A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Hierarchical Markov Chain Monte Carlo Simulation for Modeling Transverse Cracks in Highway Pavements
Transverse cracks are distresses whose initiation and propagation affect the stability and structural integrity of the highway pavement. They are caused by load, moisture, temperature, construction defects, or a combination of these. Cracking leads to inherent pavement defects that are exacerbated by moisture infiltration as well as the formation of other pavement distresses like roughness with their attendant problems to roadway agencies and users. One feature of transverse cracks is the spontaneity of their initiation and the uncertainty of their propagation. As a result, modeling the formation and spread of transverse cracks requires a framework within which uncertainty can be expressed explicitly. This research seeks to use a statistical approach to model the propagation of transverse cracks on road pavements in Delaware. The aim is to investigate how hierarchical Markov-chain Monte Carlo (MCMC) simulation performs in estimating and predicting the spread of transverse cracks without neglecting their associated uncertainty. Hierarchical MCMC models use the Bayesian approach, which accounts for uncertainty in pavement distresses.
Hierarchical Markov Chain Monte Carlo Simulation for Modeling Transverse Cracks in Highway Pavements
Transverse cracks are distresses whose initiation and propagation affect the stability and structural integrity of the highway pavement. They are caused by load, moisture, temperature, construction defects, or a combination of these. Cracking leads to inherent pavement defects that are exacerbated by moisture infiltration as well as the formation of other pavement distresses like roughness with their attendant problems to roadway agencies and users. One feature of transverse cracks is the spontaneity of their initiation and the uncertainty of their propagation. As a result, modeling the formation and spread of transverse cracks requires a framework within which uncertainty can be expressed explicitly. This research seeks to use a statistical approach to model the propagation of transverse cracks on road pavements in Delaware. The aim is to investigate how hierarchical Markov-chain Monte Carlo (MCMC) simulation performs in estimating and predicting the spread of transverse cracks without neglecting their associated uncertainty. Hierarchical MCMC models use the Bayesian approach, which accounts for uncertainty in pavement distresses.
Hierarchical Markov Chain Monte Carlo Simulation for Modeling Transverse Cracks in Highway Pavements
Mills, Leslie N. O. (author) / Attoh-Okine, Nii O. (author) / McNeil, Sue (author)
Journal of Transportation Engineering ; 138 ; 700-705
2011-12-12
62012-01-01 pages
Article (Journal)
Electronic Resource
English
Hierarchical Markov Chain Monte Carlo Simulation for Modeling Transverse Cracks in Highway Pavements
| Online Contents | 2012
Detection of Cracks on Highway Pavements
| NTIS | 1983
Analysis of ground penetrating radar data using hierarchical Markov Chain Monte Carlo simulation
| British Library Online Contents | 2014
Location of Subsurface Cracks in Highway Pavements
| British Library Conference Proceedings | 1995
The Transverse Propagation of Cracks in Pavements
| British Library Conference Proceedings | 1994