Vulnerability Assessment of Reinforced Concrete Piers Under Vehicle Collision Considering the Influence of Uncertainty

• Published in: Buildings (Basel) Vol. 15; no. 8; p. 1222
• Main Authors: Yu, Xiaohui, Chen, Yihang, He, Yu
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.04.2025
• Subjects: Accidents; Agricultural equipment; Bridge piers; Bridges; Collapse; Collisions; Concrete; Concrete properties; Damage; Distribution (Probability theory); Earthquakes; Farm tractors; Impact tests; Influence; Liu, Timothy; Mathematical models; Monte Carlo method; Monte Carlo simulation; Numerical models; parameter analysis; Parameter uncertainty; Piers; Probabilistic analysis; RC piers; Reinforced concrete; Shear strength; Simulation methods; Software; Statistical analysis; Stirrups; Tractors; Trucks; uncertainty analysis; vehicle collision; Vehicles; Velocity; vulnerability analysis; Waterfront development; United States; China
• ISSN: 2075-5309; 2075-5309
• DOI: 10.3390/buildings15081222

In recent years, the serious damage and even collapse accidents of bridge under vehicle-to-pier collision occurred frequently and have attracted growing attention world widely. Numerous studies have been conducted to examine the structural resistance of bridge piers against vehicle-with-pier collisions. Nevertheless, most of those studies employed a deterministic approach without incorporating the inherent uncertainty in structural and loading parameters. This study proposes a probabilistic approach to investigate the vulnerability of reinforced concrete (RC) piers under collisions with trucks and tractors. To do this, a dynamic mass-spring numerical model was developed to simulate the pier–vehicle collision process, which was further validated through simulating experimental data. A total of four parameters, including concrete strength, pier diameter, stirrup yield strength, and stirrup spacing, were considered and regarded as uncertainty parameters with their probability distributions determined according to the available studies. The Monte Carlo simulation method was used to generate 1000 samples for each of the uncertainty parameters and these random samples were coupled in the simplified numerical model. Through probabilistic analysis, the collapse vulnerability of RC piers was estimated. The results revealed that a tractor with a higher mass can result in higher failure probabilities than a truck. The uncertainty of the pier diameter and concrete strength have a great impact on the vulnerability of RC piers under different damage states.