EGU2020-3422
https://doi.org/10.5194/egusphere-egu2020-3422
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Data correlation of non-destructive testing methods to assess asphalt pavement thickness

Christina Plati1, Andreas Loizos2, and Konstantinos Gkyrtis3
Christina Plati et al.
  • 1National Technical University of Athens (NTUA), Laboratory of Pavement Engineering, Greece (cplati@central.ntua.gr)
  • 2National Technical University of Athens (NTUA), Laboratory of Pavement Engineering, Greece (aloizos@central.ntua.gr)
  • 3National Technical University of Athens (NTUA), Laboratory of Pavement Engineering, Greece (gkyrtis@central.ntua.gr)

Performing structural assessment at any time of asphalt pavements service life is an inherent process within pavement condition assessment. Layers thicknesses are among the major contributors to the overall pavement response and performance. Knowledge of layer thicknesses is imperative for both new and in-service pavements, because thickness data is usually combined with other response indicators (i.e. pavement deflections) in order to perform pavement evaluation during pavements service life. As such, inaccuracies in thickness assessment might result in erroneous response analysis and life expectancy estimation with a detrimental financial impact during maintenance planning.

Traditionally, layer thicknesses were retrieved through coring or digging test pits. Because of the limitations of these methods (including location-specific information, destructive nature, need for traffic disruptions), the pavement engineering community has consistently drawn its attention to a broadened utilization of advanced Non-Destructive Testing (NDT) systems in order to non-invasively determine the pavement cross-section. The most indicative NDT tool for that purpose is the Ground Penetrating Radar (GPR), which is systematically used for layers thickness evaluation. Within the framework of pavement evaluation processes, GPR is quite often combined with the Falling Weight Deflectometer (FWD), which provides with pavement response indications in terms of surface deflections.

It is worthwhile mentioning that GPR requires high expertise in order to reliably analyze the collected data and until now, there is none uniquely recognizable and universally accepted signal processing scheme. Supplementary to experienced users and analysts, investments in time and human resources are also needed to make reliable interpretations. Such reasons may potentially discourage related stakeholders from systematic GPR use, especially in cases where there are budgets constraints for the procurement and transportation logistics of multiple expensive equipment.

In light of the above, related research is pursed in respect to the investigation of the ability of FWD surface deflections indexes to provide with reliable information on the Asphalt Concrete (AC) layer thicknesses. For this purpose, Long-Term Pavement Performance (LTPP) data is analyzed including FWD and GPR data as well as sample coring. A nonlinear regression based relationship is under development that preliminarily exhibits a satisfactory performance both during model fit and model accuracy evaluation. Based on the above framework, it is suggested that the NDT analysis with deflection indexes seems promising in terms of roughly producing AC thickness, thereby balancing constraints at network level.

How to cite: Plati, C., Loizos, A., and Gkyrtis, K.: Data correlation of non-destructive testing methods to assess asphalt pavement thickness, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3422, https://doi.org/10.5194/egusphere-egu2020-3422, 2020

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