Early damage detection of fatigue failure for RC deck slabs under wheel load moving test using image analysis with artificial intelligence. (1st November 2021)
- Record Type:
- Journal Article
- Title:
- Early damage detection of fatigue failure for RC deck slabs under wheel load moving test using image analysis with artificial intelligence. (1st November 2021)
- Main Title:
- Early damage detection of fatigue failure for RC deck slabs under wheel load moving test using image analysis with artificial intelligence
- Authors:
- Adel, Mohamed
Yokoyama, Hiroshi
Tatsuta, Hitoshi
Nomura, Takanori
Ando, Yuki
Nakamura, Takuro
Masuya, Hiroshi
Nagai, Kohei - Abstract:
- Highlights: Un-damaged and ASR-damaged RC deck slabs are tested under moving wheel loading. Detection of small delaminations (pits) along cracks that arise from out-of-plane shear deformations. U-Net architecture is proposed as machine learning model AI for crack's detection. Pit density could be considered an early index of upcoming fatigue failure RC deck slabs. Abstract: Reinforced concrete (RC) bridge decks suffer from cracking damages caused by traffic loading and environmental-related defects, such as the alkali-silica reaction (ASR). These require inspections involving measuring crack width and density followed by essential maintenance and repair works, however, there are no signs for fatigue failure. In this study, the out-of-plane shear deformations which cause small delaminations (pits) along surface cracks are proposed as an early indicator for fatigue failure. Thus, un-damaged and ASR-damaged RC deck slabs are tested under moving wheel loading and, using image-recognition for surface cracks detection, the pits along surface cracks are captured using an artificial intelligence (AI) model. The results show that, while both crack and pit density increase over the fatigue life of un-damaged slabs, there is an earlier sudden increase in pit density. In the case of the ASR-damaged slab, surface cracking is almost constant over the fatigue life until a sudden increase just prior to failure. Pit density, however, increases over the fatigue life with an earlier rapidHighlights: Un-damaged and ASR-damaged RC deck slabs are tested under moving wheel loading. Detection of small delaminations (pits) along cracks that arise from out-of-plane shear deformations. U-Net architecture is proposed as machine learning model AI for crack's detection. Pit density could be considered an early index of upcoming fatigue failure RC deck slabs. Abstract: Reinforced concrete (RC) bridge decks suffer from cracking damages caused by traffic loading and environmental-related defects, such as the alkali-silica reaction (ASR). These require inspections involving measuring crack width and density followed by essential maintenance and repair works, however, there are no signs for fatigue failure. In this study, the out-of-plane shear deformations which cause small delaminations (pits) along surface cracks are proposed as an early indicator for fatigue failure. Thus, un-damaged and ASR-damaged RC deck slabs are tested under moving wheel loading and, using image-recognition for surface cracks detection, the pits along surface cracks are captured using an artificial intelligence (AI) model. The results show that, while both crack and pit density increase over the fatigue life of un-damaged slabs, there is an earlier sudden increase in pit density. In the case of the ASR-damaged slab, surface cracking is almost constant over the fatigue life until a sudden increase just prior to failure. Pit density, however, increases over the fatigue life with an earlier rapid increase before failure. The density of pits along cracks would be, therefore, a significantly earlier indicator of fatigue failure than crack density, offering the potential for more efficient and automatable bridge inspections. … (more)
- Is Part Of:
- Engineering structures. Volume 246(2021)
- Journal:
- Engineering structures
- Issue:
- Volume 246(2021)
- Issue Display:
- Volume 246, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 246
- Issue:
- 2021
- Issue Sort Value:
- 2021-0246-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-11-01
- Subjects:
- RC deck slab -- ASR damage -- Moving wheel loading -- AI -- Crack density -- Pit density
Structural engineering -- Periodicals
Structural analysis (Engineering) -- Periodicals
Construction, Technique de la -- Périodiques
Génie parasismique -- Périodiques
Pression du vent -- Périodiques
Earthquake engineering
Structural engineering
Wind-pressure
Periodicals
624.105 - Journal URLs:
- http://www.sciencedirect.com/science/journal/01410296 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.engstruct.2021.113050 ↗
- Languages:
- English
- ISSNs:
- 0141-0296
- Deposit Type:
- Legaldeposit
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