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Procedia - Social and Behavioral Sciences
Article . 2012 . Peer-reviewed
License: CC BY NC ND
Data sources: Crossref
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Model for the Prediction of Rutting in Roads, a NordFoU Result

Authors: Huvstig, Anders;

Model for the Prediction of Rutting in Roads, a NordFoU Result

Abstract

AbstractRutting in roads is an important factor that affects the performance of a road. A model used to predict future rutting for different design alternatives is important to minimise the investment cost and LCC.In the project “Pavement Performance Models: Part 2, Project Level”, a new road design model, especially used to predict future rutting, has been developed and validated. Together with the European test method, EN 13286-7:2004, and some other standardised test methods, this model has been validated to the actual rutting of eight 10 – 20 year old LTTP roads.During this validation there have been some interesting findings:•The “Shakedown Theory” is valid for real roads, not only for triaxial tests and test roads.•There is a strong connection between rutting, roughness and cracking in these roads.•The most important factor that contributes to rutting in a road is the shear stress level.•It is possible to accurately predict the rutting on a road, if the stress level does not exceed the “Plastic Shakedown Limit”.•With this knowledge it is possible to use a better design method during the whole process.•It is also possible to predict the performance of a road, which should be built with local and/or recycled material, which is not accepted or described in the standard of the country.

Related Organizations
Keywords

Road design, rut prediction, Shakedown Theory

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Average
Top 10%
Average
gold