Traffic Load Effects on Bridges, Statistical Analysis of Collected and Monte Carlo Simulated Vehicle Data

Abstract: Research in the area of bridge design has been and still isconcentrated on the study of the strength of materials andrelatively few studies have been performed on traffic loads andtheir effects. Traffic loads have usually been assumed to begiven in codes. This is mainly because it is very difficult tomodel traffic loads in an accurate manner because of theirrandomness.In this work, statistical evaluations of traffic loadeffects, obtained from real as well as Monte Carlo (MC)simulated vehicle data, are presented. As the dynamiccontribution of the vehicle load was filtered by the systemused for measuring vehicle weight, no attention was paid in thepresent study to the dynamic effects or the impact factor. Thedynamic contribution of the traffic load models from codes wasdeducted wherever they were compared with the result from theevaluation of the real data. First, the accuracy of thecollected data was investigated. This was done to examine theinfluence of what was most probably unreasonable data on thefinal evaluated results. Subsequently, the MC simulationtechnique, using a limited amount of the collected data, wasused to generate fictitious vehicle data that could representresults from field measurements which would otherwise have tobe recorded under a long period. Afterwards, the characteristictotal traffic loads for bridges with large spans weredetermined by probabilistic analysis. This was done using realas well as simulated data and the two were compared. Theseresults were also compared with the corresponding valuescalculated using the traffic load model from the Swedish bridgedesign code.Furthermore, using traffic data, different load effects onbridges (girder distribution factor of slab-on-girder bridgesand the mid-span deflection as well as the longitudinal stressat critical locations on box-girder bridges) were investigated.The main task was to obtain a more accurate knowledge oftraffic load distributions on bridges as well as their effectsfor infrastructure design. The results showed that the trafficload models from codes gave considerably higher load effectscompared to the current actual traffic load effects. Theseinvestigations were based on the available data for the actualposition of the vehicles on a single bridge and might not coverall possible traffic scenarios. The results showed only how thereal traffic loads, under”normal”conditions andtheir transverse positions relate to the load model accordingto the codes.KEYWORDS:bridge, traffic load, load effect, transversedistribution, characteristic value,weigh in motion, MonteCarlo simulation, Rice’s formula, level crossinghistogram, vehicle queue.