Abstract
Instrumentation embedded in pavements is increasingly being used to measure the critical responses and monitor performance of specially-constructed experimental pavement sections or in-service pavements under controlled wheel loading or live traffic. On the other hand, nondestructive tests (NDT), such as falling weight deflectometer (FWD) testing, are routinely performed to evaluate pavement layer structural properties based on deflections measured on the surface of the pavements. In cases where measurements from the pavement surface only are not sufficient to infer pavement layer modulus values, e.g. rolling wheel deflectometer (RWD) tests typically with only one deflection measurement or complex geometries, a procedure that combines measurements from the embedded instruments and surface deflections would provide an alternative to the traditional backcalculation of pavement layer moduli. This study presents an inverse analysis procedure integrating finite element (FE) models and a population-based optimization technique, Covariance Matrix Adaptation Evolution Strategy (CMA-ES), to determine the pavement layer structural properties. Tests using a lightweight deflectometer (LWD) were conducted on instrumented three-layer scaled flexible pavement test sections. The time histories of the LWD load, surface deflection underneath the LWD load, subgrade deflection and vertical stress were recorded and used in the inverse analysis. While the common practice in backcalculating pavement layer properties still assumes a static FWD load and makes use of only peak values of the load and deflections, dynamic analysis was conducted to simulate the impulse LWD load. Results of the inverse analysis show that consistent pavement layer properties can be obtained based on the LWD surface deflection data and measurements of the embedded instrumentation.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: International journal of pavement research and technology
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.