Vertical compressive strain-based method for setting the rigid layer depth based on falling weight deflectometer test

2022 ◽  
Vol 319 ◽  
pp. 126156
Author(s):  
Yue Hu ◽  
Huailei Cheng ◽  
Lijun Sun
Keyword(s):  
Compressive Strain ◽  
Falling Weight Deflectometer ◽  
Layer Depth ◽  
Rigid Layer ◽  
Falling Weight

Backcalculation of pavement layer moduli from falling weight deflectometer data using an artificial neural network

2008 ◽  
Vol 35 (1) ◽  
pp. 57-66 ◽  
Author(s):  
Sunil Sharma ◽  
Animesh Das
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Falling Weight Deflectometer ◽  
Rigid Layer ◽  
Ann Models ◽  
Artificial Neural ◽  
Artificial Neural Network Ann ◽  
Equidistant Points ◽  
Falling Weight

Efforts have been made in this paper to backcalculate the in situ elastic moduli of asphalt pavement from synthetically derived falling weight deflectometer (FWD) deflections at seven equidistant points. An artificial neural network (ANN) is used as a tool for backcalculation in this work. The ANN is observed to backcalculate layer moduli, both from normal as well as noisy deflection basins, with better accuracy compared with other software, namely, EVERCALC and ExPaS. EVERCALC is a backcalculation software downloaded from the Internet and ExPaS is a backcalculation algorithm developed in-house, based on a “search and expand” approach. Work have been extended further to develop ANN models that can predict a possible rigid layer at the bottom of the pavement and can directly predict the remaining life of the pavement without backcalculating the layer moduli. Finally, a reliability analysis is performed to quantify the performance of backcalculation using an ANN.

Falling Weight Deflectometer Fleet Repeatability and Reproducibility

2004 ◽  
Vol 5 (2) ◽  
pp. 215-238
Author(s):  
Sergio Rocha ◽  
Vivek Tandon ◽  
Soheil Nazarian
Keyword(s):  
Falling Weight Deflectometer ◽  
Repeatability And Reproducibility ◽  
Falling Weight

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.

scholarly journals Propagation of Surface Waves in Asphalt Pavements Generated by Different Load Impulse of Falling Weight Deflectometer

2019 ◽  
Vol 15 (1) ◽  
pp. 29-35
Author(s):  
Jozef Komačka ◽  
IIja Březina
Keyword(s):  
Surface Waves ◽  
Travel Time ◽  
Time History ◽  
Asphalt Pavements ◽  
Load Force ◽  
Falling Weight Deflectometer ◽  
Waves Propagation ◽  
Propagation Of Waves ◽  
Falling Weight ◽  
The Waves

Abstract The propagation of waves generated by load impulse of two FWD types was assessed using test outputs in the form of time history data. The calculated travel time of wave between the receiver in the centre of load and others receivers showed the contradiction with the theory as for the receivers up to 600 (900) mm from the centre of load. Therefore, data collected by the sensors positioned at the distance of 1200 and 1500 mm were used. The influence of load magnitude on the waves propagation was investigated via the different load force with approximately the same load time and vice versa. Expectations relating to the travel time of waves, depending on the differences of load impulse, were not met. The shorter travel time of waves was detected in the case of the lower frequencies. The use of load impulse magnitude as a possible explanation was not successful because opposite tendencies in travel time were noticed.

scholarly journals Measurements of the elastic modulus of pavement subgrade layers using the SASW and FWD test methods

2015 ◽  
Vol 10 (2) ◽  
pp. 174-181 ◽  
Author(s):  
Nur Izzi Md. Yusoff ◽  
Sentot Hardwiyono ◽  
Norfarah Nadia Ismail ◽  
Mohd Raihan Taha ◽  
Sri Atmaja P. Rosyidi ◽  
...  
Keyword(s):  
Spectral Analysis ◽  
Elastic Modulus ◽  
Surface Wave ◽  
Time Lag ◽  
Test Methods ◽  
Pavement Management ◽  
Falling Weight Deflectometer ◽  
Surface Wave Propagation ◽  
Evaluation And Monitoring ◽  
Falling Weight

In pavement management systems, deflection basin tests, such as the Falling Weight Deflectometer test, are common techniques that are widely used, while the surface wave test, i.e. the Spectral Analysis of Surface Wave test, is recently employed as an alternative technique in pavement evaluation and monitoring. In this paper, the performance of both dynamic non-destructive tests on pavement subgrade investigation is presented. Surface wave propagation between a set of receivers was transformed into the frequency domain using the Fast Fourier Transform technique and subsequently a phase spectrum was produced to measure the time lag between receivers. Using the phase difference method, an experimental dispersion curve was generated. Inversion analysis based on the 3-D stiffness matrix method was then performed to produce a shear wave velocity profile. The elastic modulus of pavement layers was calculated based on linear elastic theory. In the Falling Weight Deflectometer test, seven geophones were used to collect in situ deflection data. Based on a back-calculation procedure with the ELMOD software, the elastic modulus of each flexible pavement layer can be obtained. Both techniques are able to comprehensively investigate the elastic modulus of the subgrade layer in existing pavement non-destructively. The elastic modulus between the Spectral Analysis of Surface Wave method and the Falling Weight Deflectometer test on the subgrade layer is observed to be in a good agreement. A correlation of the elastic modulus of thesubgrade layer from both techniques is also presented.

scholarly journals Quantity traceability of falling weight deflectometer

2019 ◽  
Vol 2019 (23) ◽  
pp. 8583-8586
Author(s):  
Na Miao ◽  
Yixu Wang ◽  
Lu Peng ◽  
Lu Liu ◽  
Liwei Lei
Keyword(s):  
Falling Weight Deflectometer ◽  
Falling Weight

Rutting Development in Linear Tracking Test Pavements To Evaluate Shell Subgrade Strain Criterion

1997 ◽  
Vol 1570 (1) ◽  
pp. 23-29 ◽  
Author(s):  
J. Groenendijk ◽  
C. H. Vogelzang ◽  
A. Miradi ◽  
A. A. A. Molenaar ◽  
L. J. M. Dohmen
Keyword(s):  
Data Analysis ◽  
Shear Deformation ◽  
Asphalt Concrete ◽  
Heavy Traffic ◽  
Falling Weight Deflectometer ◽  
Wheel Load ◽  
Strain Criterion ◽  
Average Criterion ◽  
Tracking Device ◽  
Falling Weight

Two full-depth gravel asphalt concrete (AC) pavements of 0.15- and 0.08-m thickness on a sand subgrade were loaded with 4 million and 0.65 million repetitions of a 75-kN super-single wheel load using the linear tracking device (LINTRACK), a heavy-traffic simulator. Frequent measurements of asphalt strains, temperatures, rutting, cracking, and falling weight deflectometer (FWD) were made. The data analysis of the rutting measurements indicates that all rutting could be ascribed to subgrade deformation (secondary rutting). No evidence was found of shear deformation within the asphalt layer (primary rutting). The data analysis also indicates that the observed rutting performance of the LINTRACK test sections (to a maximum rut depth of 18 mm) coincides closely with the average criterion from the Shell Pavement Design Manual, which relates subgrade strain to allowable number of strain repetitions.

Sign in / Sign up

Export Citation Format

Share Document