Scour Prediction

Scour prediction focuses on accurately estimating the erosion of soil around bridge foundations and other structures, a critical factor in infrastructure safety and longevity. Current research emphasizes the use of deep learning models, particularly Long Short-Term Memory (LSTM) and Convolutional Neural Networks (CNN), often integrated with physics-based equations, to improve prediction accuracy using real-time sensor data and historical records. These advanced methods aim to overcome limitations of traditional empirical models, offering more reliable risk assessments and enabling the development of early warning systems for timely intervention and improved bridge management. The improved accuracy and timeliness of scour predictions have significant implications for infrastructure maintenance and public safety.