A new journal paper, titled “A comprehensive probabilistic model of traffic loads based on Weigh-In-Motion data for applications to bridge structures” was recently published in KSCE Journal of Civil Engineering. The paper was co-authored by Mr. Jihwan Kim (Ph.D. student, SSRG) and Prof. Junho Song (Research advisor, SSRG).
The permanent link via DOI number of the paper is https://doi.org/10.1007/s12205-019-2432-9. The full reference information is
Kim, J., and J. Song* (2019). A comprehensive probabilistic model of traffic loads based on Weigh-In-Motion data for applications to bridge structures. KSCE Journal of Civil Engineering. Vol. 23(8), 3628-3643.
This paper develops a comprehensive probabilistic traffic load model based on weigh-in-motion (WIM) data collected from three highway sites in South Korea for accurate estimations of the traffic load effects on bridges. To simulate the traffic flow on a bridge by a Monte Carlo simulation approach, essential key random variables representing the site-specific conditions of traffic environments of the bridge are identified and incorporated into the model based on probabilistic studies and theories of transportation engineering. Additionally, a simple method is proposed to take into account the interaction between multiple lanes. The developed traffic load model was initially verified in terms of the total load on general types and lengths of bridges (short and long-span). Next, this paper estimated the long-term traffic load effects on the Incheon bridge using its influence lines. The 100- and 75-year maximum traffic load effects (tension of cable, moment of girder) were estimated by an extrapolation process and compared with the design loads of two design codes (KHBDC-Cable bridge, AASHTO HL-93). The estimated traffic load effects were significantly lower than those by the design code, which appears to confirm a high level of conservatism introduced by multiple presence factors
ABSTRACT: In various efforts to assure safety and serviceability of a bridge structure throughout its lifetime, it is essential to accurately estimate the traffic load effects. Although traffic loads involve large uncertainties and can vary significantly with site-specific traffic environments, bridge design codes and maintenance strategies do not utilize a probabilistic model that can reflect the actual environments and uncertainties of the target bridge. Rapid developments of weigh-in-motion (WIM) technologies now make it possible to collect various types of data describing the characteristics of vehicles and traffic patterns. Based on actual WIM data collected in South Korea, this paper develops a comprehensive probabilistic model describing the characteristics of vehicles and traffic flow so that the traffic load effects of a target bridge can be assessed using a Monte Carlo simulation approach. To describe the characteristics of vehicles and traffic flow in the WIM data, several important random variables are first identified. These key random variables are then incorporated into a comprehensive probabilistic model based on fitted probability distributions and theories of transportation engineering. The developed model is successfully verified by comparing the daily maximum total loads estimated using actual WIM data with those estimated using artificial WIM data generated from the model. Furthermore, bridge traffic load effects, e.g., moment and tension, are estimated using the influence lines of an actual cable-stayed bridge in South Korea (the Incheon Bridge) and are compared with those from the live load model of a design code. Finally, a brief parametric study is performed to explore the possibility that a probabilistic model developed by the proposed approach can be used as a generic probabilistic traffic load model capable of estimating the site-specific traffic loads through customizations based on partial measurements and available information regarding the target bridge.