Heavy rainfall and moisture susceptibility of pavement foundation: A case study coupling finite element method and MnROAD moisture monitoring data

Abstract

The Midwest region, including Minnesota, has been experiencing increased heavy precipitation events due to climate change, and the Minnesota Department of Transportation (MnDOT) is currently investigating the effect of climate change on pavement foundation and other transportation assets. As part of this effort, a study was conducted to investigate the impact of heavy rainfall on pavement foundation performance by focusing on moisture dynamics and resilient modulus changes in the pavement base layer. This study is aimed at understanding the adverse effects of heavy rainfall on moisture fluxes within pavement foundation and corresponding stiffness of the base aggregate layer. A two-step approach was adopted for predicting changes in saturation when estimating corresponding resilient modulus values using the resilient modulus prediction equation employed in AASHTOWare Pavement Mechanistic-Empirical (ME) Design. PLAXIS 3D, a finite-element analysis tool, was utilized to simulate the movement of moisture within the pavement layers under varying heavy rainfall scenarios. By incorporating predicted saturation from PLAXIS 3D simulations into the Pavement ME equation, corresponding resilient modulus values were estimated for the base layer. To ensure its accuracy and reliability, the model was validated using field sensor data from the MnROAD facility. Multiple linear regression models were developed to provide a means for estimating resilient modulus changes due to heavy rainfall. This study highlights the importance of considering moisture effects in pavement design and maintenance in regions prone to heavy rainfall events, and findings can be used by transportation agencies as part of their transportation/geotechnical asset management programs.