Session 5
This session aims to bring together not only researchers, but also fiber optic network owners, photonics manufacturers, and experts in rock mechanics from both laboratory and mining contexts, all sharing an interest in the application of fiber optic sensing for enhancing societal resilience. Policymakers interested in exploring the use of telecommunication fiber cable for this purpose are also warmly invited to actively engage in the collaborative discussion.
We invite studies focusing on the utilization of telecommunication networks for all aspects of urban planning, from near-surface structure investigation to seismic monitoring, wave propagation, ground motion analysis, and finally, developing real-time monitoring and early warning systems for natural disasters. We also welcome contributions related to applications such as infrastructure resilience, including monitoring the health and integrity of civil structures, bridges, tunnels, highways, pipelines, dams, and other critical infrastructure. Furthermore, we are enthusiastic about further untapped capabilities or challenges of fiber optic networks for urban resilience purposes. If you have any other case studies or even witness challenges (e.g., signal saturation, fiber coupling problems, data confidentiality, and protection of personal life) on utilization of telecommunication fiber in diverse settings, including urban, rural, or coastal environments — both on land and underwater — with varying cable lengths, we encourage you to share your experiences/problems and possible technical/scientific solutions in this session.
Invited speaker: Hsin-Hua Huang (Academia Sinica, Taiwan)
Distributed fiber-optic sensing (DFOS) is an emerging technique that can turn a fiber cable into a dense seismic sensor array with meter-scale spacing. Ubiquitously existing telecom fiber cables in buildings and cities render great potential for the use of DFOS in urban hazard reduction studies. One of such aspects is to identify (hidden) fault structures beneath the populated metropolis in the Taipei basin, where the NE-SW Sanchiao Fault and several basement faults transverse. While the east-dipping Sanchiao is capable of generating M 6+ earthquakes right under the urban area, its geometrical and structural characteristics are not well understood due to the absence of outcrops covered by Quaternary alluvial deposits and the lack of high-resolution seismic data. Here, we employ an existing telecommunication cable (owned by Chunghwa Telecom Company) running across the Sanchiao Fault to investigate the fault and basin structure at unprecedented resolution. The ambient noise cross-correlation and beamforming analysis are used to measure multi-frequency Rayleigh-wave phase velocities along the cable and invert for high-resolution shallow shear velocity profile across the fault. The results show a clear velocity contrast between the Taipei Basin and the Linkou Tableland, delineating a clear east-dipping geometry of the Sanchiao Fault. The presence of thick sediments to the east in the basin is also imaged to play a key role in modulating seismic waves for strong amplification and prolonged shaking. Our study evidences that the dark-fiber DFOS is a powerful direction that can offer high-resolution mapping/monitoring of the major fault structures with least cost.
How to cite: Huang, H.-H., Wang, C.-H., Wu, E.-S., Ku, C.-S., Lin, C.-J., and Ma, K.-F.: Urban hazard reduction using dark fiber distributed sensing, Galileo conference: Fibre Optic Sensing in Geosciences, Catania, Italy, 16–20 Jun 2024, GC12-FibreOptic-73, https://doi.org/10.5194/egusphere-gc12-fibreoptic-73, 2024.
Telecommunications networks based on optical fiber communication have been vastly deployed in the last years to cope with the increasing traffic demands. They cover wide terrestrial areas with thousands of kilometers of available fiber cables, arranged in meshed, rings or festoon network topologies. Moreover, their operation is becoming more and more software-defined thanks to the definition of open interfaces and data structures, transforming the infrastructure into a crucial commodity able to offer several network services.
Recently, the idea of using existing telecommunications fiber networks as a wide smart grid for environmental sensing is gaining momentum, since optical fiber can be used as an excellent mechanical stress sensors, as several physical effects are impacted by external stress. Distributed acoustic sensing (DAS) techniques deliver extremely accurate and spatially resolved measurements which are the state of the art, for example, in earthquake detection. However, its high cost, need for dark fibers and physical limitations prevent its wide deployment in telecom infrastructure.
