X-ray scattering tensor tomography based finite element modelling of heterogeneous materials
Journal article, 2024

Among micro-scale imaging technologies of materials, X-ray micro-computed tomography has evolved as most popular choice, even though it is restricted to limited field-of-views and long acquisition times. With recent progress in small-angle X-ray scattering these downsides of conventional absorption-based computed tomography have been overcome, allowing complete analysis of the micro-architecture for samples in the dimension of centimetres in a matter of minutes. These advances have been triggered through improved X-ray optical elements and acquisition methods. However, it has not yet been shown how to effectively transfer this small-angle X-ray scattering data into a numerical model capable of accurately predicting the actual material properties. Here, a method is presented to numerically predict mechanical properties of a carbon fibre-reinforced polymer based on imaging data with a voxel-size of 100 μm corresponding to approximately fifteen times the fibre diameter. This extremely low resolution requires a completely new way of constructing the material’s constitutive law based on the fibre orientation, the X-ray scattering anisotropy, and the X-ray scattering intensity. The proposed method combining the advances in X-ray imaging and the presented material model opens for an accurate tensile modulus prediction for volumes of interest between three to six orders of magnitude larger than those conventional carbon fibre orientation image-based models can cover.

Author

Robert Auenhammer

Chalmers, Industrial and Materials Science, Material and Computational Mechanics

Jisoo Kim

Paul Scherrer Institut

Carolyn Oddy

Chalmers, Industrial and Materials Science, Material and Computational Mechanics

Lars Mikkelsen

Technical University of Denmark (DTU)

Federica Marone

Paul Scherrer Institut

M. Stampanoni

Swiss Federal Institute of Technology in Zürich (ETH)

Leif Asp

Chalmers, Industrial and Materials Science, Material and Computational Mechanics

npj Computational Materials

20573960 (eISSN)

Vol. 10 1 50

UTMOST - Modelling of biobased composites in crash applications

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

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

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

Subject Categories

Accelerator Physics and Instrumentation

Other Physics Topics

Composite Science and Engineering

Areas of Advance

Materials Science

DOI

10.1038/s41524-024-01234-5

More information

Latest update

4/5/2024 8