Experimental Development of Distributed Optical Fibre Monitoring Methods for Underground Infrastructure
Doctoral thesis, 2026
Monitoring during underground construction is essential for verifying design assumptions, assessing structural behaviour, and supporting safe and efficient excavation. However, conventional monitoring methods are often limited to discrete measurement points, which may be insufficient for identifying localised deformation and load-transfer mechanisms in jointed rock masses and tunnel support systems. This thesis investigates the use of distributed optical fibre sensors (DOFS) for high-resolution strain-based monitoring in hard rock tunnelling.
Two monitoring applications are studied experimentally. The first concerns load identification in fibre-reinforced shotcrete tunnel linings. Laboratory specimens were instrumented with DOFS and subjected to two load types: idealised loose rock block loads and distributed loads combined with bond loss between substrate and concrete. The results show that these load types can be distinguished from distributed strain and curvature responses before peak load is reached, demonstrating the potential of DOFS for early warning and targeted maintenance.
The second application concerns deformation monitoring in the surrounding rock mass. A DOFS-based shape sensing system was developed, evaluated in laboratory tests, and installed in a borehole adjacent to an active drill-and-blast tunnel excavation. A beam theory-based analysis method was developed to determine load direction, longitudinal deformation, and lateral deformation, including both bending and shear deformation. Laboratory results showed good agreement with reference measurements, while the field test demonstrated that the sensor can capture relative deformation in a hard rock mass.
The thesis shows that DOFS can provide spatially continuous information that improves the interpretation of local load and deformation mechanisms in underground infrastructure. This information can support safer and more efficient excavation by enabling earlier identification of unfavourable structural behaviour, more targeted inspections, and improved assessment of support performance.
Two monitoring applications are studied experimentally. The first concerns load identification in fibre-reinforced shotcrete tunnel linings. Laboratory specimens were instrumented with DOFS and subjected to two load types: idealised loose rock block loads and distributed loads combined with bond loss between substrate and concrete. The results show that these load types can be distinguished from distributed strain and curvature responses before peak load is reached, demonstrating the potential of DOFS for early warning and targeted maintenance.
The second application concerns deformation monitoring in the surrounding rock mass. A DOFS-based shape sensing system was developed, evaluated in laboratory tests, and installed in a borehole adjacent to an active drill-and-blast tunnel excavation. A beam theory-based analysis method was developed to determine load direction, longitudinal deformation, and lateral deformation, including both bending and shear deformation. Laboratory results showed good agreement with reference measurements, while the field test demonstrated that the sensor can capture relative deformation in a hard rock mass.
The thesis shows that DOFS can provide spatially continuous information that improves the interpretation of local load and deformation mechanisms in underground infrastructure. This information can support safer and more efficient excavation by enabling earlier identification of unfavourable structural behaviour, more targeted inspections, and improved assessment of support performance.
Rock mass deformation.
Underground infrastructure monitoring
Shotcrete tunnel linings
Distributed optical fibre sensors
SB-H4, Sven Hultins gata 6, Chalmers
Opponent: Prof Neil Hoult, Queens University, Canada
Author
August Jansson
Chalmers, Architecture and Civil Engineering, Structural Engineering
Investigation of the Impact of Concrete Surface Treatment Methods on the Interfacial Bond Strength
RILEM Bookseries,;Vol. 43(2023)p. 925-934
Book chapter
Experimental dataset for loads on hard rock shotcrete tunnel linings in a laboratory environment
Data in Brief,;Vol. 57(2024)
Journal article
Experimental investigation on prevalent local failure mechanisms in hard rock tunnel linings using distributed optical fibre sensors
Engineering Structures,;Vol. 333(2025)
Journal article
Strain distributions for shotcrete failure in hard rock tunnels
IABSE Symposium Manchester 2024: Construction's Role for a World in Emergency,;(2024)p. 806-813
Paper in proceeding
Jansson, A, Berrocal, G. C, Rempling, R, Fernandez, I. Comparative analysis between Distributed Optic Fibre Sensors for the measurement of localised shear deformations
Jansson, A, Berrocal, G. C, Rempling, R, Fernandez, I Quantification of shear deformation in discontinuity planes using distributed optical fibre sensors
Monitoring is essential in underground construction because it helps engineers verify that tunnels behave as expected, maintain safe working conditions, and reduce risks to nearby structures. Most conventional monitoring methods measure deformation only at selected points, which means that the behaviour between these points must be estimated. This often requires conservative assumptions and can make it difficult to understand what caused a measured deformation and how it affects the surrounding structures. As an alternative, distributed optical fibre sensors can capture deformation over longer sections and reveal local changes that point-wise methods may miss.
In this thesis, such sensors were used for two hard rock tunnelling applications: detecting loads acting on shotcrete tunnel linings and measuring deformation in the surrounding rock mass. Both applications were tested in the laboratory, and the rock deformation sensor was also tested during an ongoing tunnel excavation.
The results show that optical fibre sensors embedded in shotcrete can distinguish between loads from loose rock blocks and loads related to loss of bond between shotcrete and rock, provided that the sensor crosses the loaded area. For rock deformation monitoring, optical fibres were attached to an aluminium rod grouted into a borehole. Laboratory tests verified the developed analysis model, and the field test showed that the sensor could measure deformation in the rock mass and identify a possible shear plane. Overall, the thesis demonstrates that distributed optical fibre sensing can provide more detailed information about tunnel behaviour and support safer, more efficient underground construction.
In this thesis, such sensors were used for two hard rock tunnelling applications: detecting loads acting on shotcrete tunnel linings and measuring deformation in the surrounding rock mass. Both applications were tested in the laboratory, and the rock deformation sensor was also tested during an ongoing tunnel excavation.
The results show that optical fibre sensors embedded in shotcrete can distinguish between loads from loose rock blocks and loads related to loss of bond between shotcrete and rock, provided that the sensor crosses the loaded area. For rock deformation monitoring, optical fibres were attached to an aluminium rod grouted into a borehole. Laboratory tests verified the developed analysis model, and the field test showed that the sensor could measure deformation in the rock mass and identify a possible shear plane. Overall, the thesis demonstrates that distributed optical fibre sensing can provide more detailed information about tunnel behaviour and support safer, more efficient underground construction.
SensIT – Verifiering och prognostisering av tekniska funktionskrav på tunnelinfattning av betong – sensorbaseras prognosmetod med artificiell intelligens
Swedish Transport Administration (TRV2021/66599), 2021-11-01 -- 2024-12-31.
Subject Categories (SSIF 2025)
Other Civil Engineering
Infrastructure Engineering
DOI
10.63959/chalmers.dt/5939
ISBN
978-91-8103-482-0
Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 5939
Publisher
Chalmers
Related datasets
Experimental data for loads on tunnel linings including distributed optical fiber sensing and digital image correlation [dataset]
DOI: https://doi.org/10.5878/dvcn-bg03