tested is astronomically large. Experimentally testing all the possible sequences is practically impossible. Therefore, computational protein design methods have been developed for over a decade. In addition to the intrinsic combinatorial complexity of the protein design problem, computational methods have to face the natural flexibility of proteins (i.e. proteins are flexible molecules that fluctuate between nearly isoenergetic states). Indeed, the protein design problem is even more challenging if dynamical aspects (e.g. allosteric shifts, loop motions, ...) are considered in addition to static aspects (e.g. positional arrangement of catalytic residues for enzyme activity). Due to all these difficulties, and despite great advances in recent years, computational protein design remains a largely open problem. In particular, improvements in models and algorithms are essential to better explore the protein sequence combinatorial space while taking into account protein flexibility. Besides, accurate and computationally efficient energy functions, able to better account for interactions with solvent and entropy change, are necessary. The goal of this project is to yield advances in a general methodology for protein design, and to develop suitable computational design tools that will lead the development of new proteins for applications in biotechnology, biomolecular nanotechnology, molecular medicine and synthetic biology. The methodological breakthrough expected from this interdisciplinary project builds on the combination of cutting-edge methods in computational biology with efficient algorithms originating from robotics. Among all the possible applications of the methods developed in this project, special attention will be given to enzyme design for applications in biotechnology such as the production of high-valued molecules, the development of eco-friendly bioprocesses and the valorization of renewable carbon resources. Such applications are of high interest to the pre-industrial demonstrator Toulouse White Biotech (TWB), supporter of our project, and to the Competitive Cluster AgriMip. The achievement of the project relies on the complementary expertise of four partners: LAAS-CNRS for robotics and computer science, BIOS-Polytechnique and LISBP-INSA for computational biology & protein engineering, and Kineo CAM, a company specialized in software development for computer-aided design and manufacturing.

Objectives, originality and novelty of the project In order to reduce the economic, environmental and energy impact of building usage it is necessary to improve the performance of the envelope as well as the HVAC systems so as to exploit local renewable energy. However, the more the design aims for high performance, the more the interactions and coupling effects between the building, its environment and the conditions of use are important. Real consumptions and comfort level depend on the way the building is controlled while it gets more and more difficult to define in an intuitive way an optimal building management strategy. In order to ensure the best thermal comfort to occupants without deteriorating the actual performance of the building, the later should constantly adapt to changing use and environmental conditions based on a prediction of its future state and the forecast of variables like energy price or CO2 emissions associated with energy use, etc. PRECCISION project aims at bringing scientific and technical solutions to improve building energy management systems in order to fulfill these requirements. We will develop new methods and tools to analyze in real-time the building’s energy behavior and to control it, either by acting directly on the systems configuration or by providing the user or the building manager with useful information about the building state. The project PRECCISION project aims at developing software components including modeling tools based on building physics, model reduction techniques, identification and inverse modeling methods and optimization algorithms. Some developments will also concern a software front-end in order to provide useful information to the occupant or building manager, involving them in the control loop. In order to demonstrate the feasibility, the developed software tools and associated hardware will be implemented and tested in real life buildings. Three experimental platforms will be used: an unoccupied house for experimental validation needs (INCAS research platform); an occupied well-instrumented building (the PREDIS/MHI platform); finally, an occupied retrofitted apartment building that will provide useful information about the acceptability of the impact on the inhabitants. Organisation and Consortium The consortium brings together building physics specialists (Armines CEP, I2M TREFLE, CEA INES, IFSTTAR), a company specialized on multiphysics systems modeling (LMS IMAGINE), two teams in the areas of software frameworks for optimization of thermal and electric systems (Grenoble-INP), the VESTA-System startup specialized on software solutions for energy system optimization and the DeltaDore group, service and software supplier for energy management of buildings.