A Milestone Vision on The Applied Methodologies for Concrete Dam Health Monitoring

Abstract

This research reviews the applied various methodologies for concrete dams’ health monitoring and assessment. The main type of dams focused on this review is the embankment fill dams that serves as an important function in water supply, irrigation, and hydroelectric power. The emphasis is devoted on the integration and assessment of static and dynamic methods for dams monitoring in order to improve safety and increase the life span of dams. Static methods are usually monitor changes that are prolonged over time and are critical for the assessment of the enduring structural health. Whereas, dynamic methods are considered as real-time data crucial to address immediate changes in the environment and operation. Mathematical models and structural health monitoring techniques were surveyed that improves the encompass of hydraulic, thermal, crack, and time (HTCT) model for extreme conditions. In addition, the use of artificial intelligence (AI) was explored and particularly for internal erosion monitoring. Comparison of such analyses reveals that static monitoring is efficient in its approach to assessment over the long term, while dynamic monitoring performs better in coping with instant changes. Based on the review findings, therefore, it could be concluded that an integrated approach with the use of static and dynamic methods, supported by advanced computational models, would enhance the effectiveness of monitoring systems. The future work shall focus on the development of such integrated systems to increase the resilience of dam infrastructures, while the monitoring technologies have to be adapted continuously to the environmental challenges and the complexity of dam systems.