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

Författare

Robert Auenhammer

Chalmers, Industri- och materialvetenskap, Material- och beräkningsmekanik

Lars Mikkelsen

Danmarks Tekniske Universitet (DTU)

Leif Asp

Chalmers, Industri- och materialvetenskap, Material- och beräkningsmekanik

Brina Blinzler

Chalmers, Industri- och materialvetenskap, Material- och beräkningsmekanik

IOP Conference Series: Materials Science and Engineering

17578981 (ISSN) 1757899X (eISSN)

Vol. 942 1 012038

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

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

Europeiska kommissionen (EU) (EC/H2020/765604), 2019-01-01 -- 2021-12-31.

Drivkrafter

Hållbar utveckling

Styrkeområden

Transport

Materialvetenskap

Ämneskategorier

Teknisk mekanik

Datavetenskap (datalogi)

Kompositmaterial och -teknik

Infrastruktur

C3SE (Chalmers Centre for Computational Science and Engineering)

DOI

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

Mer information

Senast uppdaterat

2022-04-05