Now showing 1 - 5 of 5
  • Publication
    A Review of the HL-93 Bridge Traffic Load Model Using an Extensive WIM Database
    (American Society of Civil Engineers, 2014-10) ; ; ;
    HL-93, the current bridge traffic load model used in the United States is examined here. Weigh-in-motion (WIM) data from 17 sites in 16 states containing 74 million truck records are used to assess the level of consistency in the characteristic load effects (LEs) implied by the HL-93 model. The LEs of positive and negative bending moments and shear force are considered on single- and two-lane same-direction slab and girder bridges with a range of spans. It is found that the ratio of WIM-implied LE to HL-93 LE varies considerably from one LE to another. An alternative model is proposed that achieves improvements in consistency in this ratio for the LEs examined, especially for the single-lane case. The proposed model consists of a uniformly distributed load whose intensity varies with bridge length.
      540Scopus© Citations 19
  • Publication
    Validation of Scenario Modelling for Bridge Loading
    (Technika, Vilnius Gediminas Technical University, 2016-09) ; ; ;
    Accurate estimates of characteristic bridge load effects are required for efficient design and assessment of bridges, and long-run traffic simulations are an effective method for estimating the effects. For multi-lane same-direction traffic, truck weights and locations on the bridge are correlated and this affects the calculated load effects. Scenario Modelling is a recently developed method which uses weigh-in-motion (WIM) data to simulate multi-lane same-direction traffic while maintaining location and weight correlations. It has been unclear however whether the method may produce unrealistic driver behaviour when extrapolating beyond the weigh-in-motion measuring period. As weigh-in-motion databases with more than about a year of data are not available, a microsimulation traffic model, which can simulate driver behaviour, is used here to assess the accuracy of extrapolating traffic effects using Scenario Modelling. The microsimulation is used to generate an extended reference dataset against which the results of Scenario Modelling are compared. It is found that the characteristic load effects obtained using Scenario Modelling compare well with the reference dataset. As a result, for the first time researchers and practitioners can model two-lane same-direction traffic loading on bridges while being confident that the approach is generating accurate estimates of characteristic load effects as well as effectively reproducing the complex traffic correlations involved.
      497Scopus© Citations 3
  • 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.
  • 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.
  • Publication
    Portable Bridge WIM Data Collection Strategy for Secondary Roads
    A common method of collecting traffic loading data across a large road network is to use a network of permanent pavement-based WIM systems. An alternative is to use one or more portable Bridge Weigh-In-Motion systems which are moved periodically between bridges on the network. To make optimum use of such a system, a suitable data collection strategy is needed to choose locations for the system. This paper describes a number of possible strategies which the authors have investigated for the National Roads Authority in Ireland. The different strategies are examined and their advantages and disadvantages compared. Their effectiveness at detecting a heavy loading event is also investigated and the preferred approach is identified.