Now showing 1 - 6 of 6
  • Publication
    Calculation of the Dynamic Allowance for Railway Bridges from Direct Measurement
    In a traditional deterministic assessment, a dynamic amplification factor (DAF) is applied to the static loading in order to account for dynamics. The codified DAF values are appropriately conservative in order to consider the wide range of structures and load effects to which they are applied. In the current analysis, a site specific assessment dynamic ratio (ADR) is calculated from direct measurement on an 80 year old steel truss Railway Bridge. The ADR is defined as the ratio of characteristic total stress to the characteristic static stress. The application of ADR is a relatively new concept which has rarely been considered for railway bridges. An assessment performed on the bridge in question showed a decrease in the dynamic allowance when considering the site specific ADR, corresponding to a 26% decrease in calculated stress. The measurements available were also used to derive a robust stochastic model for dynamic allowance which considered the correlation between DAF and stress level. The developed model was applied to a probabilistic assessment and resulted in a 9% increase in reliability.
  • 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
    Evaluation of bridge safety based on Weigh-in-Motion data
    (Civil Engineering Research Association of Ireland, 2016-08-30) ; ; ; ; ;
    This paper investigates various concerns, sensitivities of and correlation between the different parameters influencing the load on a bridge and its resistance to that load. The actual safety, i.e. the probability of failure, is calculated by combining the dead load, Weigh-in-Motion data based traffic load and resistance models. The usefulness of updating the developed bridge safety model using damage indicators from a Structural Health Monitoring system is also examined.
  • 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.
  • 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
    Traffic Load Effect Forecasting for Bridges
    (International Association for Bridge and Structural Engineering, 2015-09-23) ; ;
    Traffic flows, as well as truck weights, increase with time. This must be taken into account in order to accurately assess traffic loading on bridges. The Eurocode Load Model 1 is used for the design of new bridges but a scaled down version of the model can be used for the assessment of existing bridges. This scaling is usually done by applying α–factors to the load model. The effect of traffic growth on these α–factors is assessed in this paper. Weigh-in-motion data from the Netherlands is used as the basis for traffic models which simulate year-on-year growth of both traffic flow and truck weights. A time-varying generalised extreme value distribution is then used to calculate the characteristic load effects and determine the α–factors. The effect of different traffic growth rates on these α–factors is then examined. It is found that an increase in truck weights has the most influence on the α–factors but that increased flow also has a significant effect.