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Modeling Extreme Traffic Loading On Bridges Using Kernel Density Estimators, Cathal Leahy, Eugene J. Obrien, Bernard Enright
Modeling Extreme Traffic Loading On Bridges Using Kernel Density Estimators, Cathal Leahy, Eugene J. Obrien, Bernard Enright
Conference papers
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
Modelling Of Highway Bridge Traffic Loading: Some Recent Advances, Bernard Enright, Colin C. Caprani, Eugene J. Obrien
Modelling Of Highway Bridge Traffic Loading: Some Recent Advances, Bernard Enright, Colin C. Caprani, Eugene J. Obrien
Conference papers
The accurate estimation of site-specific lifetime extreme traffic load effects is an important element in the cost-effective assessment of bridges. In recent years, the improved quality and increasing use of weigh-in-motion technology has meant that better quality and larger databases of vehicle weights are now available. This has enabled measurements of the regular occurrence of extremely heavy vehicles, with weights in excess of 100 t. The collected measurements have been used as the basis for building and calibrating a Monte Carlo simulation model for bridge loading. The computer programs written to implement this model generate simulated traffic in two lanes …