In this context, sensing based on state of polarization (SOP) monitoring of optical signals is an attractive solution. SOP is alredy monitored on optical coherent channel receivers for data recovery, although access to this data is usually closed by transceiver vendors. However, it is potentially accessibile on cheaper intensity modulated optical data channels, still widespread in optical networks, especially in the access segment. Also, it can be monitored using dedicated signals which can be transmitted alongside typical data channels. Moreover, SOP sensing does not require bidirectional transmission onto the same fibers and can extend its reach farther than DAS as it supports optical amplifiers, thus improving the compatibility between data and sensing services. On the downside, SOP sensing loses DAS spatial resolution, as it provides an integrated measuremnts over an entire fiber span and extraction of significant event information is complicated by the randomness of fiber birefringence. However, terrestrial networks can offer several SOP sensing sites which can be implemented with far cheaper equipment with respect to DAS or interferometry.
In this work we explore the possibility for wide sensing grids with fiber length scale spatial resolution, which can integrate the information provided by traditional seismic stations networks. In particular, while developed areas may leverage on seismic stations networks, SOP sensing represents a cost effective solutio in emerging economies where telecom infrastructure is already deployed. Another key aspect relates to the development of effective techniques to detect the environemntal events of interest features, such as the earthquakes P/S waves, from the SOP time series. Indeed, especially in the terrestrial networks scenario, anthropic activities act as noise on the monitored SOP evolutions. To this aim, detection based on machine learning techniques is promising, due to the largely vaying characteristic figures of seismic waves. Due to the lack of extensive SOP experimental observations, we have developed simulations tools able to generate SOP synthetic data from realistic strain rates and we show how they can be used to train ML models based on spatially integrated SOP time evolutions.
How to cite: Virgillito, E., Awad, H., Usmani, F., Straullu, S., Bratovich, R., Proietti, R., Pastorelli, R., and Curri, V.: Environmental Sensing and Detection based on State of Polarization Monitoring in Terrestrial Optical Data Networks, Galileo conference: Fibre Optic Sensing in Geosciences, Catania, Italy, 16–20 Jun 2024, GC12-FibreOptic-8, https://doi.org/10.5194/egusphere-gc12-fibreoptic-8, 2024.
The MEGLIO project aims to observe seismic waves using coherent laser interferometry on an active telecommunication fiber network. Open Fiber, one of Italy's leading optic fiber infrastructure providers, promoted this experiment on a buried optic cable connecting Ascoli Piceno and Teramo, Italy, spanning approximately 30 km.
The cable's route, passing through roads with moderate traffic, bridges, viaducts, and urban areas, poses challenges due to anthropogenic noise. However, one of the goals of the experiment aims to demonstrate the sensitivity of the measurement technique in real-world telecommunication networks. Nevertheless, many earthquakes with Ml2+ magnitudes have been recorded at different distances from the fiber optic cable.
The physical quantity measured here is the time variation of a phase-shift, i.e. an angle. The objective of the presentation is to show the waveform signatures of seismic waves on this type of measure and their frequency spectra from a seismological perspective. We also may quantify seismological attributes such as seismic phase arrival times, frequency content, and earthquake magnitudes. Furthermore, we compare the interferometric data with traditional seismic recordings from nearby velocimeter sensors.
In essence, the MEGLIO experiment seeks to advance seismic monitoring capabilities by leveraging existing telecommunication infrastructure. Through comprehensive waveform analysis and seismological attribute measurement, valuable insights into earthquake characteristics can be obtained, contributing to improved our seismic monitoring efforts.
