2 resultados para Pavement performance.

em Aston University Research Archive


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In Sweden, during recent years, a new type of mixing protocol has been applied, in which the order of mixing is changed from the conventional method. Improved workability and diminished mixing and compaction energy needs have been important drivers for this. Considering that it is the mastic phase, which is modified by changing the mixing order, it provides an interesting case study for explaining the mechanisms of workability in connection with the mastic phase. To do so, an analytical viscosity framework was combined with a mixture morphology framework to upscale to the mixing level and tribology principles to explain the interaction between the mastic and the aggregates. From the mastic viscosity protocol, it was found that the mixing order significantly affects the resulting mastic viscosity. To analyse the effect of this on the workability and resulting mixture performance, X-ray computed tomography was used to analyse mixtures produced by the two different mixing sequences. Mechanical testing was utilised to determine the long-term mechanical performance. In this part of the study, mastic viscosity as a function of particle concentration and distribution was directly coupled to improved mixture workability and enhanced long-term performance.

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The mechanics-based analysis framework predicts top-down fatigue cracking initiation time in asphalt concrete pavements by utilising fracture mechanics and mixture morphology-based property. To reduce the level of complexity involved, traffic data were characterised and incorporated into the framework using the equivalent single axle load (ESAL) approach. There is a concern that this kind of simplistic traffic characterisation might result in erroneous performance predictions and pavement structural designs. This paper integrates axle load spectra and other traffic characterisation parameters into the mechanics-based analysis framework and studies the impact these traffic characterisation parameters have on predicted fatigue cracking performance. The traffic characterisation inputs studied are traffic growth rate, axle load spectra, lateral wheel wander and volume adjustment factors. For this purpose, a traffic integration approach which incorporates Monte Carlo simulation and representative traffic characterisation inputs was developed. The significance of these traffic characterisation parameters was established by evaluating a number of field pavement sections. It is evident from the results that all the traffic characterisation parameters except truck wheel wander have been observed to have significant influence on predicted top-down fatigue cracking performance.