Fast falling weight deflectometer as new tool to perform accelerated pavement testing

2020 ◽  
Vol 173 (6) ◽  
pp. 396-409 ◽  
Author(s):  
Marco Francesconi ◽  
Martyn Stonecliffe-Jones ◽  
Sadaf Khosravifar ◽  
Mario Manosalvas-Paredes ◽  
Albert Navarro Comes ◽  
...  
Keyword(s):  
Falling Weight Deflectometer ◽  
Accelerated Pavement Testing ◽  
Pavement Testing ◽  
Falling Weight

Fast Falling Weight Deflectometer (FastFWD) for Accelerated Pavement Testing (APT)

2017 ◽  
pp. 2235-2241 ◽  
Author(s):  
M. Manosalvas-Paredes ◽  
A. Navarro Comes ◽  
M. Francesconi ◽  
S. Khosravifar ◽  
P. Ullidtz
Keyword(s):  
Falling Weight Deflectometer ◽  
Accelerated Pavement Testing ◽  
Pavement Testing ◽  
Falling Weight

Mechanistic Analyses and Modeling of Pavement Sections Utilizing Sustainable Aggregate Quarry By-Product Applications

2020 ◽  
Vol 2674 (10) ◽  
pp. 614-627
Author(s):  
Issam I. A. Qamhia ◽  
Erol Tutumluer ◽  
Hasan Ozer ◽  
Pranshoo Solanki
Keyword(s):  
Structural Response ◽  
Field Performance ◽  
Fe Analysis ◽  
Falling Weight Deflectometer ◽  
Accelerated Pavement Testing ◽  
Performance Trends ◽  
Control Section ◽  
Pavement Testing ◽  
Falling Weight ◽  
Sensor Errors

This paper presents a modeling study based on finite element (FE) analysis to mechanistically evaluate flexible pavements constructed with quarry by-products (QB). Twelve pavement test sections, a control section, and 11 others incorporating QB as unbound subgrade replacement and chemically stabilized base/subbase applications were evaluated for field performance using accelerated pavement testing (APT). First, falling weight deflectometer (FWD) deflection basin parameters were calculated and compared with critical pavement responses to evaluate the structural adequacies of the QB pavement sections. The moduli of the constructed pavement layers were then backcalculated from the FWD deflections using the GT-PAVE FE analysis program with nonlinear and cross-anisotropic layer characterizations. For stabilized QB applications, the layer properties calculated from this analysis for the base/subbase layers were used to calculate critical pavement responses. The sections were compared using a response benefit parameter, defined as the ratio of maximum resilient surface deflection in a conventional pavement, as the control section, to that obtained for each section having a certain QB application in consideration. According to the results obtained from the APT sections and the mechanistic FE analyses, the measured and calculated FWD deflection basins were successfully matched with individual sensor errors not exceeding 5% for all 12 test sections. The calculated response benefits indicated significant advantages for using cement-stabilized QB applications over fly ash-stabilized QB applications and conventional flexible pavement sections. Considering the pavement structural response benefits and good performance trends observed, major cost benefits can be realized by routine use of these sustainable QB applications.

Detection and Monitoring of Cracks in Asphalt Pavement Under Texas Mobile Load Simulator Testing

1997 ◽  
Vol 1570 (1) ◽  
pp. 10-22 ◽  
Author(s):  
N.-K. J. Lee ◽  
F. Hugo ◽  
K. H. Stokoe
Keyword(s):  
Surface Layer ◽  
Longitudinal Direction ◽  
Main Mode ◽  
Accelerated Pavement Testing ◽  
Surface Cracking ◽  
Longitudinal Stiffness ◽  
Load Simulator ◽  
Surface Distress ◽  
Pavement Testing ◽  
Falling Weight

The Texas mobile load simulator (TxMLS) is a newly developed accelerated pavement testing device used to evaluate pavement performance under real trafficking loads. This evaluation is performed by applying trafficking loads and monitoring surface distress, such as cracking and rutting, in conjunction with a number of other measurements of the pavement, such as those conducted with the falling weight deflectometer, multidepth deflectometer, strain gauge, pressure cells, and seismic (stress-wave) tests. A procedure for monitoring the progressive degradation of the asphalt surface was developed using the spectral-analysis-of-surface-waves (SASW) technique. This procedure was applied with the TxMLS and proved to be equally effective. SASW tests that were performed intermittently between trafficking phases on trafficked and untrafficked areas show ( a) the effect of temperatures and frequencies on the asphalt moduli, ( b) the importance of temperature and frequency corrections in analyzing the degradation of the asphalt surface layer, and ( c) the long-term trends in surface-wave velocities (and hence, moduli) of the surface layer with increasing number of load applications. It was found that stiffness of the asphalt layer in the longitudinal direction was progressively reduced under trafficking. Concurrently, surface cracking progressively increased. The reduction in longitudinal stiffness occurred at a faster rate than the crack growth. In contrast, the reduction in the stiffness of the asphalt layer in the transverse direction was slower, probably because the main mode of cracking was transverse. The feasibility of using SASW testing as a predictor of degradation and imminent cracking was confirmed with these studies.

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.

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