REaL-tIme characterization of ANisotropic Carbon-based tEchnological fibres, films and composites

Project Information

RELIANCE

Grant agreement ID: 101073040

DOI

10.3030/101073040

EC signature date 14 July 2022

Start date 1 February 2023

End date 31 January 2027

Funded under

• Marie Skłodowska-Curie Actions (MSCA)

Total cost

No data

EU contribution

€ 2 854 965,60

Coordinated by

DANMARKS TEKNISKE UNIVERSITET
Denmark

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Deliverables

Documents, reports (3)

Methodology for simulations ex-situ based CT measurements

A modelling framework that is complementary to the already envisaged ray-tracing simulation.

SAXS/WAXS measurement of yarn samples

PSI, DTU and Xenocs will measure yarn samples at synchrotron beam lines, and on laboratory SAXS/WAXS equipment. The instrumental parameters will be optimized in order to highlight the differences between the samples. Raw images will be used by DTU for analysis in work package 3.

X-ray imaging measurement of composite samples

Samples from FIB measured on existing tomography equipment.

Other (3)

Advertisement of vacancies
1st Summer School
1st and 2nd workshops

Demonstrators, pilots, prototypes (6)

Methodology for quantifying micro- and nano-structure of a material from X-ray scattering
Demonstrator of real-time reconstruction algorithm for X-ray refocusing from limited-angle data (…)

Demonstrator of real-time reconstruction algorithm for X-ray refocusing from limited-angle data with open-source software

Demonstrator of real-time reconstruction algorithm for sparse X-ray scattering data (…)

Demonstrator of real-time reconstruction algorithm for sparse X-ray scattering data with open-source software

A demonstrator case establishing a link (…) with material micro- and nano-structure measured (…)

A demonstrator case establishing a link between mock product line parameters and material micro- and nano-structure measured by the methodology developed in D3.1.

Build a (…) mechanistic digital twin of (…) fibre yarns

Build a physics/mechanistic digital twin of the carbon-based fibre yarns.

Virtual geometrical model (digital twin) of a composite

Virtual geometrical models (digital twins) of various fiber composites

Publications

Conference proceedings (1)

AUTOMATED GENERATION OF LABELED SYNTHETIC TRAINING DATA FOR MACHINE LEARNING BASED SEGMENTATION OF 3D-WOVEN COMPOSITES

Author(s): Johan Friemann, Lars P. Mikkelsen, Carolyn Oddy, Martin Fagerström
Published in: Procedings of Proceedings of the 21st European Conference on Composite Materials, 2024
Publisher: European Society for Composite Materials
DOI: 10.60691/YJ56-NP80

Other (1)

Defect detection in carbon fiber-reinforced composites using directional dark-field imaging and tomography

Author(s): Slyamov, Azat; van Roosmalen, Adriaan; Pedersen, Mads A.; Nielsen, Kenneth K.; Ferguson, Ole V.; Mikkelsen, Lars P.; Lauridsen, Erik
Published in: Slyamov , A , van Roosmalen , A , Pedersen , M A , Nielsen , K K , Ferguson , O V , Mikkelsen , L P & Lauridsen , E 2023 , Defect detection in carbon fiber-reinforced composites using directional dark-field imaging and tomography . in 43rd Risoe International Symposium on Materials Science . vol. 1293 , 012016 , IOP Publishing , IOP Conference Series: Materials Science and Engineering , 43rd Risø International Symposium on Materials Science , Risø, Roskilde , Denmark , 04/09/2023 . https://doi.org/10.1088/1757-899X/1293/1/012016, 2023