Now showing 1 - 9 of 9
  • Publication
    The Influence of Correclation on the Extreme Traffic Loading of Bridges
    Accurate traffic loading models based on measured data are essential for the accurate assessment of existing bridges. There are well-established methods for the Monte Carlo simulation of single lanes of traffic, and this can easily be extended to model the loading on bridges with two independent streams of traffic in opposing directions. However, a typical highway bridge will have multiple lanes in the same direction, and various types of correlation are evident in measured traffic. This paper analyses traffic patterns using multi-lane WIM data collected at two European sites. It describes an approach to the Monte Carlo simulation of this traffic which applies variable bandwidth kernel density estimators to empirical traffic patterns of vehicle weights, gaps and speeds. This method provides a good match with measured data for multi-truck bridge loading events, and it is shown that correlation has a small but significant effect on lifetime maximum load effects.
      222
  • Publication
    Probabilistic study of lifetime load effect distribution of bridges
    Assessment of highway bridge safety requires a prediction of the probability of occurrence of extreme load effects during the remaining life of the structure. While the assessment of the strength of an existing bridge is relatively well understood, the traffic loading it is subject to, has received less attention in the literature. The recorded traffic data are often limited to a number of days or weeks due to the cost of data collection. Studies in the literature have used many different methods to predict the lifetime maximum bridge load effect using a small amount of data, including fitting block maximum results to a Weibull distribution and raising maximum daily or maximum weekly distributions to an appropriate power. Two examples are used in this study to show the importance of the quantity of data in predicting the lifetime maximum distribution. In the first, a simple example is used for which the exact theoretical probabilities are available. Hence, the errors in estimations can be assessed directly. In the second, ‘long-run’ simulations are used to generate a very large database of load effects from which very accurate estimates can be deduced of lifetime maximum effects. Results are presented for bidirectional traffic, with one lane in each direction, based on Weigh-in-Motion data from the Netherlands.
      252
  • Publication
    Using Weigh-in-Motion Data to Determine Aggressiveness of Traffic for Bridge Loading
    (American Society of Civil Engineers, 2013-03) ;
    This paper presents results based on the analysis of an extensive database of weigh-in-motion (WIM) data collected at five European highway sites in recent years. The data are used as the basis for a Monte Carlo simulation of bridge loading by two-lane traffic, both bidirectional and in the same direction. Long runs of the simulation model are used to calculate characteristic bridge load effects (bending moments and shear forces), and these characteristic values are compared with design values for bridges of different lengths as specified by the Eurocode for bridge traffic loading. Various indicators are tested as possible bases for a bridge aggressiveness index to characterize the traffic measured by the WIM data in terms of its influence on characteristic bridge load effects. WIM measurements can thus be used to determine the aggressiveness of traffic for bridges. The mean maximum weekly gross vehicle weight is proposed as the most effective of the indicators considered and is shown to be well correlated with a wide range of calculated characteristic load effects at each site.
    Scopus© Citations 79  884
  • Publication
    Modelling of Highway Bridge Traffic Loading: Some Recent Advances
    The accurate estimation of site-specific lifetime extreme traffic load effects is an important element in the cost-effective assessment of bridges. In recent years, the improved quality and increasing use of weigh-in-motion technology has resulted in better quality and larger databases of vehicle weights. This has enabled measurements of the regular occurrence of extremely heavy vehicles, with weights in excess of 100 t. The collected measurements have been used as the basis for building and calibrating a Monte Carlo simulation model for bridge loading. The computer programs written to implement this model generate simulated traffic in two lanes – for both the same direction and the bidirectional cases – and calculate load effects for bridges of various spans. The research focuses on free-flowing traffic on short to medium-span bridges. This paper summarizes recent advances and their contribution to the highway bridge traffic loading problem.
