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Comparing fracture openings in mortar using different imaging techniques

Jonathan Marliot
Jonathan Marliot
, 
Stephen Hedan
Stephen Hedan
, 
Marja Siitari-Kauppi
Marja Siitari-Kauppi
, 
Juuso Sammaljärvi
Juuso Sammaljärvi
, 
Catherine Landesman
Catherine Landesman
, 
Pierre Henocq
Pierre Henocq
 and 
Paul Sardini
Paul Sardini
   | Mar 30, 2024
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Article Category: Research Article
Published Online: Mar 30, 2024
Page range: -
Received: Dec 15, 2023
Accepted: Feb 23, 2024
DOI: https://doi.org/10.2478/sgem-2024-0004
Keywords
© 2024 Jonathan Marliot et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.

Figure 1:

Comparison of two mortar samples’ XRCT images obtained from different vibration methods: 15 sec for tiers 1 and 2 and 1 min 15 sec for tier 3 (A) versus 1 min 15 sec per tier (B).
Comparison of two mortar samples’ XRCT images obtained from different vibration methods: 15 sec for tiers 1 and 2 and 1 min 15 sec for tier 3 (A) versus 1 min 15 sec per tier (B).

Figure 2:

The same area of the fracture in sample #39 visualised by optical microscopy (OM), magnification: x40 (A) and scanning electron microscopy (SEM) using the BSEi observation mode, magnification: x45 (B).
The same area of the fracture in sample #39 visualised by optical microscopy (OM), magnification: x40 (A) and scanning electron microscopy (SEM) using the BSEi observation mode, magnification: x45 (B).

Figure 3:

Tomographic slice of samples #5, #16 and #39.
Tomographic slice of samples #5, #16 and #39.

Figure 4:

Workflow employed for fracture segmentation. a) Greyscale tomographic slice of sample #16. b) Magnification of a region of interest of a). c) Mask image obtained by thresholding by boundaries, which is filtered in d) to remove structures which are not connected to the fracture. e) Skeletonised fracture. f) Checking the centre of the skeleton in relation to the fracture. g) View of grey-level profiles associated to the skeleton.
Workflow employed for fracture segmentation. a) Greyscale tomographic slice of sample #16. b) Magnification of a region of interest of a). c) Mask image obtained by thresholding by boundaries, which is filtered in d) to remove structures which are not connected to the fracture. e) Skeletonised fracture. f) Checking the centre of the skeleton in relation to the fracture. g) View of grey-level profiles associated to the skeleton.

Figure 5:

Mapping of the same fractured sample, #5, with X-ray computed tomography (XRCT) (A), A/A0 mapping obtained from 14C-PMMA autoradiography (B) and the normal strain (Ɛzz) obtained by heaviside-digital volumetric correlation (H-DVC) (C).
Mapping of the same fractured sample, #5, with X-ray computed tomography (XRCT) (A), A/A0 mapping obtained from 14C-PMMA autoradiography (B) and the normal strain (Ɛzz) obtained by heaviside-digital volumetric correlation (H-DVC) (C).

Figure 6:

Sample #5: Fracture aperture distribution, XRCT (blue), 14C-PMMA (orange) and H-DVC (black) methods. The distributions are displayed as probability density functions. Voxel size for XRCT and H-DVC methods: 54.6 µm and pixel size for the 14C-PMMA method: 10.6 µm.
Sample #5: Fracture aperture distribution, XRCT (blue), 14C-PMMA (orange) and H-DVC (black) methods. The distributions are displayed as probability density functions. Voxel size for XRCT and H-DVC methods: 54.6 µm and pixel size for the 14C-PMMA method: 10.6 µm.

Figure 7:

Sample #39: Fracture aperture distribution, XRCT (blue) and 14C-PMMA (orange) methods. The distributions are displayed as probability density functions. Voxel size for the XRCT method: 24.4 µm and pixel size for the 14C-PMMA method: 10.6 µm.
Sample #39: Fracture aperture distribution, XRCT (blue) and 14C-PMMA (orange) methods. The distributions are displayed as probability density functions. Voxel size for the XRCT method: 24.4 µm and pixel size for the 14C-PMMA method: 10.6 µm.

Figure 8:

Sample #16: Fracture aperture distribution, XRCT (blue) and 14C-PMMA (orange) methods. The distributions are displayed as probability density functions. Voxel size for the XRCT method: 24.4 µm and pixel size for the 14C-PMMA method: 10.6 µm.
Sample #16: Fracture aperture distribution, XRCT (blue) and 14C-PMMA (orange) methods. The distributions are displayed as probability density functions. Voxel size for the XRCT method: 24.4 µm and pixel size for the 14C-PMMA method: 10.6 µm.

Figure 9:

Fracture apertures of sample #16 obtained with XRCT. The distributions are displayed as probability density functions. Voxel size: 24.4 µm.
Fracture apertures of sample #16 obtained with XRCT. The distributions are displayed as probability density functions. Voxel size: 24.4 µm.

Figure 10:

Summary graphic of fracture opening obtained by the five methods. The black dots correspond to the artefact values for the XRCT and 14C-PMMA methods and for air bubbles for the OM and SEM methods.
Summary graphic of fracture opening obtained by the five methods. The black dots correspond to the artefact values for the XRCT and 14C-PMMA methods and for air bubbles for the OM and SEM methods.

Summary of average fracture opening obtained using X-ray computed tomography (XRCT), 14C-PMMA autoradiographs (14C-PMMA) and heaviside-digital volumetric correlation (H-DVC) methods. The numbers of data used to calculate the average values are indicated in brackets.

#5 (µm) #39 (µm) #16 (µm)
XRCT 21.2 ± 9.1 [585] 32.1 ± 13.1 [1549] 120.1 ± 68.3 [3685]
H-DVC 18.6 ± 8.1 [741] - -
14C-PMMA 18.6 ± 5.7 [3414] 26.1 ± 8 [3331] 180.2 ± 72.4 [6051]

Comparison of fracture densities calculated using the XRCT and 14C-PMMA methods. These results were obtained from the same data used to calculate the mean aperture values presented in Table 2, except for the 14C-PMMA method for sample #16 where all the data were considered.

Fracture densities (mm−1)
XRCT 14C-PMMA
#5 3.3 ± 0.3 × 10−2 3.7 ± 0.4 × 10−2
#39 3.8 ± 0.4 × 10−2 3.5 ± 0.4 × 10−2
#16 9.1 ± 0.9 × 10−2 7.6 ± 0.8 × 10−2

Process duration and constraints for each method of aperture and density analysis.

Process duration Disadvantages
OM A few hours Manual analysis of few points / Difficulties of fracture observation
SEM 1 day Manual analysis of few points / long analysis time
XRCT 1 day Fracture detection depends on image resolution
H-DVC A few weeks / months Fracture detection depends on image resolution / long process and analysis time, two image acquisitions
14C-PMMA A few months Use of radioactive tracer / long process time / semi-destructive method

Summary of average fracture opening obtained using microscopy methods: optical microscopy (OM) and scanning electron microscopy (SEM). The number of observation points is indicated in brackets.

#5 (µm) #39 (µm) #16 (µm)
OM 15.6 ± 5.5 [12] 29.3 ± 14.6 [80] 131.8 ± 85.7 [33]
SEM 15.8 ± 6.1 [59] 25 ± 14.2 [121] 129.5 ± 136.8 [137]
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