Strains and shape changes in asphalt layers: load tests & long-term measurements

This project involved two types of road surface structures equipped with Nerve-Sensors, measuring both strains (EpsilonRebars) and displacements (3DSensor). Both of them were embedded into the road layers during its construction, providing the possibility of analyzing its internal structural behaviour under static proof load tests. Our nervous system, supplemented by spot temperature sensors, was used successfully also in terms of long-term structural health monitoring (SHM).

DFOS Sensors Installed: EpsilonRebar and 3DSensor

Project challenges

How to apply non-invasive diagnostics in demanding historic structures?
How to get precise measurement data to detect local damage and imperfection?
How to measure detailed strain profiles over the entire height of the brick masonry wall?

Benefits of using the DFOS monitoring system

Measurements of both strains and displacements inside the asphalt layer
Observation of structural response and creep during static load tests
Possibility of validation and calibration of the spatial numerical models
Detailed comparison between two types of road construction technologies

Results of using the DFOS monitoring system

The DFOS-based nervous system was used for short-term measurements during static truck load tests as well as for long-term monitoring during changeable thermal conditions. The figure below presents example strain profiles measured by EpsilonRebar embedded into asphalt layers along the longitudinal direction. Two axes of the loading track are clearly indicated by tensile strains, while in the surrounding area, the compression was observed. Furthermore, short-term creeping was monitored while vertical displacements were registered by 3DSensors.

Technical specifications

10 600 measurement points
106 m of sensing path
4 x 3DSensor, 16 x ER
load tests & long-term

Example results

Recomendations (optional)

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John Doe

Project partner

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Case study
EpsilonRebar Datasheet
3DSensor Datasheet

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