      210
  • Publication
    Management Strategies for Special Permit Vehicles for Bridge Loading
    An examination of weigh-in-motion (WIM) data collected recently at sites in five European countries has shown that vehicles with weights well in excess of the normal legal limits are found on a daily basis. These vehicles would be expected to have special permits issued by the responsible authorities. It can be seen from the WIM measurements that most of them are travelling at normal highway speeds (around 80 km/h). Photographic evidence indicates that, while many are accompanied by an escort vehicle in front and/or behind, normal traffic is flowing alongside in other lanes of the highway. As European freight volume grows, the frequency of these special vehicles can be expected to increase. Hence, the probability of them meeting a heavy truck travelling in the opposite direction on a bridge also increases. Gross vehicle weights in excess of 100 t have been observed at all sites, and are a daily occurrence in the Netherlands. Most of these extremely heavy vehicles are either mobile cranes or low loaders carrying construction equipment. Both types have multiple axles at very close spacing, and the gross weight and axle layout have implications for bridge loading. This paper presents findings based on a simulation model which incorporates the load effects for all observed truck types on short to medium span bridges. It is evident that special vehicles govern the lifetime maximum bridge loading, and the occurrence of extremely heavy trucks is sufficiently frequent that meeting events can be expected during the design lives of the bridges. The effects of different management strategies for special permit vehicles are modelled and the results are presented.
      121
  • Publication
    Non-Linear Response of Structures to Characteristic Loading Scenarios
    To assess the safety of an existing bridge, the traffic loads to which it may be subjected in its lifetime need to be accurately quantified. In this paper the 75 year characteristic maximum traffic load effects are found using a carefully calibrated traffic load simulation model. To generate the bridge loading scenarios, an extensive weigh in motion (WIM) database, from three different European countries, is used. Statistical distributions for vehicle weights, inter-vehicle gaps and other characteristics are derived from the measurements, and are used as the basis for Monte Carlo simulations of traffic representing many years. An advantage of this “long-run” simulation approach is that it provides information on typical extreme traffic loading scenarios. This makes possible a series of nonlinear finite element analyses of a reinforced concrete bridge to determine the response to typical characteristic maximum loadings.
      238
  • Publication
    Monte Carlo simulation of extreme traffic loading on short and medium span bridges
    (Informa UK (Taylor & Francis), 2013-12) ;
    The accurate estimation of site-specific lifetime extreme traffic load effects is an important element in the cost-effective assessment of bridges. A common approach is to use statistical distributions derived from weigh-in-motion measurements as the basis for Monte Carlo simulation of traffic loading. However, results are highly sensitive to the assumptions made, not just with regard to vehicle weights but also to axle configurations and gaps between vehicles. This paper presents a comprehensive model for Monte Carlo simulation of bridge loading for free-flowing traffic and shows how the model matches results from measurements on five European highways. The model has been optimised to allow the simulation of many years of traffic and this greatly reduces the variance in calculating estimates for lifetime loading from the model. The approach described here does not remove the uncertainty inherent in estimating lifetime maximum loading from data collected over relatively short time periods.
      792Scopus© Citations 109
  • Publication
    The Effect of Lane Changing on Long-Span Highway Bridge Traffic Loading
    Maximum loading on long-span bridges typically occurs in congested traffic conditions. As traffic becomes congested car drivers may change lane, increasing the tendency for trucks to travel in platoons. For long-span bridges this phenomenon may increase the regularity and severity of bridge repair programs, with potential significant associated costs. This research investigates the effect of lane changing by car drivers on bridge loading. A Monte Carlo simulation model in which individual car drivers probabilistically decide, based on a lane-changing bias probability, whether or not to change lane has been developed. The sensitivity of bridge loading to this factor is investigated for different bridge lengths and traffic compositions. This research concludes that the lane-changing behavior of car drivers has an effect on bridge loading for long-span bridges, and the magnitude of this effect is quite sensitive to the percentage of trucks in the traffic.
      388
  • Publication
    Estimation of lifetime maximum distributions of bridge traffic load effects
    This paper considers the problem of assessing traffic loading on road bridges. A database of European WIM data is used to determine accurate annual maximum distributions of load effect. These in turn are used to find the probability of failure for a number of load effects. Using the probability of failure as the benchmark, traditional measures of safety – factor of safety and reliability index – are reviewed. Both are found to give inconsistent results, i.e., a given factor of safety or reliability index actually corresponds to a range of different probabilities of failure
      549