scholarly journals EFFECT OF DIELECTRIC CONSTANT ON ASPHALT LAYERS THICKNESS BASED ON GROUND PENETRATING RADAR DATA ANALYSIS

Author(s):  
Audrius Vaitkus ◽  
Rita Kleizienė ◽  
Martynas Karbočius

The ground penetrating radar (GPR) in roads is use to investigate the pavement structure layers thickness on network and project level, misaligned dowels and tie bar in concrete pavement, moisture and ground water level, air voids of asphalt layers, and to assure the quality control. Since, pavement layer thickness and materials properties are the key parameters for pavement bearing capacity and residual life determination the effective and reliable GPR analysis procedure is substantial for pavement management system. However, in order to determine asphalt layers thickness the dielectric constant or GPR velocity have to be known. The most common practice to determine the dielectric constant of specific pavement layer is to drill the cores at least every 1 km, as combination of destructive and non-destructive methods. The objective of this study is to investigate the effect of the dielectric constant to asphalt layers thickness determination accuracy. The dielectric constant of asphalt layers and GPR measurements were performed in the 27th pavement sections of the Test Road. The dielectric constant of asphalt layers calculated based on drilled cores data. Analysing the wearing, binder, and base layers separately and in combination. Finally, the errors of determined thicknesses of pavement layers were compared with actual thickness. To determine the dielectric constant influence to the asphalt layer thickness of road sections were investigated by drilling cores and determined the actual thickness. The dielectric constant based on core data and GPR measurements were compared.

PIERS Online ◽  
2006 ◽  
Vol 2 (6) ◽  
pp. 567-572
Author(s):  
Hui Zhou ◽  
Dongling Qiu ◽  
Takashi Takenaka

2021 ◽  
pp. 1-19
Author(s):  
Melchior Grab ◽  
Enrico Mattea ◽  
Andreas Bauder ◽  
Matthias Huss ◽  
Lasse Rabenstein ◽  
...  

Abstract Accurate knowledge of the ice thickness distribution and glacier bed topography is essential for predicting dynamic glacier changes and the future developments of downstream hydrology, which are impacting the energy sector, tourism industry and natural hazard management. Using AIR-ETH, a new helicopter-borne ground-penetrating radar (GPR) platform, we measured the ice thickness of all large and most medium-sized glaciers in the Swiss Alps during the years 2016–20. Most of these had either never or only partially been surveyed before. With this new dataset, 251 glaciers – making up 81% of the glacierized area – are now covered by GPR surveys. For obtaining a comprehensive estimate of the overall glacier ice volume, ice thickness distribution and glacier bed topography, we combined this large amount of data with two independent modeling algorithms. This resulted in new maps of the glacier bed topography with unprecedented accuracy. The total glacier volume in the Swiss Alps was determined to be 58.7 ± 2.5 km3 in the year 2016. By projecting these results based on mass-balance data, we estimated a total ice volume of 52.9 ± 2.7 km3 for the year 2020. Data and modeling results are accessible in the form of the SwissGlacierThickness-R2020 data package.


Data in Brief ◽  
2016 ◽  
Vol 7 ◽  
pp. 1588-1593 ◽  
Author(s):  
Ted L Gragson ◽  
Victor D. Thompson ◽  
David S. Leigh ◽  
Florent Hautefeuille

2021 ◽  
pp. 1-53
Author(s):  
Lei Fu ◽  
Lanbo Liu

Ground-penetrating radar (GPR) is a geophysical technique widely used in near-surface non-invasive detecting. It has the ability to obtaining a high-resolution internal structure of living trunks. Full wave inversion (FWI) has been widely used to reconstruct the dielectric constant and conductivity distribution for cross-well application. However, in some cases, the amplitude information is not reliable due to the antenna coupling, radiation pattern and other effects. We present a multiscale phase inversion (MPI) method, which largely matches the phase information by normalizing the magnitude spectrum; in addition, a natural multiscale approach by integrating the input data with different times is implemented to partly mitigate the local minimal problem. Two synthetic GPR datasets generated from a healthy oak tree trunk and from a decayed trunk are tested by MPI and FWI. Field GPR dataset consisting of 30 common shot GPR data are acquired on a standing white oak tree (Quercus alba); the MPI and FWI methods are used to reconstruct the dielectric constant distribution of the tree cross-section. Results indicate that MPI has more tolerance to the starting model, noise level and source wavelet. It can provide a more accurate image of the dielectric constant distribution compared to the conventional FWI.


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