X-ray scattering tensor tomography based finite element modelling of heterogeneous materials

被引:0
|
作者
Robert M. Auenhammer
Jisoo Kim
Carolyn Oddy
Lars P. Mikkelsen
Federica Marone
Marco Stampanoni
Leif E. Asp
机构
[1] Chalmers University of Technology,Material and Computational Mechanics, Department of Industrial and Materials Science
[2] Technical University of Denmark,Composites Manufacturing and Testing, Department of Wind and Energy Systems
[3] University and ETH Zürich,Institute for Biomedical Engineering
[4] Paul Scherrer Institut,Swiss Light Source
[5] GKN Aerospace Sweden,Department of Automation and Composite Technologies
[6] Korea Research Institute of Standards and Science,Advanced Instrumentation Institute
关键词
D O I
暂无
中图分类号
学科分类号
摘要
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.
引用
收藏
相关论文
共 50 条
  • [1] X-ray scattering tensor tomography based finite element modelling of heterogeneous materials
    Auenhammer, Robert M.
    Kim, Jisoo
    Oddy, Carolyn
    Mikkelsen, Lars P.
    Marone, Federica
    Stampanoni, Marco
    Asp, Leif E.
    NPJ COMPUTATIONAL MATERIALS, 2024, 10 (01)
  • [2] Finite element modelling of the actual structure of cellular materials determined by X-ray tomography
    Youssef, S
    Maire, E
    Gaertner, R
    ACTA MATERIALIA, 2005, 53 (03) : 719 - 730
  • [3] X-ray tomography image-based reconstruction of microstructural finite element mesh models for heterogeneous materials
    Huang, Ming
    Li, Yue-ming
    COMPUTATIONAL MATERIALS SCIENCE, 2013, 67 : 63 - 72
  • [4] X-ray scattering tensor tomography with circular gratings
    Kim, Jisoo
    Kagias, Matias
    Marone, Federica
    Stampanoni, Marco
    APPLIED PHYSICS LETTERS, 2020, 116 (13)
  • [5] Fast acquisition protocol for X-ray scattering tensor tomography
    Jisoo Kim
    Matias Kagias
    Federica Marone
    Zhitian Shi
    Marco Stampanoni
    Scientific Reports, 11
  • [6] Fast acquisition protocol for X-ray scattering tensor tomography
    Kim, Jisoo
    Kagias, Matias
    Marone, Federica
    Shi, Zhitian
    Stampanoni, Marco
    SCIENTIFIC REPORTS, 2021, 11 (01)
  • [7] X-ray tensor tomography
    Malecki, A.
    Potdevin, G.
    Biernath, T.
    Eggl, E.
    Willer, K.
    Lasser, T.
    Maisenbacher, J.
    Gibmeier, J.
    Wanner, A.
    Pfeiffer, F.
    EPL, 2014, 105 (03)
  • [8] Towards lab-based X-ray scattering tensor tomography with circular gratings
    Slyamov, Azat
    Kim, Jisoo
    Pedersen, Mads A.
    Nielsen, Kenneth K.
    Pedersen, Anders F.
    Ramos, Tiago
    Kagias, Matias
    Lauridsen, Erik
    e-Journal of Nondestructive Testing, 2022, 27 (03):
  • [9] Universal reconstruction method for x-ray scattering tensor tomography based on wavefront modulation
    Lautizi, Ginevra
    Studer, Alain
    Zdora, Marie-Christine
    De Marco, Fabio
    Kim, Jisoo
    Di Trapani, Vittorio
    Marone, Federica
    Thibault, Pierre
    Stampanoni, Marco
    PHYSICAL REVIEW APPLIED, 2024, 22 (02):
  • [10] X-ray computed tomography data structure tensor orientation mapping for finite element models - STXAE
    Auenhammer, Robert M.
    Jeppesen, Niels
    Mikkelsen, Lars P.
    Dahl, Vedrana A.
    Asp, Leif E.
    SOFTWARE IMPACTS, 2022, 11