Validation of Staged Construction Pavement Design with the Falling Weight Deflectometer

2016 ◽  
Vol 2591 (1) ◽  
pp. 19-22
Author(s):  
Michael J. Harrell ◽  
Steven L. Gillen ◽  
Joseph Yaede
Keyword(s):  
Pavement Design ◽  
Falling Weight Deflectometer ◽  
Staged Construction ◽  
Falling Weight

Using Geogrids for Base Reinforcement as Measured by Falling Weight Deflectometer in Full-Scale Laboratory Study

1998 ◽  
Vol 1611 (1) ◽  
pp. 70-77 ◽  
Author(s):  
Thomas C. Kinney ◽  
Danielle Stone ◽  
John Schuler
Keyword(s):  
Design Procedure ◽  
Pavement Design ◽  
Silty Sand ◽  
Crushed Rock ◽  
Falling Weight Deflectometer ◽  
Base Course Material ◽  
Course Material ◽  
Base Course ◽  
Sand And Gravel ◽  
Falling Weight

A model road was constructed in a laboratory. The road consisted of asphalt over a crushed rock base and a silty sand and gravel subbase. The silty sand and gravel were placed in a very loose state to simulate a thaw-weakened, poor-quality subbase. The water table was kept at 152 mm (6 in.) below the bottom of the asphalt. The model road was divided into three sections. A geogrid was installed at the bottom of the base course material in two of the test sections, and the third was left as a control section. A falling weight deflectometer was used to measure the dynamic response of the pavement structure. The traffic benefit ratio is defined as the expected life (equivalent single-axle loads) of one section divided by the expected life of another section. The Alaska Department of Transportation and Public Facilities asphalt pavement design procedure and the NCHRP pavement design procedure were used to compare the test sections. The results from the two procedures were very similar. By using either procedure, the life of the pavement with respect to reinforcement was on the order of 2 to 4, depending on the type of grid and the depth of base course material.

Relating Laboratory and Field Moduli of Texas Base Materials

1998 ◽  
Vol 1639 (1) ◽  
pp. 1-11 ◽  
Author(s):  
S. Nazarian ◽  
J. Rojas ◽  
R. Pezo ◽  
D. Yuan ◽  
I. Abdallah ◽  
...  
Keyword(s):  
Resilient Modulus ◽  
Design Method ◽  
Field Tests ◽  
Pavement Design ◽  
Falling Weight Deflectometer ◽  
Nondestructive Tests ◽  
Second Stage ◽  
Base Materials ◽  
Two Stages ◽  
Falling Weight

Resilient modulus of base is an important parameter in the AASHTO pavement design method. However, the manner to determine this parameter is not well defined. Recent efforts in combining the resilient moduli from laboratory testing with those obtained in the field using nondestructive testing devices are presented. Laboratory tests were carried out in two stages. In the first stage, virgin materials from the quarry compacted to optimum moisture content were tested. In the second stage, similar base materials were retrieved from in-service roads. Specimens were prepared and tested at the corresponding field densities and moisture contents. Nondestructive tests were performed with the Falling Weight Deflectometer and the Seismic Pavement Analyzer. Based on tests on 10 different base materials from different parts of Texas, it was concluded that it may be difficult to directly compare moduli from laboratory and field tests; however, they can be combined for effective pavement design.

Detection of Nonresilient Behavior in Pavements with a Falling-Weight Deflectometer

2003 ◽  
Vol 1860 (1) ◽  
pp. 26-32 ◽  
Author(s):  
David P. Orr
Keyword(s):  
Plastic Deformation ◽  
Moisture Content ◽  
Granular Materials ◽  
Load Level ◽  
Pavement Design ◽  
Falling Weight Deflectometer ◽  
Current Standard ◽  
Load Detection ◽  
Chi Squared ◽  
Falling Weight

The use of resilient models to describe the behavior of the materials in pavement design is the current standard. However, there are periods of the year when these resilient models may not be valid. Granular materials in pavements show some resiliency at every load level and moisture content. Nonresiliency is critical, however, when the plastic deformation becomes a large portion of the overall deformation in response to a load. Detection of possible nonresiliency in a pavement during use of a falling-weight deflectometer (FWD) would alert the FWD operator to possible nonresilient behavior. Two statistical checks are proposed to test for nonresiliency using the raw data provided by the FWD. Daily testing of a very weak pavement during spring thaw provided FWD data during and after a period of known nonresilient behavior. A chi-squared test of the variance may be able to detect nonresilient behavior.

Efforts by North Carolina Department of Transportation to Develop Mechanistic Pavement Design System

1996 ◽  
Vol 1539 (1) ◽  
pp. 18-24
Author(s):  
Judith B. Corley-Lay
Keyword(s):  
North Carolina ◽  
First Generation ◽  
Design Procedure ◽  
Pavement Design ◽  
Design System ◽  
Falling Weight Deflectometer ◽  
Department Of Transportation ◽  
North Carolina Department ◽  
Falling Weight ◽  
Repetitions To Failure

A first generation mechanistic empirical pavement design procedure was developed using falling weight deflectometer deflections taken over a 3-year period at 16 test sections in Siler City, North Carolina. Information available for use in developing the procedure included deflection data, surface and air temperature, coring thicknesses at each test location, pavement performance records regarding rate of cracking, and traffic records. Jung's method, based on the curvature of the deflection bowl, was used to calculate strain at the bottom of the asphalt layer as a measure of fatigue. This calculated strain was used to obtain a calculated number of load repetitions to failure. Comparision of actual loads to failure with calculated loads to failure resulted in a table of shift factors by pavement type.

DIPLOBACK: Neural-Network-Based Backcalculation Program for Composite Pavements

1997 ◽  
Vol 1570 (1) ◽  
pp. 143-150 ◽  
Author(s):  
Lev Khazanovich ◽  
Jeffery Roesler
Keyword(s):  
Neural Network ◽  
Winkler Foundation ◽  
Multilayer Composite ◽  
Falling Weight Deflectometer ◽  
Subgrade Reaction ◽  
Elastic Parameters ◽  
The Neural Networks ◽  
Elastic Layers ◽  
Falling Weight ◽  
Moduli Of Elasticity

A neural-network-based backcalculation procedure is developed for multilayer composite pavement systems. The constructed layers are modeled as compressible elastic layers, whereas the subgrade is modeled as a Winkler foundation. The neural networks are trained to find moduli of elasticity of the constructed layers and a coefficient of subgrade reaction to accurately match a measured deflection profile. The method was verified by theoretically generated deflection profiles and falling weight deflectometer data measurements conducted at Edmonton Municipal Airport, Canada. For the theoretical deflection basins, the results of backcalculation were compared with actual elastic parameters, and excellent agreement was observed. The results of backcalculation using field test data were compared with the results obtained using WESDEF. Similar trends were observed for elastic parameters of all the pavement layers. The backcalculation procedure is implemented in a computer program called DIPLOBACK.

Sign in / Sign up

Export Citation Format

Share Document