The development of a diagnostic approach to predicting the probability of road pavement failure

Schlotjes, Megan Rose (2013). The development of a diagnostic approach to predicting the probability of road pavement failure. University of Birmingham. Ph.D.

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Road maintenance planning, an essential component of road asset management, preserves the integrity of road networks. Current state of the art pavement management systems exercise optimisation tools, pavement deterioration models, and intervention criteria to forecast the future maintenance requirements of a road network. However, using this current approach to pavement management, uncertainties associated with the failure of individual road sections may not always be accounted for explicitly, and therefore the susceptibility of a road network to failure is unknown.

Predicting the probability of the end of life of a road pavement involves wholly understanding possible modes of failure and utilising suitable computational techniques, so that engineering knowledge can be well represented in data driven models. To this end, this thesis describes the development of a diagnostic approach that infers engineering knowledge into computational models, to quantify the probability and identify the most likely causes of failure of road pavements.

To do so, this research developed a number of failure charts that capture engineering knowledge and present possible failure paths, detailing a set of factors contributing to failure. One technique, based on support vector machines, was identified as the most suitable for this research. The developed prototype system, consisting of a failure system for rutting, fatigue cracking, and shear, performed well in both the development phase and network testing of the system. A case study focusing on rural New Zealand roads was carried out, which demonstrated the use of this tool in network and project level applications.

Type of Work: Thesis (Doctorates > Ph.D.)
Award Type: Doctorates > Ph.D.
College/Faculty: Colleges (2008 onwards) > College of Engineering & Physical Sciences
School or Department: School of Engineering, Department of Civil Engineering
Funders: None/not applicable
Subjects: T Technology > TA Engineering (General). Civil engineering (General)


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