This study applies machine learning (ML) methods to predict post-impact damage states of
reinforced concrete (RC) bridge piers under vehicle collision. 251 datasets of various …

Performance-based earthquake engineering requires the identification of different damage
states in structural components. Bridge piers are one of the most critical components in the …

This study investigates the failure behavior and post-impact damage of glass fiber reinforced
polymer (GFRP) bar reinforced bridge pier under truck collision. The finite element model of …

Along with the increase of motor vehicles on the roads, the number of vehicle collisions with
highway bridge piers has increased. The collision can cause severe damage to the structure …

Reinforcement concrete (RC) pier columns are the main supporting elements of many
highway bridges and city viaducts, therefore the health state of a pier column is critical to the …

Railway bridges in mountainous regions are susceptible to damage and collapse due to
rockfall impacts, posing a risk to train operations. This research specifically focuses on risk …

This paper presents a novel probabilistic classification framework for promptly assessing the
probability of barge–bridge collision damage of piers based on Bayesian inference with …

Heavy vehicle collisions have been reported as one of the major causes of normal concrete
(NC) bridge pier failure due to its low crashworthiness. Ultra-high performance concrete …

This study presents a machine learning (ML) approach to identify vulnerability of bridges to
fire hazard. For developing this ML approach, data on a series of bridge fires was first …

Bridge piers have a high risk of being attacked in wartime, which has the potential to trigger
progressive bridge collapse. This study aims to predict the failure probability of reinforced …