How to cite: Herrero, A., Govoni, A., Margheriti, L., Vassallo, M., donatello, S., Clivati, C., Brenda, D., Hovsepyan, M., Bertacco, E., Concas, R., Levi, F., Mura, A., Carpentieri, F., and Calonico, D.: Advancing Seismic Monitoring using Interferometric Data Recorded on Telecom Fiber Networks, Galileo conference: Fibre Optic Sensing in Geosciences, Catania, Italy, 16–20 Jun 2024, GC12-FibreOptic-43, https://doi.org/10.5194/egusphere-gc12-fibreoptic-43, 2024.
The ubiquitous optical fiber infrastructure already installed for telecommunications purposes represents a precious asset for pervasive sensing. The telecom fiber plan can be used not only for controlling the network integrity itself, but also for monitoring the road traffic, for large breaches and damages detection in civil structures, for the supervision of utilities health, and for the prompt detection of seismic and natural hazards. Nowadays, systems based on distributed acoustic sensing (DAS) are successfully applied also in telecom links, to provide measurements with very high resolution and spatial accuracy in localization. In particular, DAS systems appear very attractive to operate as fiber seismometers for early earthquake detection. However, DAS back-scattering approach requires complex and expensive DSP and storage of a huge amount of data, not generally compatible with the budget of large-scale sensing applications. Interferometric solutions constitute a possible alternative, but usually they employ ultra-stable laser sources, characterized by laser coherence length longer than the sensing fiber to monitor.
For extensive applications of optical sensing in the pervasive fiber telecom infrastructure, sustainable in terms of cost, energy efficiency and reliability, we propose to adopt the interferometric approach, but constructing the interferometer itself directly embedded inside the multi-fiber telecom cable, where two fiber operate as interferometric arms. No stringent requirement is necessary for the laser sources and typical telecom DFB lasers are employed together with a simple detection scheme.
In this paper we show how the proposed “in-cable” sensor is used over the deployed telecom network to monitor geo-hazards. In particular, its operation to detect risks of landside affecting the safety of a railway in the north side of the Lake Iseo, Lombardia is presented. Two standard single-mode fibers of the 48-fiber telecom cable installed in a conduit under the sidewalk running alongside the railroad tracks by an Italian operator are employed to realize the sensor. Not only traffic events such as travelling trains, car passages on a railroad crossings and pedestrians crossing the track are detected, but above all the fall of rocks obstructing the tracks are identified. Suitable machine-learning allows to classify and discriminate dangerous events for the safety of the railway from nuisances caused by the noisy and hostile environment, that can be sources of annoying false alarms. Providing integral measurements, this interferometric sensor does not localize the event, but gives early warning of possible risks for the railway, detecting in real time landslides and notifying the alarm in a proactive way. Other applications related to the monitoring of tunnels and viaducts, river embankments and shallow landslides triggered by rainfalls are also demonstrated.
This work was partially supported by the Italian Government through project PRIN 2022 SURENET and by the European Union under the Italian National Recovery and Resilience Plan (NRRP) of NextGeneration EU, partnership on “Telecommunications of the Future” (PE00000001 - program “RESTART”) in the project SENSING NET.
How to cite: Morosi, J., Brunero, M., Ferrario, M., Fasano, M., Madaschi, A., and Boffi, P.: Landside hazards detection by interferometric sensor over deployed telecom fibers for railway safety surveillance, Galileo conference: Fibre Optic Sensing in Geosciences, Catania, Italy, 16–20 Jun 2024, GC12-FibreOptic-74, https://doi.org/10.5194/egusphere-gc12-fibreoptic-74, 2024.
This article delves into the concept of Network Sensing, first by revisiting sensor networks and telecommunications networks (Telco networks) and analyzing the informational content they convey.
Sensor networks interconnect sensor devices designed to measure physical quantities, yielding unintentional informational content from monitored events like temperature, pressure, light, motion, vibrations, and other environmental or industrial parameters.
Conversely, Telco networks, whether human-to-human, human-to-machine, or machine-to-machine, transport intentional informational content such as voice, data, and video.
