A B-WIM algorithm considering the modeling of the bridge dynamic response. (1st February 2021)

• Record Type: Journal Article
• Authors: Gonçalves, Matheus Silva; Carraro, Felipe; Lopez, Rafael Holdorf
• Is Part Of: Engineering structures. Volume 228(2021)
• Publication Date: 2021-02-01
• Subjects: Influence lines -- Bridge weigh-in-motion -- Dynamic modeling -- Vehicle weight prediction; Structural engineering -- Periodicals; Structural analysis (Engineering) -- Periodicals; Construction, Technique de la -- Périodiques; Génie parasismique -- Périodiques; Pression du vent -- Périodiques; Earthquake engineering; Structural engineering; Wind-pressure; Periodicals; 624.105
• DOI: 10.1016/j.engstruct.2020.111533
• Languages: English
• ISSNs: 0141-0296

Abstract

Highlights: Application of a maximum likelihood method for assembling influence lines based on multiple vehicle runs. Employment of a simplified and computationally inexpensive dynamic modeling for the vehicle-bridge system. Extension of a dynamics-incorporating influence line extraction method for weighing vehicles. Calculation of continuous influence line curves, whilst incorporating the effect of vehicle speed. Numerical parametric investigation of three variations of the method and their underlying generalization capabilities compared to static algorithms. Abstract: A Bridge weigh-in-motion (B-WIM) system is able to estimate vehicle weights based on data gathered by sensors underneath the bridge structure. It is a valuable tool for many applications related to the assessment of bridges safety, already operating in many sites around the world. Although the dynamic behavior of the bridge structure is a well recognized troublesome point for the improvement in B-WIM algorithm performance, most of the current employed methods rely only on static assumptions. The main goal of the present study is to adapt a simplified dynamic modeling, proposed by a recent study, to work as a B-WIM algorithm. Three main modifications are performed: the implementation of a maximum likelihood approach to perform the influence line assembly strategy for data regarding multiple runs, the derivation of a weigh procedure and the inclusion of the full analytical dynamic model. As a result, the method described is able to calculate influence lines that are both continuous curves and a direct function of the vehicle speed. Furthermore, the overall procedure needs only simple matrix operations, resulting in a computational cost similar to the static algorithms. Numerical simulations related to bridges with distinct span lengths and road roughness profiles indicated that the adapted method is able to overcome the results of the current state-of-the-art methods, specially for longer bridges.