Probabilistic estimation of flexural loading capacity of existing RC structures based on observational corrosion-induced crack width distribution using machine learning

Zhang, Mingyang; Akiyama, Mitsuyoshi; Shintani, Mina; Xin, Jiyu; Frangopol, Dan M.

doi:10.1016/j.strusafe.2021.102098

Cited by 49 publications

(12 citation statements)

References 48 publications

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“…Compared with the epoxy coating, the R c values of WO 3 , WO 2.9 , WO 2.72 , and WO 2 coatings were increased by 48.67, 192.90, 413.00, and 155.09%, respectively. The larger the R c value, the better the properties to prevent the invasion of water and aggressive ions. , The defects, pores, and other artifact in coatings were cemented with the help of WO 3– x MVMOs; thus, the diffusion of aqueous corrosive ions was restricted and the shielding properties of the coatings were enhanced. The contact angle test (Figure S1) revealed that the WO 2.72 coating had the largest contact angle and the smallest surface energy, indicating the difficulty of WO 2.72 coating for water and Cl – to penetrate into the surface, thus mentioning the corrosion resistance.…”

Section: Results and Discussionmentioning

confidence: 99%

Gradient Design of Vacancies and Their Positive Correlation with Electrochemical Anticorrosion Protection

et al. 2022

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The contribution of defects to electrochemistry is a controversial but practically applicable subject. Meanwhile, it is challenging to obtain precisely a certain nonchemometric single phase in mixed-valence compounds. The precise design of nonchemometric single-phase WO3–x (x = 0, 0.1, 0.28, and 1) mixed-valence metal oxides (MVMOs) was achieved by the gradient intrinsic reduction method, and the correlation between oxygen vacancies and electrochemical anticorrosion protection was explored systematically. Then, the decisive role of periodic oxygen vacancies in electrochemical anticorrosion was confirmed. And the origin was the synergistic reaction of oxygen vacancy-upgraded photocathodic protection, vacancy-induced passivation, and mixed-valence reductive protection, which were brought about by the high oxygen vacancy concentration. Integrating the above three aspects, the WO2.72 MVMO showed the best electrochemical anticorrosion performance by increasing the resistance value to 7.67 times that of the epoxy resin coating. The establishment of a positive correlation between oxygen vacancy and corrosion protection in WO3–x (x = 0, 0.1, 0.28, and 1) materials can not only guide the design of MVMOs but also make an important contribution to the rapid precorrosion performance of the materials.

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Section: Results and Discussionmentioning

confidence: 99%

Gradient Design of Vacancies and Their Positive Correlation with Electrochemical Anticorrosion Protection

et al. 2022

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“…Thus, a risk system should be developed for every type of tunnel support. The structural capacity and risk with respect to cracks in reinforced cast concrete have been well studied, see, e.g., [ 92 , 93 , 94 ]. However, for fiber-reinforced concrete, there is a lack of research on experimental testing and numerical simulation focusing on the effect of cracks.…”

Section: Assessment Of the Safety Of Damaged Concrete Liningsmentioning

confidence: 99%

Towards Automated Inspections of Tunnels: A Review of Optical Inspections and Autonomous Assessment of Concrete Tunnel Linings

Sjölander

Belloni

Ansell

et al. 2023

Sensors

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In recent decades, many cities have become densely populated due to increased urbanization, and the transportation infrastructure system has been heavily used. The downtime of important parts of the infrastructure, such as tunnels and bridges, seriously affects the transportation system’s efficiency. For this reason, a safe and reliable infrastructure network is necessary for the economic growth and functionality of cities. At the same time, the infrastructure is ageing in many countries, and continuous inspection and maintenance are necessary. Nowadays, detailed inspections of large infrastructure are almost exclusively performed by inspectors on site, which is both time-consuming and subject to human errors. However, the recent technological advancements in computer vision, artificial intelligence (AI), and robotics have opened up the possibilities of automated inspections. Today, semiautomatic systems such as drones and other mobile mapping systems are available to collect data and reconstruct 3D digital models of infrastructure. This significantly decreases the downtime of the infrastructure, but both damage detection and assessments of the structural condition are still manually performed, with a high impact on the efficiency and accuracy of the procedure. Ongoing research has shown that deep-learning methods, especially convolutional neural networks (CNNs) combined with other image processing techniques, can automatically detect cracks on concrete surfaces and measure their metrics (e.g., length and width). However, these techniques are still under investigation. Additionally, to use these data for automatically assessing the structure, a clear link between the metrics of the cracks and the structural condition must be established. This paper presents a review of the damage of tunnel concrete lining that is detectable with optical instruments. Thereafter, state-of-the-art autonomous tunnel inspection methods are presented with a focus on innovative mobile mapping systems for optimizing data collection. Finally, the paper presents an in-depth review of how the risk associated with cracks is assessed today in concrete tunnel lining.

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“…Machine learning is a field that has received increased attention from researchers studying steel corrosion in concrete and has been shown to be a promising approach for predicting damage in reinforced concrete structures experiencing corrosion. 51,115,116 Some studies even have used machine learning to predict CT or corrosion initiation in concrete structures. 117,118 However, these machine learning approaches rely on existing collected data on CT that are still subject to the challenges associated with the CT concept and cannot address the big questions that are described in this paper.…”

Section: Improved Approaches To Forecasting Corrosion Of Steel In Con...mentioning

confidence: 99%

Beyond the chloride threshold concept for predicting corrosion of steel in concrete

Angst

Isgor

Hansson

et al. 2022

Applied Physics Reviews

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All existing models to forecast the corrosion performance of reinforced concrete structures exposed to chloride environments are based on one common theoretical concept, namely, a chloride threshold, as a sharply defined trigger for corrosion, followed by a period of active corrosion. We critically review the resulting treatment of corrosion initiation and propagation as two distinct, successive stages. We conclude that this concept presents a major barrier for developing reliable corrosion forecast models, and that a new approach is needed. In reality, steel corrosion in concrete is a continuous process, that is, rarely separable into uncoupled, sequential phases. We propose that the focus be placed on the quantification of the time- and space-variant corrosion rate from the moment steel is placed in concrete until it reaches the end of the service life. To achieve this, a multi-scale and multi-disciplinary approach is required to combine the scientific and practical contributions from materials science, corrosion science, cement/concrete research, and structural engineering.

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Probabilistic estimation of flexural loading capacity of existing RC structures based on observational corrosion-induced crack width distribution using machine learning

Cited by 49 publications

References 48 publications

Gradient Design of Vacancies and Their Positive Correlation with Electrochemical Anticorrosion Protection

Gradient Design of Vacancies and Their Positive Correlation with Electrochemical Anticorrosion Protection

Towards Automated Inspections of Tunnels: A Review of Optical Inspections and Autonomous Assessment of Concrete Tunnel Linings

Beyond the chloride threshold concept for predicting corrosion of steel in concrete

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