Sensor networks exhibit a variable and distributed geometry, adaptable to monitored events or areas, allowing for flexible sensor density and distribution based on specific application needs. In contrast, Telco networks feature a predefined and structured geometry with specific connection points (e.g., cell towers, telephone exchanges, network nodes), ensuring reliable coverage and reach, optimized for data flow and service quality.
This difference in network geometry requires precise connection points for Telco networks (e.g., individuals, cities, nations, servers, clouds), while the geometry of sensor networks depends on events, sometimes necessitating a uniform and costly distribution due to event dispersion.
Traditionally, overlaying these networks results in cost duplication, hindering the development of techniques that, while advantageous in measured scale, lack economic efficiency.
Projects like Meglio [1] aim to reuse Telco infrastructure and geometry for event collection, such as seismic activities. The convergence of sensor and Telco networks introduces Network Sensing, explored in 6G wireless networks and recently implemented in fiber optic networks for applications like seismic alarms. This convergence could halve implementation costs, rendering initiatives sustainable. However, the effectiveness in measuring certain events requires further analysis through future experimentation.
Reference
[1] Simone Donadello et al.: Earthquake observatory with coherent laser interferometry on the telecom fiber network , arXiv:2307.06203v1 [physics.geo-ph] 12 Jul 2023
How to cite: Carpentieri, F., Hovsepyan, M., and Brenda, D.: Exploring Network Sensing for Cost-Effective Event Detection, Galileo conference: Fibre Optic Sensing in Geosciences, Catania, Italy, 16–20 Jun 2024, GC12-FibreOptic-53, https://doi.org/10.5194/egusphere-gc12-fibreoptic-53, 2024.
Many cities worldwide are threatened by flooding and sea level rise because of climate change. Early detection of potential threats is essential for safeguarding human lives and housing, as well as critical infrastructures. Continuous monitoring of the subsurface by analysis of surface waves recorded by roadside DAS systems that exploit preexisting telecommunication fibers can provide useful information at a low cost. In urban areas, vehicles transiting on city streets generate large amounts of broad-band (2-25 Hz) surface waves that propagate in the subsurface and can be readily used for continuous monitoring. We designed and successfully tested a targeted interferometry workflow capable of generating high signal-to-noise (SNR) virtual source gathers.
The first step in our workflow is to identify the path of vehicles transiting on roads close to the fiber cable. That can be accomplished by following the low-frequency strain signal caused by the quasi-static elastic deformation of the ground. The path is tracked using an algorithm based on Kalman filters. Because long and heavy vehicles generate lower frequency surface waves, we could also perform space deconvolution of the quasi-static signal to estimate the vehicle length and number of axels to improve the signal-to-noise ratio (SNR) at low frequencies. The second step is to perform targeted seismic interferometry in the time-space windows where the surface waves generated by the tracked vehicles are strongest. We found that about two hundred vehicles were sufficient to synthesize high SNR virtual source gathers. The temporal resolution of the measurements is thus of the order of hours, depending on traffic intensity and the SNR required by the specific monitoring application. We used the virtual gathers to generate phase and group velocity profiles. We also measured the amplitude decay as a function of offsets and frequencies to estimate surface-wave attenuations. The analysis of DAS data continuously recorded before, during, and after the heavy rains in California during the 2022-23 winter showed that seismic velocities decreased and attenuation increased as the rains saturated the ground, and they rebounded as the ground dried up. The reliability and high spatial-resolution of the measurements (order of tenth of meters) also enabled us to observe the difference in the seismic response between paved and lawn areas.
How to cite: Biondi, B. and Yuan, S.: Monitoring changes in subsurface seismic properties caused by heavy rains with a roadside DAS by targeted interferometry, Galileo conference: Fibre Optic Sensing in Geosciences, Catania, Italy, 16–20 Jun 2024, GC12-FibreOptic-42, https://doi.org/10.5194/egusphere-gc12-fibreoptic-42, 2024.
