This paper presents experimental work aimed at proving the feasibility of using Distributed Fibre Optic Sensing (DFOS) as an early warning system for sinkhole detection. 1g experiments were conducted using a plane strain trapdoor and scaled to provide insight into the formation of a sinkhole in sand, in which DFOS cables are laid at selected depths. The DFOS data are compared with the geomechanics of the soil displacement, recorded using Particle Image Velocimetry (PIV). It was demonstrated that the DFOS exhibits a signature strain profile at the location of the sinkhole, allowing a sinkhole to be located using the DFOS data. Differences in the PIV and DFOS data are however apparent, notably the strain magnitudes. Nonetheless, it is possible to estimate the size and location of the sinkhole at depth using the DFOS data. Using a preliminary study of the development of the zone of subsidence, for a range of relative densities, it is then possible to predict the extent of the damage zone at ground surface. Such results show the potential for the incorporation of DFOS in the construction of critical infrastructure to enable early detection of sinkhole formation and thus opportunity for remedial action to prevent catastrophic failures.

The construction of tunnels in urban areas can affect the nearby existing infrastructures and buildings, as shallow excavations induce movements up to the ground surface. An important parameter to be monitored during the excavation is the volume loss, which plays a crucial role in determining the ground movements at the surface. InSAR satellite monitoring has the potential to detect ground movements at the millimetric scale on a vast area for tunneling applications. In the present study, the Multi-Temporal InSAR (MT-InSAR) technique, based on the persistent scattering method, is used to retrieve vertical displacements induced by the excavation of twin tunnels of a metro line in the City of Naples (Italy). Here, the volume loss is obtained by fitting a Gaussian curve on the monitored settlement data induced by the excavation of the first tunnel. The latter is then used to predict the settlement of the second excavation about one year later and compared to the MT-InSAR data. These monitored data show the typical shape of the settlement profile, confirming the empirical Gaussian distribution and MT-InSAR capability to detect millimetric displacements. Therefore, MT-InSAR can be used to feed algorithms to improve the prediction of tunneling-induced displacements.

This paper forms part of the SINEW project (SINkhole Early Warning) and continues the work from Möller et al. (2022), where 1g experiments demonstrate the feasibility of using Distributed Fibre Optic Sensing (DFOS) for sinkhole early warning. This experimental campaign highlighted an order of magnitude difference in the strain between the soil and the cable that remains unexplained and weakens the confidence in the technology and/or the experimental method. This paper uses 3D finite element analyses to further examine this discrepancy and the soil-cable interface. The results further support the experimental findings and demonstrate that the DFOS signature strain profile is induced by the horizontal movement of the ground, and enhanced when sufficient coupling at the soil-cable interface is achieved. This result holds when modelling is scaled to realistic confining pressure and its significance is twofold. First, this needs to be accounted for in the DFOS laying technique. Second, particles of cohesionless soils undergo relatively high horizontal displacement away from the centre of the sinkhole, and this means that DFOS cables are able to detect subsidence away from the centre of the sinkhole. The paper illustrate this result and the signature strain profile expected in this case.