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Title: Reliability in pavement design
Author: Dalla Valle, Paola
ISNI:       0000 0004 5358 5786
Awarding Body: University of Nottingham
Current Institution: University of Nottingham
Date of Award: 2015
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This research presents a methodology that accounts for variability of key pavement design input variables and variations due to lack-of-fit of the design models and assesses effects on pavement performance (fatigue and deformation life). Variability is described by statistical terms such as mean and standard deviation and by its probability density distribution. The subject of reliability in pavement design has pushed many highway organisations around the world to review their design methodologies to evaluate the effect of variations in materials on pavement performance. This research has reinforced this need for considering the variability of design parameters in the design procedure and to conceive a pavement system in a probabilistic way, similar to structural designs. This study has only considered flexible pavements. The sites considered for the analysis, all in the UK (including Northern Ireland), were mainly motorways or major trunk roads. Pavement survey data analysed were for Lane 1, the most heavily trafficked lane. Sections 1km long were considered wherever possible. Statistical characterisation of the variation of layer thickness, asphalt stiffness and subgrade stiffness input parameters is addressed. A model is then proposed which represents an improvement on the Method of Equivalent Thickness for the calculation of strains and life for flexible pavements. The output is a statistical assessment of the estimated pavement performance. The proposed model to calculate the fatigue and deformation life is very fast and simple, and is well suited to use in a pavement management system where stresses and strains must be calculated millions of times. The research shows that the parameters with the greatest influence on the variability of predicted fatigue performance are the asphalt stiffness modulus and thickness. The parameters with the greatest influence on the variability of predicted deformation performance are the granular subbase thickness, the asphalt thickness and the subgrade stiffness.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: TE Highway engineering. Roads and pavements