Nondestructive Evaluation of Pavement Structural Condition for Rehabilitation Design

2016Final reportPDFTech ReportUTRC/RF Grant No: 49997-28-2549997-28-25DeflectionDelaminationFalling weight deflectometersFinite element methodNondestructive testsPavement maintenancePavement performanceStructural analysisPavement evaluationfalling weight deflectometerfinite element modeldynamic analysismaterial propertieslayer interfaceboundary conditionsResearch HubUnited StatesCity University of New York. University Transportation Research CenterWang, HaoLi, MaoyunRutgers University. Department of Civil & Environmental EngineeringCity University of New York. University Transportation Research CenterUnited States. Federal Highway AdministrationUnited States. Dept. of Transportation. Office of the Assistant Secretary for Research and TechnologyUniversity Transportation Centers Program (U.S.)US Transportation CollectionFalling Weight Deflectometer (FWD) is the common non-destructive testing method for in-situ evaluation of pavement condition. This study aims to develop finite element (FE) models that can simulate FWD loading on pavement system and capture the complexity in material properties, layer interface, and boundary conditions. Parametric analysis was conducted considering the effects of dynamic analysis, temperature gradient, bedrock depth, asphalt layer delamination, viscoelasticity, and unbound material nonlinearity on pavement surface deflections and critical strain responses. Although the parametric analysis findings vary depending on the specific pavement response, the study results illustrate the appropriate selection of analysis type, constitutive models of pavement material, and layer boundary conditions on the accuracy of FE modeling results. In particular, the analysis findings show that delamination in asphalt layers induces the greater strain responses; while neglecting bedrock effect overestimates surface deflections. The developed FE models can directly benefit the use of FWD testing for in-situ pavement condition evaluation, such as pavement performance prediction and/or backcalculation of layer moduli