Digital Design strategies to certify and mAnufacture Robust cOmposite sTructures 

Informazioni relative al progetto

DIDEAROT

ID dell’accordo di sovvenzione: 101056682

DOI

10.3030/101056682

Data della firma CE 10 Maggio 2022

Data di avvio 1 Settembre 2022

Data di completamento 31 Ottobre 2026

Finanziato da

• Climate, Energy and Mobility

Costo totale

€ 4 702 366,25

Contributo UE

€ 4 702 365,00

Coordinato da

CENTRE DE RECHERCHE EN AERONAUTIQUE ASBL - CENAERO
Belgium

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

Documents, reports (7)

Strategies for combining physics-based models and data-driven models

Analysis on how the proposed digital twin concept, further developed in WPs3 & 4, could be employed to optimize other lifecycle stages, and specifically MRO

Project Management Roadmap and procedures

Roadmap on the activities of the project and the different interactions with the WP at play. Definition of roles in the consortium for interactions between WP, with the Advisory board

Implemented optimized micro-mechanics and laminate models

Report on model to generate a mesoscopic homogenized response implemented and optimized for high-performance computing by BSC,

Data Requirements Specification Report

Requirements for data (type, sources, amount, standardization...) along the whole lifecycle including design, manufacturing, validation and testing to be included in the different simulations and modelling tasks

Data Management Plan

Data management plan for all the data generated through WP2 to WP5 in the project

Initial Dissemination and Exploitation Plan

Dissemination and exploitation plan discussed by the partners at kick-off with quantification of the impact in terms of quantity of activities and number of researchers, industrial & academic institutions contacted / impacted

Methodologies input data quality analysis

Report on the methodologies created that allow the quality of the input data to be analyzed so that it is possible to know a priori if suitable conditions to proceed with the analysis are fulfilled

Websites, patent fillings, videos etc. (2)

Organization of Workshop 1 (research community)

Organization of a dedicated workshop oriented towards the research community to communicate breakthroughs and results achieved throughout the project as well as perspectives for collaboration

Public website and social media account

Website accessible to the public and mentioned on linked-in account, beneficiary internet sites and communicated to the EU for general public information dissemination

Data sets, microdata, etc (2)

Synthetic dataset of meso-scale response from ULiège

Particularization and training of the ML based (different scales) surrogatemodels developed in Task 2.3 to the (different scales) damage models developed in Task 4.1. Developments made by ULiège

Synthetic dataset of meso-scale response from INEGI

Particularization and training of the ML based (different scales) surrogatemodels developed in Task 2.3 to the (different scales) damage models developed in Task 4.1. Developments made by INEGI

Other (2)

Surrogate model of the meso-scale response

ML-based surrogate of the meso-scale response accounting for loading history and damaging proces

Surrogate model of the laminate-scale response

ML-based surrogate of the failure envelope at the laminate leve

Pubblicazioni

Peer reviewed articles (6)

Pressure-dependent strain gradient plasticity for micro-mechanical analyses of fibre-reinforced polymers

Autori: Igor A. Rodrigues Lopes, A. Francisca Carvalho Alves, Nathan Klavzer, Thomas Pardoen, Pedro P. Camanho
Pubblicato in: Composite Structures, Numero 381, 2026, ISSN 0263-8223
Editore: Elsevier BV
DOI: 10.1016/J.COMPSTRUCT.2025.119965

A mold compensation method using spectral shape representation

Autori: S. Zein, A. Parmentier, D. Dumas
Pubblicato in: Composite Structures, Numero 370, 2025, ISSN 0263-8223
Editore: Elsevier BV
DOI: 10.1016/J.COMPSTRUCT.2025.119325

Stochastic deep material networks as efficient surrogates for stochastic homogenisation of non-linear heterogeneous materials

Autori: Ling Wu, Ludovic Noels
Pubblicato in: Computer Methods in Applied Mechanics and Engineering, Numero 441, 2025, ISSN 0045-7825
Editore: Elsevier BV
DOI: 10.2139/SSRN.5137186

Discrete non-local interactions formulation of deep material networks for damage-enhanced constitutive material models

Autori: Ling Wu, Ludovic Noels
Pubblicato in: Computer Methods in Applied Mechanics and Engineering, Numero 463, 2027, ISSN 0045-7825
Editore: Elsevier BV
DOI: 10.2139/SSRN.6539687

Unveiling interrelations among material properties of polymer composite laminates

Autori: Erdem Dinler, Igor A. Rodrigues Lopes, Carolina Furtado, Pedro P. Camanho
Pubblicato in: Journal of Composite Materials, 2025, ISSN 0021-9983
Editore: SAGE Publications
DOI: 10.1177/00219983251361205

Computer Methods in Applied Mechanics and Engineering

Autori: Ling Wu, Ludovic Noels
Pubblicato in: Computer Methods in Applied Mechanics and Engineering, Numero 424, 2024, ISSN 0045-7825
Editore: Elsevier B.V.
DOI: 10.2139/ssrn.4659520

Conference proceedings (1)

A High-Fidelity HPC Workflow for Predicting Process-Induced Distortions in Composites Using Surrogate Models

Autori: M. Teixidor-Vilarrasa, A. Quintanas-Corominas, A. Ortega, I. Zárate, E. Marquinez, I. Otero and G. Guillamet
Pubblicato in: Materiales Compuestos
Editore: scipedia