Climate Data and Its Effects on Concrete Structures Using ML Model

This research focuses on chloride-induced corrosion, which remains a major challenge to the durability and serviceability of concrete structures and structures in general due to the effects of climate change. Chloride ions cause undesirable reactions that not only affect the concrete matrix but also the reinforcement bar resulting in problems such as cracking, spalling, and danger of ultimate failure. Temperature changes and increased humidity due to climate change also affect rates of corrosion and carbonation making concrete even more tender. Carbonation weakens the protection of the steel bars by reducing the alkalinity which protects against rust. The maintenance issues are the fluctuations of local climatic conditions: depth of carbonation and chloride penetration can be rather different for two close squares. This research seeks to establish proactive measures and better methods of maintenance using sophisticated corrosion models to reduce the effects of climate change on concrete structures. In addition to the climate data of Velachery, Manali, and Alandur obtained using machine learning, this study intends to advance understanding of how climate influences concrete durability. This knowledge is particularly useful when planning and constructing transportation and infrastructure structures that would be immune to environmental changes, and chloride intrusion.