Ambient noise interferometry applied to Distributed Acoustic Sensing (DAS) arrays is an increasingly common approach to subsurface investigations. In this study, we show that analysis of urban seismic noise acquired on a DAS array can be used to track velocity variations caused by groundwater level changes in an alluvial aquifer.
We apply our methodology to the Crépieux-Charmy aquifer, a strategic site for the city of Lyon, France. This site provides more than 90% of the city's drinking water and uses a Managed Aquifer Recharge (MAR) system, which allows controlled recharge of the aquifer through infiltration basins. We analyzed four weeks of DAS ambient noise data recorded on a 3 km spiral DAS array surrounding an infiltration basin. During this period, a controlled water infiltration experiment was conducted by the site operators.
We used traffic noise in the 2-5 Hz frequency band and performed DAS-based time-lapse surface wave tomography of velocity variations in the area. We were then able to map relative changes in seismic velocity in the vadose zone. Comparison of point-scale water level measurements from piezometers and adjacent cells in the velocity variation maps shows good agreement between the two observables. These velocity variations are directly related to the water table variations and to residual water saturation changes within the unsaturated zone.
This pilot application demonstrates the potential for groundwater monitoring in aquifer systems using DAS combined with seismic interferometry.
How to cite: Nziengui Bâ, D., Coutant, O., Jestin, C., and Lanticq, V.: Monitoring groundwater dynamics in the Crepieux-Charmy water catchment using DAS-based surface wave tomography, Galileo conference: Fibre Optic Sensing in Geosciences, Catania, Italy, 16–20 Jun 2024, GC12-FibreOptic-55, https://doi.org/10.5194/egusphere-gc12-fibreoptic-55, 2024.
The vulnerability of urban assets, encompassing soils, buildings, and infrastructure, is intricately linked to human activities, environmental exposure, and societal vulnerabilities. By employing Distributed Acoustic Sensing (DAS) technology on telecom fiber networks, we have developed an information model that facilitates data extraction, exchange, and networking to enhance decision-making regarding civil engineering assets. In collaboration with the APRR-AREA French company, our focus lies on two long-span bridges situated along a 25 km stretch of telecom optic fiber on the A40 motorway concession — known as the "autoroute des Titans" — in eastern France. Our objective is to characterize the deformation of these structures under heavy vehicle traffic, aiming at discerning behavioral disparities between spans and identifying potential plasticization zones. Employing a standard beamforming approach, we track vehicles using DAS data records. A statistical analysis of signal amplitudes helps to establish standard deformation thresholds and to detect anomalous deformation events. We conduct diagnostics to identify the origins of these events through DAS signals identification and classification. Simultaneously, we continuously monitor the vibrational characteristics of the structures, including frequencies, damping, and modal shapes, to ascertain if traffic-induced deformations enter the plastic regime. Throughout the 68-hour acquisition campaign, we tracked 5 423 vehicles with weight ranging from 2 568 to 73 123 kilograms. On one of the bridges, our analysis revealed 402 events exceeding the 5-sigma threshold, 58 surpassing the 10-sigma threshold, 33 exceeding the 12-sigma threshold, and 4 surpassing the 15-sigma threshold. We will analyse if these events coincide temporally and spatially with those detected with conventional long-base extensometers deployed all along the bridge deck. There is no indication of plastic deformation. This study highlights the potential of utilizing DAS technology applied to telecom optic fibers to complement specialized instrumentation for monitoring the behavior of long-span bridges.
How to cite: Rodet, J., Tauzin, B., Amin Panah, M., and Pittet, R.: Urban Dark Fiber Distributed Acoustic Sensing for Bridge Monitoring under Road Traffic Sollicitation, Galileo conference: Fibre Optic Sensing in Geosciences, Catania, Italy, 16–20 Jun 2024, GC12-FibreOptic-39, https://doi.org/10.5194/egusphere-gc12-fibreoptic-39, 2024.
