Fibre orientation distribution function mapping for short fibre polymer composite components from low resolution/large volume X-ray computed tomography
Journal article, 2024

Short glass fibre injection moulded composites, used in interior and exterior automotive parts, are exposed to complex stress states, for example during a crash. As the fibre scale dominates the composite’s material properties, numerical models need to account for the local fibre orientation. In recent years, mould flow simulation results have been exploited to predict the fibre orientations for finite element models, albeit with limited accuracy. Alternatively, X-ray computed tomography can be used to directly image and analyse fibre orientations. Traditionally, achieving the necessary resolution to image individual fibres restricts the imaging to small regions of the component. However, this study takes advantage of recent advancements in imaging and image analysis to overcome this limitation. As a result, it introduces, for the first time, a reliable, fast, and automated fibre orientation mapping for a full component based on image analysis at the individual fibre level; even for cases where the pixel size is significantly larger than the fibre diameter. By scanning at lower resolutions, a drastically larger volume of interest can be achieved. The resulting fibre orientation analysis and mapping algorithm, based on X-ray computed tomography, is well matched to the level of information required for automotive crash modelling with a standard element-size of a few millimetres. The entire process, encompassing image acquisition, image analysis and fibre orientation mapping, can be directly integrated into an industrial full component application in a matter of hours.

CT

Fibre orientation analysis

Fibre orientation mapping

Structure tensor

Author

Robert Auenhammer

Chalmers, Industrial and Materials Science, Material and Computational Mechanics

Technical University of Denmark (DTU)

Anuj Prajapati

University of Manchester

Kaldon Kalasho

Volvo Cars

Lars Mikkelsen

Technical University of Denmark (DTU)

Philip Withers

University of Manchester

Leif Asp

Chalmers, Industrial and Materials Science, Material and Computational Mechanics

Renaud Gutkin

Chalmers, Industrial and Materials Science

Volvo Cars

Composites Part B: Engineering

1359-8368 (ISSN)

Vol. 275 111313

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

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

UTMOST - Modelling of biobased composites in crash applications

VINNOVA (2021-05062), 2022-05-02 -- 2024-12-31.

Areas of Advance

Materials Science

Subject Categories

Computer Vision and Robotics (Autonomous Systems)

Composite Science and Engineering

DOI

10.1016/j.compositesb.2024.111313

More information

Latest update

3/13/2024