Designed to achieve reduction in fuel consumption, the Ultra-High Bypass and High Propulsive Efficiency Geared Turbofan engine incorporates evolutions likely to produce high frequency (HF) vibration excitations which propagate through the structure. Numerical simulation is an efficient tool to control vibrations hence supporting the mechanical design. Where Finite Element (FE) based approaches show limitations due to computational hardware performances and HF dispersion management, Statistical Energy Analysis (SEA) stand as proven and effective method for this frequency range to predict the vibrational energy transfers across partitions – subsystems – of a structure. Challenges of SEA modelling consist of the structure partitioning which usually requires expertise and the accuracy loss at lower frequencies where the high stiffness of parts or complexity of junctions counter the method initial assumptions. Those statements depend strongly on the studied structure, therefore the objective of the proposed project is to develop and demonstrate a SEA modelling process to predict the vibration propagated in a typical complex engine frame. In this scope, best modelling practices from detailed numerical analysis are engaged to both support an extensive test campaign preparation including test vehicle design and manufacture, and produce models covering the target frequency range: from 400Hz to 10kHz. A crucial phase consists in the validation and update of these models from tests post-processing techniques and known methods such as Experimental SEA, Decay Rate damping estimation or input conductance as well as innovative inverse approaches relying on optimization loops. From the comprehensive comparison of these different methods with tests results, a best methods and associated modelling practices are delivered to the topic leader. CETIM and ESI join their complementary competences to develop the modelling and experimental know how applied to the HF vibrations assessment.

MeDiTATe aims to develop state-of-the-art image based medical Digital Twins of cardiovascular districts for a patient specific prevention and treatment of aneurysms. The Individual Research Projects of the 14 ESRs are defined across five research tracks: (1) High fidelity CAE multi-physics simulation with RBF mesh morphing (FEM, CFD, FSI, inverse FEM) (2) Real time interaction with the digital twin by Augmented Reality, Haptic Devices and Reduced Order Models (3) HPC tools, including GPUs, and cloud-based paradigms for fast and automated CAE processing of clinical database (4) Big Data management for population of patients imaging data and high fidelity CAE twins (5) Additive Manufacturing of physical mock-up for surgical planning and training to gain a comprehensive Industry 4.0 approach in a clinical scenario (Medicine 4.0) The work of ESRs, each one hired for two 18 months periods (industry + research) and enrolled in PhD programmes, will be driven by the multi disciplinary and multi-sectoral needs of the research consortium (clinical, academic and industrial) which will offer the expertise of Participants to provide scientific support, secondments and training. Recruited researchers will become active players of a strategic sector of the European medical and simulation industry and will face the industrial and research challenges daily faced by clinical experts, engineering analysts and simulation software technology developers. During their postgraduate studies they will be trained by the whole consortium receiving a flexible and competitive skill-set designed to address a career at the cutting edge of technological innovation in healthcare. The main objective of MeDiTATe is the production of high-level scientists with a strong experience of integration across academic, industrial and clinical areas, able to apply their skills to real life scenarios and capable to introduce advanced and innovative digital twin concepts in the clinic and healthcare sectors.

Nowadays, European manufacturing enterprises are facing a number of challenges in a turbulent globalized market facing unprecedented and abrupt changes in market demands, an ever-increasing number of product variants and smaller lot sizes, intensifying the worldwide competition and causing a continuous pressure on production costs, product quality and production efficiency. Therefore, novel product development strategies for ensuring and optimising the manufacturing of new products or variants in low-volume production systems must be implemented. PIONEER aims the development of an open innovation platform and interoperable digital pipeline for addressing a design-by-simulation optimisation framework. For that, PIONEER implements inline feedforward control strategies for enhancing the efficiency of the industrial systems in high-mix/low-volume production schemes, based on the connection between materials modelling and materials characterisation, simulation-based digital twins and data-driven models, updated through distributed production data from embedded IoT edge devices and product quality. PIONEER is built over five pillars for development a common methodology deployed in two demonstrators by involving multidisciplinary optimisation for ensuring certified path planning strategies for the manufacturing of topology optimised structural elements through Wire-Arc Additive Manufacturing (WAAM) in construction –i.e., low-volume production schemes–, as well as for ensuring an efficient design and manufacturing strategy for the manufacturing of Carbon Fibre Sheet Moulding Compound (CF-SMC) components in automotive –i.e., high-mix production schemes–. PIONEER is built on the knowledge and results gained in i) previous H2020 EU projects; ii) associations –i.e. EMMC ASBL, IOF, VMAP Standard Community, IDTA—; and iii) commercial products from project partners.