The mechanical behavior of woven fibrous media is of high interest nowadays, due to their increasing use in various contexts, according to their very interersting properties: low weight, important gain of machining time for large scale productions, mighty saving of labour time, materials and energy, better distribution of efforts, important mobility of the dry fabric, increased mechanical performances, good chemical stability, resistance to corrosion. Those advantages justify the use of textiles for products with a high added value, especially in aeronautics, an area whitnessing a strong increase of the developement of composites with a thick reinforcement with a 3D architecture. SNECMA has developed a technology of gas turbine engine fan blade made of a composite material with a 3D woven reinforcement, which constitutes by itself a technological breakthrough. The orientation of fibers in the three directions of space gives this material a very good resistance to impact in comparison to solutions based on classical composites. The methodology implemented in this project aims at improving the quantitative understanding of the deformation mechanisms of 3D interlocks, in order to increase their service performances in a context of lightening of strucutres. This constitutes a major scientific and technological lock considering economic issues. Despite many attempts to model the effective behavior, there is up to now no satisfactory approach able to efficiently predict the most important aspects of the deformation of 3D wovens, and to predict the macroscopic mechanical response of the structure in a dry or preimpregnated state, from the knowledge of the behavior of fibres or complex yarns at the smaller scales. Thanks to the development of multiscale simulation techniques and imaging techniques at very fine scales such as microtomography X, it becomes possible to investigate the mechanical behavior of fibrous media at the level of fiber interactions, which opens new roads for the exploration and understanding of phenomena occurring at those scales, and especially to elaborate and identify models at intermediate scales, which is essential to predict the macroscopic behavior. The principal objecitve of the project is to build multiscale models and constitutive laws of 3D weavings, in order to solve the problems of lightening and increase of performances, leading to the search of products with low weight and optimal performances. Those models shall incorporate the fine informations related to the elementary constituents (fibres and yarns) and their muutal interactions (contact, friction), which shall be characterized by appropriate techniques. The experimental and numerical analyses shall provide criteria for the choice of the 3D architecture of weavings according to performance indicators accounting for phenomena charactérizd and modeled at the smallest scales. The identification of the principal representative phenomena, the search of relevant variables to quantify theml, are central and open questions at the interface between scales. The elaboration of predictive models will allow to evaluate the impact of the parameters of the elaborated products on their mechanical functionalities, and to optimize the criteria for the choice of 3D weavings. The principal objective at the ultimate scale is the optimization of the shape forming of 3D textiles thanks to experimental, theoretical and numerical methods.

AIQuAM3D is a French-German research project that will open up application fields of artificial intelligence (AI) and improve the use of AI in cutting-edge technologies. The SMEs Xploraytion (DE) and Novitom (FR), together with the research organizations SOLEIL (FR) and Fraunhofer IPK (DE), constitute the project consortium and will work together on transferring AI research into the application fields of additive manufacturing (AM) and synchrotron micro-computed tomography (SR-µCT). With regard to AM technology, an embedded AI model for real-time bulk defects prediction in Laser-Powder Bed Fusion (L-PBF) will be developed, enhancing the quality assurance of AM process, leading to the wide application and industrialization of the AM technology. The approach goes from data fusion of in-situ process signals (level 0 to 3), through labelling and training of in-situ monitoring models with quality-optimized µCT data sets, up to defect prediction model development, validation and implementation as embedded solution into a L-PBF system. In regard to 3D material characterization, AIQuaAM3D will develop AI tools to integrate with a tomography data analysis pipeline. The integration of the AI analysis with the SR-µCT acquisition will enable real time data analysis, even for fast acquistions, providing feedback on the quality of results being collected. This closer integration means that the system can warn the user in the event of poor-quality data and/or image artefacts. The total project duration is 3 years, the subject of the project is aligned with the priorities of the funding program set by the partner countries.

For more than 25 years, synchrotron X-ray microtomography, especially in phase contrast or diffraction mode, has enabled the 3D characterization at the micro-meter scale of crystalline and amorphous media, both heterogeneous and architectured. By the earlier 2000s, laboratory X-ray micrography, which is easier of access, emerged. However, this technology currently does not offer as many possibilities as what is available at synchrotrons. This project aims to develop advanced laboratory X-ray tomography techniques taking into account phase contrast and diffraction mechanisms and using a new generation of detectors, called “color detector” to provide new information for the material scientist. Color detectors are able to select the different energies of the X-ray beam produced by laboratory sources. They can be coupled with interferometers, to obtain simultaneously dark field images as well as phase images to be acquired in order to increase the contrast in measurements performed with laboratory X-ray scanning. Such detectors will also be used to analyze diffraction patterns to get 3D maps of the crystalline orientation.