Model to Estimate Pavement Structural Number at Network Level with Rolling Wheel Deflectometer Data

Abstract

Nondestructive testing provides key information about the structural integrity and the capacity of in-service pavements. The rolling wheel deflectometer (RWD) was introduced to support existing nondestructive testing techniques by providing a screening tool for structurally deficient pavements at the network level. The objective of this study was to develop and validate a direct and simple model for determining the pavement structural number (SN) by using RWD deflection data. To achieve this objective, the relationship between the average RWD surface deflection and the peak falling weight deflectometer (FWD) deflection was investigated. The developed model correlated pavement SN with three RWD-measured properties: average and standard deviation of RWD deflection and RWD index. The developed model was fitted to RWD data collected in 16 road sections (each 1.5 mi long), referred to as research sites, in Louisiana. The model was then validated on the basis of data from the FWD and RWD collected on 52 road sections in Louisiana. Results showed agreement between SN calculations obtained from FWD and those from RWD deflection testing. Although the developed model is independent of pavement thickness and layer properties, it provides promising results as an indicator of pavement structural integrity at the network level. The fitting statistics support the use of the proposed model as a screening tool for identifying structurally deficient pavements at the network level.

Assessment of pavement deflection under vehicle loads using a 3D-DIC system in the field

“…Devices for continuous pavement deflection profiling are currently widely used in many projects, because of their performance. However, some of these techniques using moving vehicular loads such as TSD 85 – 87 , RDT 88 , 89 or RWD 90 , 91 generally provide much poorer accuracies (70–250 µm) than those achieved by DIC. Among the most frequently used methods for the continuous pavement deflection profiling, RDD is considered to be one of the most accurate, as employs contact-type loading (with a sinusoidal loading).…”

Improved Statistical Analysis Method Based on Big Data Technology

“…The regression analysis reflects the attribute value of the data in the database, and finds the dependence between the attribute values through the relation between the function and the data mapping [7]. It can be applied to the prediction of the data sequence and the study of the correlation.…”

Enhanced Sensing and Data Processing System for Continuous Profiling of Pavement Deflection

“…In order to continuously measure pavement deflections at higher speeds, extensive efforts have been carried out over the past decades. The continuous deflection measurement technologies currently in use are the Traffic Speed Deflectograph (TSD) [1,2,3,4,5], Rolling Wheel Deflectometer (RWD) [6,7,8,9,10], Quest Integrated/Dynatest Consulting Rolling Weight Deflectometer [11,12], Road Deflection Tester (RDT) [13,14], and the Rolling Dynamic Deflectometer (RDD) [15]. In January 2018, Dynatest Raptor (Rapid Pavement Tester) was introduced to the Transportation Research Board (TRB).…”