Identifying critical clusters of traffic-loading events in recurrent congested conditions on a long-span road bridge

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Abstract

This paper examines the nature of traffic loading in recurrent congested traffic conditions on a long-span suspension bridge. Traffic flow and percentage of trucks are extracted from image data and a cluster analysis performed to classify the data into four clusters. One cluster (MTHF, medium truck percentage and high flow) is identified that incorporates almost 50% of the hours of traffic data scattered throughout the day. Site-specific load assessment confirms that this MTHF cluster is the most critical for the bridge considered, the Forth Road Bridge in Scotland. For non-recurrent congestion, another cluster (HTLF, high percentage of trucks and low flow) is shown to govern but this finding is highly site-specific, depending on the relative frequency of the different types of congestion. A comparison of the maximum hourly/daily MTHF load effect of the cable force for five notional bridges shows that a 100% increase in the bridge span generates an increase of about 65% in the characteristic load effect.

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APA

Micu, E. A., O’Brien, E. J., Malekjafarian, A., McKinstray, R., Angus, E., Lydon, M., & Catbas, F. N. (2020). Identifying critical clusters of traffic-loading events in recurrent congested conditions on a long-span road bridge. Applied Sciences (Switzerland), 10(16). https://doi.org/10.3390/APP10165423

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