SOURCE-LINKED INTELLIGENCE

Digital Design strategies to certify and mAnufacture Robust cOmposite sTructures

CORDIS · observation · Publication date unknown

nges 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

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recordType

award

status

SIGNED

region

EU

value

4702365

unit

EUR