Case Studies


The monitoring system consists of 28 transverse measurement sections aimed at controlling the tensile and deformation evolution of the tunnel lining over time. The monitoring system, consisting of MEMS inclinometers integrated with post-installed local tension-deformation sensors within the lining, allows for both local and global monitoring of the structure's response. The diagnostics are complemented by nonlinear FEM modeling and a real-time alert service for any structural issues.
Location: Italy
Project type: Highway Tunnel
Sensor type: Bi-axial Inclinometers | Local Tension and Deformation Sensors
Number of sensors: 448 Bi-axial Inclinometers | 196 Local Tension and Deformation Sensors
Installation period: June 2021


  • Executive plant design
  • Installation support
  • Nonlinear FEM modeling, model updating, and continuous structural diagnostics with automatic alerting


  • Continuous monitoring of the membrane deformation and tension state, with the definition of two active thresholds, one for attention and one for alarm, based on damage scenarios and global safety checks of the structure
  • Monitoring over time of the structural response evolution in the areas where the failure occurred
  • Continuous monitoring of the areas adjacent to the affected areas
  • Real-time alerting of any structural issues.


The subject of this project is a highway tunnel with a total length of approximately 13 kilometers, with excavation activities lasting about four years. The rocky mass, mainly composed of calc-schist, can only be considered homogeneous to a limited extent in terms of its behavior on a large scale, while locally, the lithologies present several systems of discontinuities (schistosity, faults, and joints) that have characterized and influenced the stability of the excavations and the behavior of the rock mass.

During the excavation process, which was carried out using traditional full-section blasting methods, it became evident that the measured convergence values were locally affected by the presence of tectonic faults and laminated and degraded calc-schist, highlighting an anisotropic behavior of the tunnel and an extension of the fractured and plasticized zone from the lining. The excavation section was approximately 90 m2 with an average profile width of about 11.50 m and an average height of about 8.50 m. The significant length of the project made it necessary to execute ventilation shafts that lead to two pairs of in-cavern ventilation plants, and to construct two ventilation ducts inside the section, one for stale air and one for fresh air.

The monitoring system consists of a network of MEMS bi-axial inclinometers to monitor and quantify the deformation of the tunnel lining over time. Additionally, the system includes a network of strain-deformation sensors installed within the lining to monitor and quantify the evolution of the stress state over time. There are 28 monitored sections distributed along the longitudinal development of the tunnel, all with the same arrangement of sensors in terms of the number and type of installed sensors, with varying spacing and a more concentrated distribution in sections of greater structural interest.


The behavior of the tunnel is simulated through non-linear FEM modeling calibrated with respect to historical investigative campaigns carried out on the structure, with accurate reconstruction of the stress-strain state of the pre-existing lining prior to instrumentation, and subsequent continuous control of the same through the installed distributed monitoring system.

The time-based control of the structural response evolution in the areas where instability has manifested and in neighboring areas is executed with respect to threshold, attention, and alarm levels, defined based on damage scenarios and global safety verifications of the structure.

The monitoring and diagnostics are supported by ad-hoc studied algorithms and medium to long-term data analytics processes aimed at extracting, with model-driven and data-driven analysis, the most significant performance indicators for the control of the local and global stress-strain response of the structure. Correlations are performed between sensor groups and adjacent monitoring sections for the timely identification and localization of anomalies.

The diagnostics are completed by a real-time alerting service of any structural criticalities.


Case history


The monitoring system has been specifically designed in terms of number and positioning of sensors to capture the complex dynamic response of the structure. By means of FEM modeling of damage scenarios, appropriate dynamic thresholds have been calculated for the continuous monitoring of the state of the stays and the evolution over time of the response of the footbridge deck.

The monitoring aims at analyzing the behavior of post-tensioned cables during the bridge's operation, through time and frequency domain analyses. Real-time monitoring is a key tool to provide useful information for the detection of possible effects induced by ongoing deterioration or fatigue processes. The analysis allows a comparison between the expected modal parameters and the measured natural frequencies in the initial monitoring conditions, with consequent definition of corresponding attention and alarm threshold levels set for automatic alerting of the operator.
The structural monitoring and diagnostics of the two tunnel tubes are supported by a complex non-linear FEM modeling, through which, for each monitoring section, the deformation and the evolution of its ovalization with respect to the evolution of the ongoing landslide phenomenon are evaluated. In cable sections where the mechanical characterization and the surrounding stratigraphic conditions are completely similar, a Data-Driven approach is used to extend the Performance Indicators and monitor the most significant structural response parameters at all measurement sections.
The monitoring allowed the real-time control of the response of the deck of a span during open traffic restoration works, and was subsequently extended to the entire viaduct for static and dynamic behavior control over time. The Model Driven monitoring approach allowed the investigation of the main damage scenarios of the structure and the definition of Performance Indicators on which to set threshold values and conditions.
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