WIM-based assessment of load effects on bridges due to various classes of heavy trucks. (1st June 2017)

• Record Type: Journal Article
• Authors: Tabatabai, Habib; Titi, Hani; Zhao, Jian
• Is Part Of: Engineering structures. Volume 140(2017:Jun. 01)
• Page Start: 189
• Page End: 198
• Publication Date: 2017-06-01
• Subjects: Weigh-in-motion -- Truck loads -- Statistical analysis -- Copulas -- WIM -- Bridge loads -- Monte Carlo simulations -- Permit vehicles; 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.2017.02.060
• Languages: English
• ISSNs: 0141-0296

Abstract

Highlights: Probability of exceedance for moment or shear due to permit vehicles are addressed. Statistical information for Class 9 trucks can represent effects of all trucks. Class 9 percentile level of 98.6 equivalent to 99th percentile level for all trucks. Issuance of truck permits can be based on a selected probability of exceedance. Abstract: This study presents statistical evaluations of extreme load effects on bridges due to different truck classes. Using the developed information, a set of procedures are proposed to conduct probabilistic assessments of the relative severity of any heavy truck loading on simply-supported bridges. The truck information used in the analyses was recorded in one entire year by weigh-in-motion stations located throughout the State of Wisconsin. Data on the heaviest five percent of trucks in each truck class-axle group were extracted for analyses. Best-fit unimodal and multimodal statistical distributions for all axle loads and axle spacings (in each truck class-axle group) were determined. Standard and empirical copulas were generated to allow consideration of interdependencies between various marginal distributions. The accuracy of the developed marginal distributions and empirical copulas were verified using multivariate Monte Carlo simulations. Simulations were also used to determine magnitudes (and percentiles) of moments and shears on simply-supported bridges of various span lengths of up to 240 ft (73.2 m) for different truck class-axle groups. Procedures are provided for assessing the relative magnitude of moments/shears due to any heavy truck as percentile of each truck class-axle group, or as percentile of the entire truck population. This could allow the process of issuing truck permits to be based on a chosen probability of exceedance. Results indicate that the Class 9 truck statistics can be used to represent the extreme load effects associated with all truck classes/groups combined.