Risk assessment is crucial to the safety and durability of buildings constructed using concrete with high concentrations of chloride ions. This study adopted grey statistical clustering and multi-phase fuzzy statistics in the development of a risk assessment model for existing reinforced concrete buildings. In the proposed model, evaluative indicators are divided into two categories: strength category included compressive strength and corrosion category included carbonation depth, chloride ion content, and steel corrosion current. Overall, the risk to the building can be divided into three levels (low, medium, and high) based on critical values in risk evaluation strategies, parameter weights, and grey statistical clustering coefficients. A case study is presented to demonstrate the applicability and effectiveness of the proposed model.

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