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A platform for research: civil engineering, architecture and urbanism
Development of a Stochastic Model of Pavement Crack Initiation
Pavement cracking models provide useful predictions of cracking initiation and progression, for purposes of pavement design and management. Pavement cracking initiation is a highly variable event. The widespread use of deterministic models of pavement cracking initiation is inherently problematic, as these models do not provide information on the variability of the cracking initiation times. Another common problem in modeling pavement cracking initiation is the inappropriate treatment of data censoring. Data collection surveys are usually of limited length. Thus, some pavement sections will have already cracked by the day the survey starts; others will crack during the survey period, while others will only do so after the survey is concluded. If the censoring of the cracking initiation times is not accounted for properly, the model may suffer from statistical biases. In this paper, an analysis of the pavement cracking data collected during the AASHO Road Test is presented. The analysis is based on the use of stochastic duration modeling techniques. Duration models enable the stochastic nature of pavement cracking initiation to be represented as well as censored data to be incorporated in the statistical estimation of the model parameters. The results presented in this paper show that the cracking initiation model provides good fit to the data, the parameter estimates have the correct signs and relative magnitudes, and the model predictions are more accurate than those obtained with the original AASHO model.
Development of a Stochastic Model of Pavement Crack Initiation
Pavement cracking models provide useful predictions of cracking initiation and progression, for purposes of pavement design and management. Pavement cracking initiation is a highly variable event. The widespread use of deterministic models of pavement cracking initiation is inherently problematic, as these models do not provide information on the variability of the cracking initiation times. Another common problem in modeling pavement cracking initiation is the inappropriate treatment of data censoring. Data collection surveys are usually of limited length. Thus, some pavement sections will have already cracked by the day the survey starts; others will crack during the survey period, while others will only do so after the survey is concluded. If the censoring of the cracking initiation times is not accounted for properly, the model may suffer from statistical biases. In this paper, an analysis of the pavement cracking data collected during the AASHO Road Test is presented. The analysis is based on the use of stochastic duration modeling techniques. Duration models enable the stochastic nature of pavement cracking initiation to be represented as well as censored data to be incorporated in the statistical estimation of the model parameters. The results presented in this paper show that the cracking initiation model provides good fit to the data, the parameter estimates have the correct signs and relative magnitudes, and the model predictions are more accurate than those obtained with the original AASHO model.
Development of a Stochastic Model of Pavement Crack Initiation
Shin, Hee Cheol (author) / Madanat, Samer (author)
Seventh International Conference on Applications of Advanced Technologies in Transportation (AATT) ; 2002 ; Boston Marriot, Cambridge, Massachusetts, United States
2002-07-31
Conference paper
Electronic Resource
English
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