[1] Sun Lu, Ge Minli, Gu Wenjun, et al. Characterizing uncertainty in pavement performance prediction [J]. Journal of Southeast University (English Edition), 2012, 28 (1): 85-93. [doi:10.3969/j.issn.1003-7985.2012.01.015]

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Characterizing uncertainty in pavement performance prediction()

路面性能预测中不确定性的量化

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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:

28

Issue:

2012 1

Page:

85-93

Research Field:

Traffic and Transportation Engineering

Publishing date:

2012-03-30

Info

Title:

Characterizing uncertainty in pavement performance prediction

路面性能预测中不确定性的量化

Author(s):

Sun Lu¹;  2;  Ge Minli¹;  Gu Wenjun¹;  Xu Bing¹

¹School of Transportation, Southeast University, Nanjing 210096, China
²Department of Civil Engineering, Catholic University of America, Washington DC 20064, USA

孙璐¹;  2;  葛敏莉¹;  顾文钧¹;  徐冰¹

¹东南大学交通学院, 南京210096; ²Department of Civil Engineering, Catholic University of America, Washington DC 20064, USA

Keywords:

-

路面性能;  不确定性;  预测;  蒙特卡洛数值模拟

PACS:

U418.6

DOI:

10.3969/j.issn.1003-7985.2012.01.015

Abstract:

Taking variability and uncertainty involved in performance prediction into account, in order to make the prediction reliable and meaningful, a distribution-based method is developed to predict future PSI. This method, which is based on the AASHTO pavement performance model, treats predictor variables as random variables with certain probability distributions and obtains the distribution of future PSI through the method of Monte-Carlo simulation. A computer program PERFORM using Monte Carlo simulation is developed to implement the numerical computation. Simulation results based on pavement and traffic parameters show that traffic, surface layer material property, and initial pavement performance are the most significant factors affecting pavement performance. Once the distribution of future PSI is determined, statistics such as the mean and the variance of future PSI are readily available.

考虑到路面性能预测中存在的大量可变性和不确定性, 为使得路面性能PSI的预测结果可信且有意义, 提出了一种基于分布的路面性能指标PSI预测方法.该方法建立在AASHTO路面性能预测模型基础上, 把预测变量处理成具有某种概率分布的随机变量, 通过蒙特卡洛数值模拟获得PSI的概率分布.基于路面结构和交通参数建立仿真模型, 应用PERFORM程序得到数值计算结果.研究结果表明:交通荷载、表面层材料特性和路面初始性能是影响未来路面性能的最主要因素.在获得路面性能PSI指标的概率分布后, 其他统计量如未来路面性能的均值函数和方差函数可以很容易得到.

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Memo

Memo:

Biography: Sun Lu(1972—), male, doctor, professor, sunl@ cua.edu.
Foundation items: The US National Science Foundation(No.CMMI-0408390, CMMI-0644552), the American Chemical Society Petroleum Research Foundation(No.PRF-44468-G9), Chang Jiang Scholars Program, the Fok Ying-Tong Education Foundation(No.114024), the Natural Science Foundation of Jiangsu Province(No.SBK200910046), the Postdoctoral Science Foundation of Jiangsu Province(No.0901005C).
Citation: Sun Lu, Ge Minli, Gu Wenjun, et al.Characterizing uncertainty in pavement performance prediction[J].Journal of Southeast University(English Edition), 2012, 28(1):85-93.[doi:10.3969/j.issn.1003-7985.2012.01.015]

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