Ferrante, Chiara, Bianchini Ciampoli, Luca, Tosti, Fabio ORCID: https://orcid.org/0000-0003-0291-9937, Alani, Amir and Benedetto, Andrea (2020) Predicting the bearing capacity of road flexible pavements using GPR. In: EGU General Assembly 2020, 03 - 08 May 2020, Vienna, Austria.

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Abstract

Most of the damage in road-flexible pavements occur where stiffness of the asphalt and loadbearing layers is low. To this extent, an effective assessment of the strength and deformation properties of these layers can help to identify the most critical sections [1]. This work proposes an experimental-based model [2] for the assessment of the bearing capacity of road-flexible pavements using ground-penetrating radar (GPR – 2 GHz horn antenna) and the Curviameter [3] non-destructive testing (NDT) methods. It is known that the identification of early decay and loss of bearing capacity is a major challenge for effective maintenance of roads and the implementation of pavement management systems (PMSs). To this effect, a time-efficient methodology based on a quantitative modelling of road bearing capacity is developed in this study. The viability of using a GPR system in combination with the Curviameter NDT equipment is also proven. The research is supported by the Italian Ministry of Education, University and Research under the National Project “Extended resilience analysis of transport networks (EXTRA TN): Towards a simultaneously space, aerial and ground sensed infrastructure for risks prevention”, PRIN 2017, Prot. 20179BP4SM

Item Type:	Conference or Workshop Item (Paper)
Identifier:	10.5194/egusphere-egu2020-7021
Identifier:	10.5194/egusphere-egu2020-7021
Keywords:	Ground Penetrating Radar (GPR); Pavement Engineering; Flexible Pavements; Bearing Capacity
Subjects:	Construction and engineering > Civil and environmental engineering Construction and engineering > Digital signal processing Construction and engineering > Electrical and electronic engineering Construction and engineering > Built environment Construction and engineering
Related URLs:	Organisation Organisation
Depositing User:	Livia Lantini
Date Deposited:	10 Feb 2020 18:22
Last Modified:	04 Nov 2024 12:48
URI:	https://repository.uwl.ac.uk/id/eprint/6748

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