This paper investigates the phenomenon of growth in truck volumes during the lifetime of a bridge and the influence of that growth on characteristic maximum load effects. The study uses Weigh-in-Motion (WIM) data from the Netherlands to calibrate Monte Carlo simulation of load effects on a range of bridge spans. For short spans, the distribution of 25-day maximum data is Weibull. As span increases, a better fit is obtained with a mixture that separates low loader vehicles from all others. Growth is addressed by assuming constant, linear or quadratic variations in the properties of the best-fit Generalized Extreme Value distributions. The principle of parsimony is used to select the most appropriate fit. Growth is shown to change the nature of the trend on probability paper, shifting the curves to the right. While the influence of growth is relatively modest, fitting non-stationary data to a stationary curve gives erroneous results.

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