Mapping the chloride-induced corrosion damage risks for bridge decks under climate change

被引:5
|
作者
Xu, Mingsai [1 ]
Yang, Cancan [1 ]
机构
[1] McMaster Univ, Dept Civil Engn, Hamilton, ON, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Corrosion; reinforced concrete; bridge decks; machine learning; climate change impact; time-dependent reliability; corrosion hazard maps; data visualization tools; REINFORCED-CONCRETE STRUCTURES; RELIABILITY-ANALYSIS; STEEL CORROSION; PHYSICAL MODEL; SEA STRUCTURES; SERVICE LIFE; PREDICTION; INITIATION; DIFFUSION; REPAIR;
D O I
10.1080/15732479.2023.2236599
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Climate change is expected to alter the environmental factors that are known to influence the corrosion process, creating additional uncertainties in the long-term performance of reinforced concrete (RC) decks. With due consideration of site-specific exposure and environmental conditions, this study aims to investigate the degree to which projected climate change may impact corrosion-induced damage for RC bridges. A hierarchical two-tier framework was developed incorporating the material deterioration process simulation at the local element level, and a component level prediction of the corrosion-induced damage severity and extent over the bridge deck domain. The predictive accuracy of this framework was validated against the historical bridge inspection data. Case studies were performed for decks located in Toronto and Victoria to investigate the influence of climate data resolution and climate projection models on deck deterioration status. At last, ANN (artificial neural network) and SVM (support vector machine) approaches were used to generate a series of cartographic expressions to reveal how the corrosion-induced deck deterioration risk varies with the region due to the difference in the environmental conditions. These maps can serve as visual tools to express the corrosion damage risks for different bridge locations and to formulate region-based durability design requirements.
引用
收藏
页数:17
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