Sampietrini stone pavements: Distress analysis using pavement condition index method

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Abstract

In several Italian cities, it is possible to find historical pavements such as the Sampietrini pavements, which are mainly located in the center of the city of Rome. The Sampietrini pavement is a particular road surface paved in natural stone with irregular sharp elements that are assembled by hand with the evident not plan effect. Because of their peculiarities, they are not suitable for streets where high speed is allowed. In many cases, high vibration and noise levels due to road traffic traveling on Sampietrini pavements are caused by inadequate maintenance, which is also affected by the absence of specific evaluation criteria regarding surface conditions and performances of Sampietrini pavements. It is not possible, in fact, to adopt common approaches developed to be used for flexible and rigid pavements, because they present completely different features and distresses. In this paper, to overpass this problem, a new evaluation criterion based on Pavement Condition Index (PCI) method established for block pavements is proposed. Furthermore, to fully characterize this kind of pavements, other analyses, i.e., International Roughness Index (IRI) and comfort level evaluation based on ISO 2631 standard, were also carried out. The results showed a good correlation between PCI and IRI approaches (R2 = 0.82), also highlighting that new or reconstructed Sampietrini pavements present not negligible roughness level. This aspect was also confirmed estimating the comfort level perceived by users traveling at several speeds (≤50 km/h). Finally, speed related threshold values to be adopted for PCI and IRI methods are proposed. The proposed method can be implemented by pavement managers in a PMS ad hoc for stone block paving and thus, it can be integrated with other equivalents methods of visual inspection based on PCI.

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Zoccali, P., Loprencipe, G., & Galoni, A. (2017). Sampietrini stone pavements: Distress analysis using pavement condition index method. Applied Sciences (Switzerland), 7(7). https://doi.org/10.3390/app7070669

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