Dams are among the most important civil engineering structures, but they are also susceptible to damage that can endanger their stability and functionality. It is therefore crucial to detect any damage in dams to ensure their long-term integrity and overall safety. In light of this, the present study proposes a new two-stage method for identifying damage in concrete gravity dams. In the first stage, a modal curvature-based damage index (MCBDI) is presented to detect the location of suspected damaged zones along the height of the dam. The mode shape data collected from some measurement points on the downstream side of the dam is used to accomplish this task. In the second stage, the pathfinder algorithm (PFA) as a powerful meta-heuristic optimization technique is applied to determine the severity of potentially damaged zones by minimizing an objective function specified in terms of natural frequencies and mode shapes. The capability and effectiveness of the proposed method are evaluated by implementing two numerical simulation examples of concrete gravity dams under both noise-free and noisy conditions. The results obtained suggest that the proposed two-stage method, comprising the MCBDI indicator and the PFA algorithm, represents an accurate and efficient approach for localizing and quantifying damage in concrete gravity dams.
