養(yǎng)護(hù)干預(yù)下的瀝青路面平整度預(yù)測
[Abstract]:As a comprehensive index in the performance system, smoothness can not only evaluate the driving quality of pavement, but also provide the basis for maintenance decision. Based on the construction science and technology project of Ministry of Transportation (LAPP) (No. 2014 318223 010), this paper establishes the evolution law of asphalt pavement performance under the intervention of different cross section information and maintenance activities, which provides a realistic basis for determining the maintenance time and the best maintenance scheme in the maintenance planning, and also provides an idea for further perfecting the scientific maintenance planning system. Based on the mechanism analysis of the influencing factors of smoothness and a large number of existing studies, this paper summarizes that the influencing factors of flatness development can be divided into seven categories: pavement disease, road age, traffic load, pavement structure, environment, initial smoothness and maintenance activities. On this basis, combined with the data types in the long-term performance database of asphalt pavement in China, all the data items related to smoothness are extracted, and all the data are preprocessed to complete the reconstruction of asphalt pavement smoothness database. Finally, the statistical method is used to analyze the different detection data and attribute data, and the statistical law and comparative analysis are obtained. The influencing factors are analyzed item by item, and three kinds of cross section information are selected: pavement disease, traffic load and pavement structure as candidate variables for variable analysis, and refined into 11 specific variables. Through the comparative study of factor analysis and cluster analysis, it is determined that SAS statistical analysis software is used to cluster the candidate variables, and finally the input variables of the smoothness prediction model are damage rate, traffic volume and pavement structure index. Through the comparative analysis of various prediction methods and theories, the mixed effect model suitable for panel data modeling is selected as the statistical theoretical basis of the smoothness prediction model. Based on the Logistic model, the nonlinear mixed effect model of the smoothness of the new pavement is established by using the NLMIXED module of SAS. The random effect in the model can reflect the difference of different road sections, and the introduction of covariables into the parameters can not only further explain the differences of each road section, but also improve the fitting accuracy of the model to a certain extent. At the same time, the establishment of the model verifies the applicability of the nonlinear mixed effect model in smoothness prediction, and provides a theoretical basis for the next study of conservation intervention. Finally, based on the nonlinear mixed effect model, the smoothness decay law of asphalt pavement under the intervention of maintenance activities is studied, and the influence of different maintenance measures, leveling value before maintenance and pavement structure index on the evolution law of smoothness after maintenance activities is analyzed. Based on the above analysis, combined with the determination of maintenance threshold, cost-benefit analysis and so on, the asphalt pavement maintenance planning system based on smoothness is put forward.
【學(xué)位授予單位】:東南大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2016
【分類號】:U416.217
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