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首页> 外文期刊>Journal of Transportation Engineering >Efficient Simulation Techniques for Reliability Analysis of Flexible Pavements Using the Mechanistic-Empirical Pavement Design Guide
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Efficient Simulation Techniques for Reliability Analysis of Flexible Pavements Using the Mechanistic-Empirical Pavement Design Guide

机译：机械化-经验性路面设计指南中用于柔性路面可靠性分析的高效仿真技术

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摘要

Many sources of uncertainty are inherent in pavement design. These uncertainties must be incorporated systematically in a reliability analysis to compute their combined effects on the probability of failure of a given pavement structure. Monte Carlo simulation has been the technique of choice in the past to simulate the effects of uncertainties in input parameters on pavement distress and the resultant reliability analyses. The impractical computational time associated with a Monte Carlo scheme, however, has prompted the deferral of the implementation of similar techniques in the current Mechanistic-Empirical Pavement Design Guide (MEPDG). Instead, the reliability analysis implemented in the current MEPDG is performed on the basis of a simple assessment of the overall standard error of the predicted distress compared to the observed distress of the long-term pavement performance (LTPP) sections. It relies on a set of predetermined variability values obtained from a performance database instead of the site-specific input parameters that induce such uncertainty in distress predictions. Past efforts found that techniques (such as the Latin hypercube method) that require a substantially reduced number of simulations compared with Monte Carlo accuracy still suffered from the need for repeated execution of the MEDPG calculations. This study proposes to combine an efficient numerical scheme to conduct statistical simulations with the MEPDG calculations. It makes use of the concept of the representative linear elastic (LE) structure to minimize the number of repeated executions involved in simulations. The numerical scheme can be combined with any simulation technique of random variables to perform a reliability analysis of flexible pavements. The relative merits of Monte Carlo simulation, Latin hypercube simulation, and Rosenblueth's 2K + 1 point-estimate method are compared. The simulations show that the Latin hypercube method is an efficient alternative to the computationally intensive Monte Carlo technique. On the other hand, although Rosenblueth's IK + 1 point-estimate method is much simpler, it is not capable of capturing the important attributes of the distribution of either input or output variables.
机译：路面设计固有的许多不确定性来源。这些不确定性必须系统地纳入可靠性分析中，以计算它们对给定路面结构破坏概率的综合影响。过去，蒙特卡洛模拟已成为一种选择技术，它可以模拟输入参数的不确定性对路面遇险和所产生的可靠性分析的影响。然而，与蒙特卡洛方案相关的不切实际的计算时间促使推迟了当前《机械-经验路面设计指南》（MEPDG）中类似技术的实施。取而代之的是，在当前MEPDG中实施的可靠性分析是基于对预测的遇险与长期路面性能（LTPP）部分的遇险相比的总体标准误差的简单评估而进行的。它依赖于从性能数据库获得的一组预定变异性值，而不是在遇险预测中引起此类不确定性的特定于站点的输入参数。过去的努力发现，与蒙特卡洛精度相比，需要大量减少模拟次数的技术（例如Latin hypercube方法）仍然受到重复执行MEDPG计算的困扰。这项研究建议结合一个有效的数值方案来进行统计模拟与MEPDG计算。它利用代表性的线性弹性（LE）结构的概念来最大程度地减少仿真中涉及的重复执行次数。数值方案可以与随机变量的任何模拟技术结合使用，以对柔性路面进行可靠性分析。比较了蒙特卡洛模拟，拉丁超立方体模拟和Rosenblueth的2K +1点估计方法的相对优点。仿真表明，拉丁超立方体方法是计算密集型蒙特卡洛技术的有效替代方法。另一方面，尽管Rosenblueth的IK + 1点估计方法要简单得多，但它无法捕获输入或输出变量分布的重要属性。

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