Multiple input multiple output (MIMO) distributed fiber Sensing (DFS) is an innovative digital approach to phase-OTDR derived from technologies used in long-haul transmission over both terrestrial and submarine telecom networks. The probing signal is composed of digital codes that modulate in phase a highly coherent laser source over two orthogonal polarization axes, and the Rayleigh backscattered optical field is captured by a coherent mixer set in a homodyne configuration. This technique estimates, after digital processing, the backscattered signal without polarization fading effect and under a Jones matrix form, so giving access to the intensity, the local phase and the state of polarization along the fiber link under test. The link is continuously probed, which allows to monitor the local phase changes induced by mechanical events occurring in the fiber vicinity over a maximal bandwidth given by length of the monitored fiber link. We demonstrated the MIMO-DFS capabilities over links up to 100km with a gauge length of 10 meters and a capture of events linearly to disturbance pressure, in a microphone-like way, over a 200Hz bandwidth. The detection threshold, or noise floor, increases along the fiber length and was shown to be drastically lowered compared with standard DFS techniques which probe the fiber over one polarization axis only. The 100km figure achieved will be further improved soon by enhancing the stability of the laser source.
The MIMO-DFS technique has been designed to be compliant with telecom networks in a way so that a fiber can be monitored using one WDM channel without impacting the traffic rate propagating over adjacent WDM channels. We recently conducted a field trial using a telecom operator active network in Saudi Arabia. The purpose was to early detect mechanical threats that may lead to a traffic disruption. We provoked mechanical events by means of jackhammer and excavator in the vicinity of a 57km deployed cable buried two meters depth, both in a city area and in the desert, at distance of 15 and 30km from the fiber start respectively. The aim of the paper is to highlight the ability to detect, localize and even recognize the various noise sources under test in the context of a realistic deployed network, thanks to the outstanding sensitivity of the sensing technique. Beyond early detection of human induced threats for telecom networks integrity, the MIMO-DFS approach is also suited to detect much more critical environmental threats such as seisms with potential impact on people safety.
How to cite: Dorize, C.: MIMO-DFS for detection-localization-identification of mechanical threats over existing telecom networks, Galileo conference: Fibre Optic Sensing in Geosciences, Catania, Italy, 16–20 Jun 2024, GC12-FibreOptic-46, https://doi.org/10.5194/egusphere-gc12-fibreoptic-46, 2024.
In the last few years, a number of technologies to use fiber optic cables as sensing devices have been established, among them Distributed Acoustic Sensing (DAS) and State-of-Polarisation (SoP). The potential of these technologies for monitoring a range of Earth System parameters in submarine cables has been demonstrated through several pilot experiments, but full integration with telecommunication infrastructure has not yet been achieved. The SUBMERSE (SUBMarinE cables for ReSearch and Exploration) project links Research and Education Networks (RENs), universities, research institutes and industry to establish multi-method monitoring along submarine optical telecommunication cables at several key oceanic cable routes branching off from Sines in Portugal, Madeira, Svalbard and in the Ionian Sea, and in addition the Transatlantic cable between Fortaleza and Sines. Those pilot sites should serve as a blueprint for establishing continuous monitoring services along many more cables.
The project comprises technical developments for integrating DAS and SoP measurements, for establishing differential SoP measurements between repeaters and for operating DAS in a co-existence mode, i.e., in fibers also carrying telecommunications traffic. Furthermore, a range of geoscientific and marine biology use cases are included, which seek to establish code/services for monitoring earthquakes and tsunamis, tracking whales, measuring the sea state and other Earth System variables. The data collected by SUBMERSE will be distributed according to FAIR principles through established community-specific distribution channels such as EIDA for seismological data, with exceptions for security sensitive time periods, spatial or frequency ranges.
The presentation will present some example data and methodological developments in the context of this project. Furthermore, an outlook on the seismological real-time and archive products will be provided.
