Moisture - Introduction

While asphalt layers are heavily affected by temperature, the resilient and permanent behaviour of granular materials are a function of moisture content. A model, therefore, has to be provided to simulate how moisture varies in the pavement and how this affects the performance of the granular layers.

The moisture model presented hereafter is what is used in the ME-PDG, which seems to be most suitable thanks to its simplicity and flexibility. This approach takes into account the effect of moisture by multiplying the resilient modulus of the granular material at optimum moisture content by an environmental factor F_env, which can assume the three forms F_f (for frozen material), F_r (for thawing material) or F_u (for unfrozen material). These factors are function of the moisture content, which is calculated by means of a Soil-Water Characteristic Curve that defines, for a particular material, the relationship between suction and degree of saturation.

In general, water table and moisture contents are considered constant throughout the year if there is no water infiltration into the pavement layers. Nonetheless, there can be cases when the moisture content distribution changes, such as the appearance of full depth cracks or the bursting of a pipe. These are considered very traumatic events for a pavement and it can be very important to simulate how and when they might take place and the amount of damage they might cause. In order to take into account this type of events, a variably saturated flow model is also presented in this paper that allows estimating how moisture content might evolve in different case scenarios. This model is implements the two-dimensional finite difference algorithm discussed by Clement et al. and requires each time step to be solved iteratively by means of a Picard iteration, where each iteration consists in solving a system of linear equations.

Coupling this transient flow model with the F_env approach from the ME-PDG it is possible to estimate the mechanical properties of the granular layers for the critical cases discussed above, enabling the software to consider the presence of weak spots along the pavement that can lead to premature failure.

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