Now showing 1 - 10 of 27
  • Publication
    A Bayesian approach for estimating characteristic bridge traffic load effects
    This paper investigates the use of Bayesian updating to improve estimates of characteristic bridge traffic loading. Over recent years the use Weigh-In-Motion technologies has increased hugely. Large Weigh-In-Motion databases are now available for multiple sites on many road networks. The objective of this work is to use data gathered throughout a road network to improve site-specific estimates of bridge loading at a specific Weigh-In-Motion site on the network. Bayesian updating is a mathematical framework for combining prior knowledge with new sample data. The approach is applied here to bridge loading using a database of 81.6 million truck records, gathered at 19 sites in the US. The database represents the prior knowledge of loading throughout the road network and a new site on the network is simulated. The Bayesian approach is compared with a non-Bayesian approach, which uses only the site-specific data, and the results compared. It is found that the Bayesian approach significantly improves the accuracy of estimates of 75-year loading and, in particular, considerably reduces the standard deviation of the error. With the proposed approach less site-specific WIM data is required to obtain an accurate estimate of loading. This is particularly useful where there is concern over an existing bridge and accurate estimates of loading are required as a matter of urgency.
      177
  • 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
      391
  • Publication
    Study Of Same-Lane And Inter-Lane GVW Correlation
    Extensive work has been done over the last two decades on the simulation of traffic loading on bridges. The methodology used is to generate a number of years of simulated traffic and to use extreme value statistics to predict more accurately the characteristic loading for a given bridge. The parameters and probability distributions used in the Monte Carlo simulation must be based on observed sample traffic data. Many previous studies have assumed that there is no significant correlation between the Gross Vehicle Weights (GVW) of trucks in the same lane, or between trucks in adjacent, same direction lanes. For this paper, an extensive database of Dutch Weigh in Motion data is analysed. Data is collected from two same direction lanes and is time stamped to the nearest 0.01 seconds. The statistical characteristics of this set of data are presented, and various techniques are used to establish the nature and extent of GVW correlation.
      44
  • 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.
      158
  • Publication
    EU FP6 - ARCHES Deliverable D08: Recommendations on the use of results of monitoring on bridge safety assessment and maintenance
    The ARCHES, which is the Specific Targeted Research Project, was planned in response to the European Commission’s call for proposals 3B, addressing Topic 2.6 ‘Design and manufacture of new construction concepts’ of objective ‘Sustainable Surface Transport’ under the Thematic priority 1.6 ‘Sustainable Development, Global Change and Ecosystems’ of the GROWTH part of the Sixth Framework Programme. The contract was signed by the Commission on the 25th of October 2006. Project commencement date was the 1st of September 2006 and the duration of the project is 36 months.
      63
  • Publication
    Estimating characteristic bridge traffic load effects using Bayesian statistics
    This paper investigates the use of Bayesian updating to improve estimates of characteristic bridge traffic loading. Over recent years the use Weigh-In-Motion technologies has increased hugely. Large Weigh-In-Motion databases are now available for multiple sites on many road networks. The objective of this work is to use data gathered throughout a road network to improve site-specific estimates of bridge loading at a specific Weigh-In-Motion site on the network. Bayesian updating is a mathematical framework for combining prior knowledge with new sample data. The approach is applied here to bridge loading using a database of 81.6 million truck records, gathered at 19 sites in the US. The database represents the prior knowledge of loading throughout the road network and a new site on the network is simulated. The Bayesian approach is compared with a non-Bayesian approach, which uses only the site-specific data, and the results compared. It is found that the Bayesian approach significantly improves the accuracy of estimates of 75-year loading and, in particular, considerably reduces the standard deviation of the error. With the proposed approach less site-specific WIM data is required to obtain an accurate estimate of loading. This is particularly useful where there is concern over an existing bridge and accurate estimates of loading are required as a matter of urgency.
      86
  • 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.
      141
  • 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.
      180
  • Publication
    Modelling Extreme Traffic Loading on Bridges Using Kernal Density Estimators
    (Eugenides Foundation, 2011-10-13) ; ;
    Kernel density estimators are a non-parametric method of estimating the probability density function of sample data. In this paper, the method is applied to find characteristic maximum daily truck weights on highway bridges. The results are then compared with the conventional approach.
      131
  • Publication
    Nonlinear Analysis of Isotropic Slab Bridges under Extreme Traffic Loading
    Probabilistic analysis of traffic loading on a bridge traditionally involves an extrapolation from measured or simulated load effects to a characteristic maximum value. In recent years, Long Run Simulation, whereby thousands of years of traffic are simulated, has allowed researchers to gain new insights into the nature of the traffic scenarios that govern at the limit state. For example, mobile cranes and low-loaders, sometimes accompanied by a common articulated truck, have been shown to govern in most cases. In this paper, the extreme loading scenarios identified in the Long Run Simulation are applied to a non-linear, two-dimensional (2D) plate finite element model. For the first time, the loading scenarios that govern in 2D nonlinear analyses are found and compared to those that govern for 2D linear and 1D linear/nonlinear analyses. Results show that, for an isotropic slab, the governing loading scenarios are similar to those that govern in simple one-dimensional (beam) models. Furthermore, there are only slight differences in the critical positions of the vehicles. It is also evident that the load effects causing failure in the 2D linear elastic plate models are significantly lower, i.e. 2D linear elastic analysis is more conservative than both 2D nonlinear and 1D linear/nonlinear.
      245