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Development of a Stochastic Model of Pavement Crack Initiation

机译:路面裂纹萌生随机模型的建立

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摘要

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.
机译:路面开裂模型为路面设计和管理提供了有用的开裂开始和发展预测。路面开裂是一个高度可变的事件。路面开裂起始性确定性模型的广泛使用具有固有的问题,因为这些模型不能提供有关开裂起始时间变化性的信息。建模路面开裂的另一个常见问题是对数据审查的不当处理。数据收集调查通常是有限的。因此,一些路面在勘测开始之日就已经开裂了。其他人将在调查期间开裂,而其他人只会在调查结束后才这样做。如果未适当考虑开裂起始时间的检查,则该模型可能会遭受统计偏差。本文对AASHO道路测试期间收集的路面开裂数据进行了分析。该分析基于随机持续时间建模技术的使用。工期模型可以表示路面开裂的随机性,也可以将审查数据纳入模型参数的统计估计中。本文给出的结果表明,开裂起始模型可以很好地拟合数据,参数估计具有正确的符号和相对大小,并且与原始AASHO模型相比,模型的预测更为准确。

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