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Computers and Concrete Volume 12, Number 1, July 2013 , pages 091-107 DOI: https://doi.org/10.12989/cac.2013.12.1.091 |
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Reliability assessment of concrete bridges subject to corrosion-induced cracks during life cycle using artificial neural networks |
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Afshin Firouzi and Alireza Rahai
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| Abstract | ||
| Corrosion of RC bridge decks eventually leads to delamination, severe cracking and spalling of the concrete cover. This is a prevalent deterioration mechanism and demands for the most costly repair interventions during the service life of bridges worldwide. On the other hand, decisions for repairs are usually made whenever the extent of a limit crack width, reported in routine visual inspections, exceeds an acceptable threshold level. In this paper, while random fields are applied to account for spatial variation of governing parameters of the corrosion process, an analytical model is used to simulate the corrosion induced crack width. However when dealing with random fields, the Monte Carlo simulation is apparently an inefficient and time consuming method, hence the utility of neural networks as a surrogate in simulation is investigated and found very promising. The proposed method can be regarded as an invaluable tool in decision making concerning maintenance of bridges. | ||
| Key Words | ||
| concrete; corrosion; random field; ANN; Monte carlo | ||
| Address | ||
| Afshin Firouzi: Construction Engineering and Management Group, Islamic Azad University, Science and Research Branch, Tehran, Iran Alireza Rahai: Department of Civil Engineering, Amirkabir University of Technology, Tehran, Iran | ||