Font Size: a A A

Predicting flexible pavement deterioration for pavement management systems

Posted on:2004-09-24Degree:Ph.DType:Dissertation
University:University of KentuckyCandidate:Wang, YuhongFull Text:PDF
GTID:1462390011970800Subject:Engineering
Abstract/Summary:
The importance of highways in modern transportation systems cannot be overstated. Pavements are one of the major subsystems of the highway systems. Today, pavement management systems have been increasingly employed by many state agencies to assist in highway pavement management. One of the key components of a pavement management system, which is also the most challenging part, is the pavement deterioration prediction models. Over years, numerous studies have been performed to investigate the relationship between pavement deterioration and its influencing factors. However, pavement deterioration models are still immature due to the complexity of this subject, lack of a comprehensive research dataset to support model development and verification, and inadequate data analysis approaches.; The Long-term Pavement Performance (LTPP) program---established as part of the Strategic Highway Research Program (SHRP) and now managed by the Federal Highway Administration (FHWA)---is a major undertaking to address the pavement research data problem. The program continually conducts field experiments by monitoring more than 2,400 asphalt and Portland cement concrete pavement test sections across the U.S. and Canada. This research used the data provided by the LTPP Information Management System (IMS) to predict flexible pavement deteriorations using various performance indicators and influencing factors. The flexible pavement performance indictors used in this research include deflections measured by falling weight deflectometers (FWD), pavement roughness defined by the International Roughness Index (IRI), fatigue cracking, and pavement rutting. Various environmental, traffic, and structural factors were used to estimate or predict these performance indicators.; To investigate the Surface Curvature Index (SCI) and Base Curvature Index (BCI) calculated from FWD, linear models using panel data analysis approaches were developed. For predicting pavement roughness, linear models and a dynamic model were developed. For predicting pavement fatigue cracking, a survival analysis was conducted. Finally, a dynamic model was developed to predict pavement rut depth. The individual change patterns of major flexible pavement performance indicators and influencing factors were also investigated in this research.
Keywords/Search Tags:Pavement, Systems, Influencing factors, Performance indicators, Major, Predict, Highway
Related items