Airport Pavement Evaluation based on Falling Weight Deflectometer Measurements

Author(s):  
A.A.H. Sha'ath
2018 ◽  
Vol 2018 (6) ◽  
pp. 32-42
Author(s):  
Juliusz Sołkowski ◽  
Dawid Siemieński

This project is based on search for the method of measuring and evaluation the railway pavement construction. The authors note some analogies between road and railway, both in terms of construction and the dynamic load. Already in the 1960s a method for measuring road pavement deflections under dynamic load was developed using Falling Weight Deflectometer. During years the device and the results analysis method were developed and currently commonly used. The FWD device was adapted for use on railway pavement construction. The first tests were done in the field and have brought reliable results. The device and measuring and pavement evaluation methods are under development.


Author(s):  
A. Samy Noureldin ◽  
Karen Zhu ◽  
Shuo Li ◽  
Dwayne Harris

Nondestructive testing has become an integral part of pavement evaluation and rehabilitation strategies in recent years. Pavement evaluation employing the falling-weight deflectometer (FWD) and ground-penetrating radar (GPR) can provide valuable information about pavement performance characteristics and be a very useful tool for project prioritization purposes and estimation of a construction budget at the network level. Traditional obstacles to the use of the FWD and GPR in pavement evaluation at the network level used to be expenses involved in data collection, limited resources, and lack of simplified analysis procedures. Indiana experience in pavement evaluation with the FWD and the GPR at the network level is presented. A network-level FWD and GPR testing program was implemented as a part of a study to overcome those traditional obstacles. Periodic generation of necessary data will be useful in determining how best to quantify structural capacity and estimate annual construction budgets. Three FWD tests per mile on 2,200 lane-mi of the network is recommended annually for network-level pavement evaluation. The information collected will allow the equivalent of 100% coverage of the whole network in 5 years. GPR data are recommended to be collected once every 5 years (if another thickness inventory is needed) after the successful network thickness inventory conducted in this study. GPR data collection is also recommended at the project level and for special projects. Both FWD and GPR data are recommended to be used as part of the pavement management system, together with automated collection of data such as international roughness index, pavement condition rating, rut depth, pavement quality index, and skid resistance.


Author(s):  
Douglas Steele ◽  
Hyung Suk Lee ◽  
Curt Beckemeyer ◽  
Thomas Van

Traffic speed deflection devices (TSDDs) have been developed since around 2000 to allow for safe and efficient structural evaluation of highway networks. One barrier to TSDD implementation is the inherent differences in deflections produced by moving truck loads and by falling weight deflectometer (FWD), the current deflection testing standard. To better understand the differences in data produced by the two devices, FHWA sponsored research into one particular TSDD, the rolling wheel deflectometer (RWD). The study utilized the finite layer program ViscoWave to model both FWD and RWD loads to demonstrate the effect of their inherent differences on pavement deflections and other simulated parameters. In addition, ViscoWave was used to generate theoretical FWD and RWD deflections for a diverse set of pavement structures and subgrade conditions. The resulting deflections were used to develop correlations between the two devices, which were validated with side-by-side FWD and RWD field tests performed on 23 sites. The research determined that the differences between FWD and RWD deflections vary depending on pavement factors and loading characteristics. The two devices produced similar deflections on thicker, stiffer, lower-deflection pavements, while the FWD produced relatively higher deflections on thinner, weaker, higher-deflection pavements. Therefore, use of common FWD data analysis programs will produce different results, such as layer moduli, for TSDD devices. Advanced analysis routines capable of modeling the TSDD’s moving load and loading configurations are needed.


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