Simplified vehicle–bridge interaction for medium to long-span bridges subject to random traffic load

• Published in: Journal of civil structural health monitoring Vol. 10; no. 4; pp. 693 - 707
• Main Authors: Sadeghi Eshkevari, Soheil, Matarazzo, Thomas J., Pakzad, Shamim N.
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2020; Springer Nature B.V
• Subjects: Bridge loads; Civil Engineering; Comparative studies; Compatibility; Computer simulation; Control; Dynamical Systems; Engineering; Measurement Science and Instrumentation; Original Paper; Random excitation; Vibration; White noise; Numerical simulation; Mobile sensing; Crowdsensing; Coupled system; Vehicle-bridge interaction
• ISSN: 2190-5452; 2190-5479
• DOI: 10.1007/s13349-020-00413-4

This study introduces a simplified model for bridge–vehicle interaction for medium- to long-span bridges subject to random traffic loads. Previous studies have focused on calculating the exact response of the vehicle or the bridge based on an interaction force derived from the compatibility between two systems. This process requires multiple iterations per time step per vehicle until the compatibility is reached. When a network of vehicles is considered, the compatibility equation turns to a system of coupled equations which dramatically increases the complexity of the convergence process. In this study, we simplify the problem into two sub-problems that are decoupled: (a) a bridge subject to random excitation, and (b) individual sensing agents that are subjected to linear superposition of the bridge response and the road profile roughness. The study provides sufficient evidences to confirm that the proposed simulation approach is valid with minimal error when the bridge span is medium to long, and the spatio-temporal load pattern can be modeled as random white noise. The latter assumption is verified using a comparative study on a random traffic network. Quantitatively, the proposed approach is over 1000 times computationally more efficient when compared to the conventional approach for a 500 m long bridge, with response simulation errors below 0.1%.