New certified designs for structures are critical for the new upcoming changes in conception of aircraft architectures. A variety of breakthrough designs and new strategies for a better use of material and integration of functions in aircrafts are required. They range from regional electrical mobility solutions to increased aspect ratio wings that will bring higher flexibility in structures. Digital conception and simulation need to play an ever-bigger role to reach a certified design that includes production scenarii before full manufacturing. High-end simulation is a spearhead research activity present in many fundamental and applied research activities. The level of complexity of phenomena being solved through dedicated modeling techniques is constantly evolving and faces many challenges in validation and exploitation. For better use of these methods, the consortium will pursue the objective of scalability and representativity of results in the design process through appropriate Machine Learning surrogates, benefiting from High Performance Computing. The DIDEAROT project aims at bringing a digital centrepiece approach that could integrate the move to more digital designs in the aircraft industry. It will cover the robust optimization of composite structures focused on digital predictions of two key aspects in its lifetime: Manufacturing: predicting distortions, stress build-up and assembly challenges for ever-more integrated industrial scale composite parts Dynamic loads and impact: predicting damage and effects from loads occurring at high speed or repeated loads over time that can lead to critical certification conditions. While both aspects have been partially addressed by the research community, the challenge we tackle here is to integrate them together in the testing pyramid (up to an industrial scale) for certification of structures and increase the reliance on digital technologies (data or simulation driven) to ensure optimized design approaches.

The mission of COMPOSELECTOR is to develop a Business Decision Support System (BDSS), which integrates materials modelling, business tools and databases into a single workflow to support the complex decision process involved in the selection and design of polymer-matrix composites (PMCs). This will be achieved by means of an open integration platform which enables interoperability and information management of materials models and data and connects a rich materials modelling layer with industry standard business process models. In order to satisfy the need for effectively designing and producing increasingly sophisticated materials, components and systems with advanced performance on a competitive time scale there is a particular need in industry for chemistry/physics-based materials models and modelling workflows which capture the performance of materials, accounting for material internal microstructure and effects of processing, provide accuracy/validation of predicted data, and relevant management of uncertainty and assemble knowledge ready for decision makers to act upon. COMPOSELECTOR will address these needs by integration of (discrete and continuum) materials models and process models as well as structured and unstructured data into a standards-based, open integration framework, implementing uncertainty management and multi-criteria optimisation in order to provide actionable choices, and building tailored knowledge apps to support decision makers. The human interface of COMPOSELECTOR will be supported by Visual Analytics capable of integrating qualitative, quantitative and cognitive aspects for a user-friendly management of the vast quantity of available data. The COMPOSELECTOR BDSS will be applied to and validated by end users targeting accurate, reliable, efficient and cost effective decision-making and management of polymer matrix composite (PMC) materials in the transport and aerospace value chains.