X-ray tomography based numerical analysis of stress concentrations in non-crimp fabric reinforced composites - assessment of segmentation methods
Paper in proceeding, 2020

In this study two automated segmentation methodologies of an X-ray computer tomography based numerical analysis are compared. These are then assessed based on their influence on the stress distribution results of finite element models of glass fibre reinforced composites made out of non-crimp fabrics. Non-crimp fabrics reinforced composites are commonly used for wind turbine blades due to their high stiffness to weight ratio for the dominating bending load. Finite element modelling based on X-ray computer tomography allows the reduction of the cost and can accelerate the development process of the key material parameters of wind turbine blades. Recent research progress in the last years has laid the basis for such a procedure. Those processes must be easy applicable, fast and accurate. The main challenge in current methodologies is the segmentation part. The segmentation methods applied for this study have overcome this issue by being automated. This allows for a comparatively fast transfer from X-ray computer tomographic data to finite element results.

Non-crimp fabric composites

X-ray computer tomography

Finite element modelling

Segmentation

Author

Robert Auenhammer

Chalmers, Industrial and Materials Science, Material and Computational Mechanics

Lars Mikkelsen

Technical University of Denmark (DTU)

Leif Asp

Chalmers, Industrial and Materials Science, Material and Computational Mechanics

Brina Blinzler

Chalmers, Industrial and Materials Science, Material and Computational Mechanics

Published in

IOP Conference Series: Materials Science and Engineering

17578981 (ISSN) 1757899X (eISSN)

Vol. 942Issue 1 art. no 012038

Conference

41st Risø International Symposium on Materials Science
Roskilde, Denmark,

Research Project(s)

MUltiscale, Multimodal and Multidimensional imaging for EngineeRING (MUMMERING).

European Commission (EC) (EC/H2020/765604), 2019-01-01 -- 2021-12-31.

Categorizing

Driving Forces

Sustainable development

Areas of Advance

Transport

Materials Science

Subject Categories

Applied Mechanics

Computer Science

Composite Science and Engineering

Infrastructure

C3SE (Chalmers Centre for Computational Science and Engineering)

Identifiers

DOI

10.1088/1757-899X/942/1/012038

More information

Latest update

4/5/2022 6