Now showing 1 - 4 of 4
  • 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.
  • Publication
    Considering Traffic Growth in Characteristic Bridge Load Effect Calculations
    Traffic volumes and weights increase with time. This is an important consideration in order toaccurately calculate characteristic load effects for the design and assessment of bridges. A modeling approach is presented which can allow for future growth of truck weights and volumes when assessing truck loading on bridges. Weigh-in-motion data from a site in the Netherlands is used as an example to demonstrate traffic growth at that site. In assessing the effect of growth on characteristic load effects, different growth rates for both truck volumes and truck weights are considered. It is found that growth of truck weights has considerablymore influence although growth in truck volumes also has a significant effect.
  • 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
    The Effect of Traffic Growth on Characteristic Bridge Load Effects
    Freight traffic in the European Union is increasing with time. This paper describes a method for considering this growth when assessing traffic loading on bridges and examines the effect of this growth on characteristic load effects. The Eurocode Load Model 1 is used for the design of new bridges. As this model can be overly conservative for the assessment of existing bridges, a scaled down version can be used by applying a–factors to the load model. This is usually done by modelling the traffic loading on the bridge using site-specific weigh-in-motion data and calculating the a–factors in accordance with the results. In this paper, weigh-in-motion data from a site in the Netherlands is used to demonstrate the proposed approach. 40-year simulations of traffic loading are performed on various bridges. The simulations consider year-on-year growth in both the volume and weight of trucks. Time-varying generalized extreme value distributions are then fitted to the simulated data and used to calculate the characteristic load effects. The results are then compared with the load effects generated by Load Model 1 in order to calculate the associated factors. It is found that an increase in truck weights has the most significant influence on the factors but that increased flow also has a significant effect.
      265Scopus© Citations 23