ABSTRACT
Road freight transport in the European Union is expected to grow by about 1.8% until 2030 due to economic growth and an increased flow of freight traffic between member states (Capros et al. 2008). This traffic growth must be considered in order to facilitate the efficient design/assessment of bridges. This paper describes a method for considering this traffic growth when calculating characteristic bridge load effects. It describes work which was performed as part of the CEDR Re-Gen project (www.re-gen.net) to examine this issue.
A traffic simulation approach which can model two-lane same-direction traffic growth is described. Year-on-year growth in both the volumes and weights of heavy vehicles is examined. Weigh-in-motion (WIM) data from a site in the Netherlands is used to demonstrate the approach. 40-year simulations of traffic loading are performed. The simulations consider different annual growth rates for both the volume and weight of trucks. Time-varying generalized extreme value (GEV) distributions – see Figure 1 – are then fitted to the simulated data and used to calculate the characteristic load effects. The traffic modeling approach is based on the method proposed by O’Brien et al. (2014). Time varying GEV distribution. https://s3-euw1-ap-pe-df-pch-content-public-p.s3.eu-west-1.amazonaws.com/9781315207681/cd556cd4-4dcf-4efe-8e29-56fc67b8bfbd/content/fig22_1.tif"/>
Various growth rates are examined and characteristic load effects calculated. The results for each growth rate are compared with the results without growth. Different load effects are examined and hogging moment appears to be the most sensitive of the load effects to traffic growth. It is also found that greater increases in characteristic load effects are evident for the longer bridge lengths. This is likely due to multiple truck presence events being more critical on longer spans.
Overall, growth in truck weights has significantly more influence than growth in flow. This can be seen in Table 1 which shows the average increase in 1000-year load effect across all influence lines examined for each combination of growth rate. Average increase in characteristic 1000-year load effects for each combination of growth.
Annual Flow Growth
0%
1%
2%
Annual
0%
0%
6%
9%
Weight
0.5%
19%
27%
31%
Growth
1%
43%
51%
48%
