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Prediction of Deterioration of Asphalt Pavements by Mechanistic-Empirical Methods
2008-10-23, Belay, Abraham, O'Brien, Eugene J., Collop, Andrew
Cracking of an asphalt layer arises from repeated tensile strains, the maximum value of which typically occurs at the bottom of the layer (particularly for thinner asphalt layers). The crack, once initiated, propagates upwards causing gradual weakening of the structure. The development of a rut arises from the accumulation of permanent strains throughout the structure. A model of pavement damage accumulation, leading to a prediction of pavement life, is described. In addition to pavement damage, the model allows for the spatial repeatability of traffic loading and differences in the progression of damage at different points along the road. The procedure is divided into four main areas: dynamic vehicle simulation; pavement primary response calculation; pavement damage calculation and damage feedback mechanism. The modes of damage that are included in the model are structural rutting and fatigue damage to the asphalt layers. These primary response influence functions are combined with the dynamic tyre forces, to give primary pavement response time histories at a large number of equally spaced discrete points along the pavement. The primary responses are combined with the appropriate pavement damage models and the number of load applications, to predict damage (rutting and fatigue damage) as a function of distance along the pavement for each time increment. An updated surface profile is then generated by subtracting the calculated rutting in the wheel path from the initial profile used for that time increment. This mechanism accounts for the effects of changing surface roughness on the pattern of statistical spatial repeatability and hence the pattern of mean dynamic tyre force. The calculated fatigue damage is used to reduce the stiffness of the asphaltic material for each sub-section. This mechanism reflects the effects of cumulative fatigue damage on the primary responses and hence subsequent pavement damage. The above process is then repeated for many time increments until the pavement has reached the end of its serviceable life. The model gives many insights into the nature of the deterioration process and the changing pattern of spatial repeatability as the profile deforms.
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Truck fleet model for design and assessment of flexible pavements
2008-04, Belay, Abraham, O'Brien, Eugene J., Kroese, Dirk P.
The mechanistic empirical method of flexible pavement design/assessment uses a large number of numerical truck model runs to predict a history of dynamic load. The pattern of dynamic load distribution along the pavement is a key factor in the design/ assessment of flexible pavement. While this can be measured in particular cases, there are no reliable methods of predicting the mean pattern for typical traffic conditions. A simple linear quarter car model is developed here which aims to reproduce the mean and variance of dynamic loading of the truck fleet at a given site. This probabilistic model reflects the range and frequency of the different heavy trucks on the road and their dynamic properties. Multiple Sensor Weigh-in-Motion data can be used to calibrate the model. Truck properties such as suspension stiffness, suspension damping, sprung mass, unsprung mass and tyre stiffness are represented as randomly varying parameters in the fleet model. It is used to predict the statistical distribution of dynamic load at each measurement point. The concept is demonstrated by using a pre-defined truck fleet to calculate a pattern of statistical spatial repeatability and is tested by using that pattern to find the truck statistical properties that generated it.