Deflection analysis of long-span girder bridges under vehicle bridge interaction using cellular automaton based traffic microsimulation.

Deflection is a crucial indicator to reflect the operating condition of girder bridges, which can be used to evaluate structure condition and identify abnormal loading. The paper analyzed the deflection characteristics of long-span girder bridges based on the coupling vibration between stochastic traffic stream and bridge. First, the latest research advances were integrated to form an analytical model of the coupling vibration between stochastic traffic stream and bridge. Then, a generalized Pareto distribution model based on peaks-over-threshold theory was established to predict the extreme girder deflection. Next, a cellular automaton based microsimulation method was proposed to model the traffic loads on bridges, which utilized the intelligent driver car-following model and acceptance distance based lane-changing model. Finally, these theories were applied in the case study of a long-span prestressed concrete continuous girder bridge. It is discovered from the study that, under the coupling vibration between stochastic traffic stream and bridge, the predicted extreme deflection of the case bridge is far lower than the specified design value. Hence, a grading warning model was established and employed to the analysis of deflection monitoring data of the bridge, showing a wide potential prospect of application.

[1]  Colin Christopher Caprani,et al.  An efficient approach for traffic load modelling of long span bridges , 2019 .

[2]  Gary Klein,et al.  Excessive Deflections of Record-Span Prestressed Box Girder , 2010 .

[3]  Jun Xie,et al.  Review of Study of Long-term Deflection for Long Span Prestressed Concrete Box-girder Bridge* , 2007 .

[4]  Lin Ye,et al.  Sensitivity of fundamental mode shape and static deflection for damage identification in cantilever beams , 2011 .

[5]  Eugene J. O'Brien,et al.  Characteristic Dynamic Increment for Extreme Traffic Loading Events on Short and Medium Span Highway Bridges , 2010 .

[6]  Seng Tjhen Lie,et al.  Damage detection method based on operating deflection shape curvature extracted from dynamic response of a passing vehicle , 2013 .

[7]  Huizhao Tu,et al.  An improved cellular automaton with axis information for microscopic traffic simulation , 2017 .

[8]  Yi-Qing Ni,et al.  Technology developments in structural health monitoring of large-scale bridges , 2005 .

[9]  Eugene J. O'Brien,et al.  Monte Carlo simulation of extreme traffic loading on short and medium span bridges , 2013 .

[10]  Dirk Helbing,et al.  Enhanced intelligent driver model to access the impact of driving strategies on traffic capacity , 2009, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[11]  Masaki Sekiguchi,et al.  Dynamics of an ultra-discrete SIR epidemic model with time delay. , 2018, Mathematical biosciences and engineering : MBE.

[12]  J.W. LEE,et al.  HEALTH-MONITORING METHOD FOR BRIDGES UNDER ORDINARY TRAFFIC LOADINGS , 2002 .

[13]  Jan Ming Ko,et al.  Fatigue damage model for bridge under traffic loading: application made to Tsing Ma Bridge , 2001 .

[14]  Colin Christopher Caprani,et al.  Long-span bridge traffic loading based on multi-lane traffic micro-simulation , 2016 .

[15]  Qiang Yu,et al.  Excessive Long-Time Deflections of Prestressed Box Girders. I: Record-Span Bridge in Palau and Other Paradigms , 2012 .

[16]  C. S. Cai,et al.  Equivalent Wheel Load Approach for Slender Cable-Stayed Bridge Fatigue Assessment under Traffic and Wind: Feasibility Study , 2007 .

[17]  Hans Beushausen,et al.  Durability, service life prediction, and modelling for reinforced concrete structures – review and critique , 2019, Cement and Concrete Research.

[18]  Nasim Uddin,et al.  Drive-by bridge damage monitoring using Bridge Displacement Profile Difference , 2016 .