Now showing 1 - 5 of 5
  • Publication
    Spatially Variable Assessment of Lifetime Maximum Load Effect Distribution in Bridges
    Bridge structures are key components of highway infrastructure and their safety is clearly of great importance. Safety assessment of highway bridges requires accurate prediction of the extreme load effects, taking account of spatial variability through the bridge width and length. This concept of spatial variability i s also known as random field analysis. Reliability - based bridge assessment permits the inclusion of uncertainty in all parameters and models associated with the deterioration process. Random field analysis takes account of the probability that two points n ear each other on a bridge will have correlated properties. This method incorporates spatial variability which results in a more accurate reliability assessm ent. This paper presents an integrated model for spatial reliability analysis of reinforced concre te bridges that considers both the bridge capacity and traffic load. A sophisticated simulation model of two - directional traffic is used to determine accurate annual maximum distributions of load effect. To generate the bridge loading scenarios, an extensi ve Weigh-in-Motion (WIM) database, from five European countries, is used. For this, statistical distributions for vehicle weights, inter - vehicle gaps and other characteristics are derived from the measurements, and are used as the basis for a Monte Carlo simulation of traffic. Results are presented for bidirectional traffic, with one lane in each direction, with a total flow of approximately 2000 trucks per day.
  • 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.
  • 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
  • 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.
  • Publication
    Probability-based assessment of the durability characteristics of concretes manufactured using CEM II and GGBS binders
    (Elsevier, 2012-05) ;
    This paper presents an overview of an investigation into the durability characteristics of blends of GGBS with CEM II/A Portland cements. The introduction of the Emission Trading Scheme has focussed attention on the carbon footprint arising from concrete construction, leading to many countries employing cementitious binder combinations not previously used. In Ireland for example concrete practice has recently changed to allow the addition of GGBS to CEM II/A cements at the concrete mixer, dependent on these blends providing adequate durability. To demonstrate this performance, specific research was conducted into the influence of GGBS addition on resistance to chloride ingress and carbonation, as well as compressive strength. The data from the testing was then used as input parameters for a number of probabilistic models describing chloride and carbonation related deterioration mechanisms. The influence of GGBS content on the expected service life is determined and compared to other research in this area
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