ABSTRACT

Presently, most of the road agencies use Non-Destructive (NDT) tools to help them prioritise pavement maintenance and rehabilitation (M&R) activities at the network level, thus optimising the limited budgetary resources. One of the most widely used NDT techniques for pavement structural evaluations, at the network level assessment, is the Falling Weight Deflectometer (FWD). Using a database comprising of a wide array of typical layer moduli and thicknesses of traditional flexible pavements, that were generated based on multiple Monte Carlo numerical simulations, as a reference datum, this study successfully developed probabilistic models that allow for analysing the condition of a flexible pavement, at the network level, from FWD surface deflection data, namely the Deflection Bowl Parameters (DBPs), to identify which layers of the pavement structure present a probability of structural failure or damage.

摘要

目前，大多数道路机构使用无损 (NDT) 工具来帮助他们优先考虑路面维护和修复 ( M&R)) 网络层面的活动，从而优化有限的预算资源。在网络级评估中，用于路面结构评估的最广泛使用的 NDT 技术之一是落锤挠度计 (FWD)。使用由多个典型层模数和传统柔性路面厚度组成的数据库（基于多个蒙特卡罗数值模拟生成）作为参考数据，本研究成功开发了概率模型，可以分析柔性路面的状况路面，在网络级别，从 FWD 表面变形数据，即变形碗参数 (DBP)，以确定路面结构的哪些层存在结构失效或损坏的可能性。