X-ray computed tomography data structure tensor orientation mapping for finite element models - STXAE

Robert M. Auenhammer; Niels Jeppesen; Lars Pilgaard Mikkelsen; Vedrana A. Dahl; Leif E. Asp

doi:10.1016/j.simpa.2021.100216

X-ray computed tomography data structure tensor orientation mapping for finite element models - STXAE

Robert M. Auenhammer^*
, Niels Jeppesen
, Lars Pilgaard Mikkelsen
, Vedrana A. Dahl
, Leif E. Asp

^*Corresponding author for this work

Chalmers University of Technology

Research output: Contribution to journal › Journal article › Research › peer-review

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Abstract

Accurate modelling of fibre-reinforced composites requires anisotropic material models. Structure tensor analysis of X-ray 3D images has been shown to provide fast and robust estimation of local structural orientations in fibre-reinforced composites. We present two mapping algorithms which can be used to map estimated local orientations onto finite element models for more accurate material modelling. The two functions allow for elementwise and integration point-wise mapping, respectively, and have been implemented using Python in a Jupyter notebook. Together with the previously published structure tensor code, these two functions demonstrate the concept of Structure Tensor X-ray computed tomography Aided Engineering (STXAE) (Phonetics: [stekseIi:]).

Original language	English
Article number	100216
Journal	Software Impacts
Volume	11
Number of pages	3
ISSN	2665-9638
DOIs	https://doi.org/10.1016/j.simpa.2021.100216
Publication status	Published - 2022

Keywords

X-ray computed tomography
Material orientation anaysis
Structure tensor
Orientation mapping finite elements

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3DIM: 3D imaging center
Poulsen, H. F. (Project Manager), Gundlach, C. (Project Manager), Dahl, A. B. (Project Participant), Oddershede, J. (Project Participant), Trinderup, C. H. (Project Participant), Simonsen, S. B. (Project Participant), Zheng, Y. (Project Participant), Brink, B. (Project Participant), Lauridsen, T. (Project Participant), Thydén, K. T. S. (Project Participant), Sanna, S. (Project Participant), Baier-Stegmaier, S. M. (Project Participant), Bentzen, J. J. (Project Participant), Christensen, A. N. (Project Participant), Sørensen, H. O. (Project Participant), Mikkelsen, L. P. (Project Participant), Fæster, S. (Project Participant), Johansen, N.F.-J. (PI), Mokso, R. (PI), Kjer, H. M. (PI), Christensen, A. N. (PI), Quagliotti, D. (PI), Zhang, Y. (PI), Rasmussen, P. W. (PI) & Dahl, V. A. (PI)
01/01/2016 → 31/12/2029
Project: Research

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1 Journal article

Robust numerical analysis of fibrous composites from X-ray computed tomography image data enabling low resolutions
Auenhammer, R. M., Jeppesen, N., Mikkelsen, L. P., Dahl, V. A., Blinzler, B. J. & Asp, L. E., 2022, In: Composites Science and Technology. 224, 12 p., 109458.
Research output: Contribution to journal › Journal article › Research › peer-review

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title = "X-ray computed tomography data structure tensor orientation mapping for finite element models - STXAE",

abstract = "Accurate modelling of fibre-reinforced composites requires anisotropic material models. Structure tensor analysis of X-ray 3D images has been shown to provide fast and robust estimation of local structural orientations in fibre-reinforced composites. We present two mapping algorithms which can be used to map estimated local orientations onto finite element models for more accurate material modelling. The two functions allow for elementwise and integration point-wise mapping, respectively, and have been implemented using Python in a Jupyter notebook. Together with the previously published structure tensor code, these two functions demonstrate the concept of Structure Tensor X-ray computed tomography Aided Engineering (STXAE) (Phonetics: [stekseIi:]).",

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year = "2022",

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volume = "11",

journal = "Software Impacts",

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AU - Jeppesen, Niels

AU - Mikkelsen, Lars Pilgaard

AU - Dahl, Vedrana A.

AU - Asp, Leif E.

PY - 2022

Y1 - 2022

N2 - Accurate modelling of fibre-reinforced composites requires anisotropic material models. Structure tensor analysis of X-ray 3D images has been shown to provide fast and robust estimation of local structural orientations in fibre-reinforced composites. We present two mapping algorithms which can be used to map estimated local orientations onto finite element models for more accurate material modelling. The two functions allow for elementwise and integration point-wise mapping, respectively, and have been implemented using Python in a Jupyter notebook. Together with the previously published structure tensor code, these two functions demonstrate the concept of Structure Tensor X-ray computed tomography Aided Engineering (STXAE) (Phonetics: [stekseIi:]).

AB - Accurate modelling of fibre-reinforced composites requires anisotropic material models. Structure tensor analysis of X-ray 3D images has been shown to provide fast and robust estimation of local structural orientations in fibre-reinforced composites. We present two mapping algorithms which can be used to map estimated local orientations onto finite element models for more accurate material modelling. The two functions allow for elementwise and integration point-wise mapping, respectively, and have been implemented using Python in a Jupyter notebook. Together with the previously published structure tensor code, these two functions demonstrate the concept of Structure Tensor X-ray computed tomography Aided Engineering (STXAE) (Phonetics: [stekseIi:]).

KW - X-ray computed tomography

KW - Material orientation anaysis

KW - Structure tensor

KW - Orientation mapping finite elements

U2 - 10.1016/j.simpa.2021.100216

DO - 10.1016/j.simpa.2021.100216

M3 - Journal article

SN - 2665-9638

VL - 11

JO - Software Impacts

JF - Software Impacts

M1 - 100216

ER -

X-ray computed tomography data structure tensor orientation mapping for finite element models - STXAE

Abstract

Keywords

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Projects

3DIM: 3D imaging center

Research output

Robust numerical analysis of fibrous composites from X-ray computed tomography image data enabling low resolutions

Cite this