How to cite: Tilmann, F., Atherton, C., Asero, C., Evangelidis, C., Charalampakis, M., Landrø, M., Rondenay, S., Ottemöller, L., Maji, V., Corela, C., Matias, L., Custódio, S., Schlaphorst, D., Strollo, A., Xiao, H., Papapostolou, A., Perivoliotis, L., Morten, J. P., Heinloo, A., and Loureiro, A. and the SUBMERSE WP3 team (additional members): Towards continuous fibre-optic monitoring in the oceans with submarine telecommunications cables – the SUBMERSE project, Galileo conference: Fibre Optic Sensing in Geosciences, Catania, Italy, 16–20 Jun 2024, GC12-FibreOptic-31, https://doi.org/10.5194/egusphere-gc12-fibreoptic-31, 2024.
SAFAtor is planned as a major infrastructure project (30 millions Euros) of the German Helmholtz Association which aims at effectively closing the observational gap in the continental shelf, slope, and deep oceans by using new cable technologies. SAFAtor (SMART Cables And Fiber-optic Sensing Amphibious Demonstrator) will have three main outcomes: 1) SAFAtor will establish DAS permanent offshore monitoring at three existing Plate Boundary Observatories located in coastal areas (Northern Chile, the Marmara Sea and Etna volcano, see the presentation of Krawczyk et al.). This integration will build on outcomes from the European SUBMERSE project (to finish in 2026) and will enable unprecedented monitoring of tectonic and volcanic events (landslides, observation of the preparation phase of strong earthquakes on submarine faults close to the coast, new early warning systems for earthquakes and tsunamis, and submarine volcanic processes). 2) SAFAtor will provide a working demonstrator by equipping a submarine telecommunication cable with robust sensor technology packages to measure temperature, absolute pressure and ground acceleration on the sea floor. The location of the demonstrator cable will be discussed with the international community and chosen to maximize scientific exploitation. 3) SAFAtor will finally develop a FAIR infrastructure necessary to process, archive and distribute these new DAS and cable data, and enable the global user community to select and process the data services in a user-friendly and interoperable way. The development of these novel DAS data management strategies has already started (EU project GeoInquire https://www.geo-inquire.eu). This new data infrastructure will be integrated into national German data services (Helmholtz Data-Hub, NFDI4Earth) and contribute to European data infrastructures (e.g., EPOS, EMSO, Copernicus Marine Services). Such new infrastructure and data services have the potential to profoundly change geohazards warning systems, ocean and marine life observations and revolutionize the development of models used to analyze and predict climate change and the variability of ocean currents.
How to cite: Cotton, F., Krawczyk, C., Tilmann, F., Wallace, L., and team, T. S.: Closing the Ocean Data Gap by combined fibre-optics, SMART cable sensing and novel data management strategies., Galileo conference: Fibre Optic Sensing in Geosciences, Catania, Italy, 16–20 Jun 2024, GC12-FibreOptic-35, https://doi.org/10.5194/egusphere-gc12-fibreoptic-35, 2024.
The application of ambient noise interferometry to distributed acoustic sensing (DAS) data recorded on existing telecommunication networks provides a promising opportunity for effectively imaging the urban subsurface with high resolution at local and regional scales. This approach holds significant potential for various applications, including assessing the suitability of the urban subsurface for safe utilization, such as in geothermal development, and evaluating risks associated with subsurface activities, particularly concerning geological hazards like subsidence and sinkholes. Such capabilities are essential for developing resilience strategies and mitigating potential impacts in urban environments. However, extracting coherent seismic signals from the ambient wavefield recorded by DAS in urban settings remains a challenge. One obstacle is the presence of diverse and complex noise sources, which are often unevenly distributed. These localized sources can introduce deviation into the result of ambient noise interferometry and generate nonphysical arrivals, complicating the analysis and interpretation of the results.
In this study, we present the analysis of 15 days of continuous passive DAS data recorded on a pre-existing fiber optic cable (dark fiber) spanning 11 km along a major urban road in Berlin, Germany. Our investigation reveals anthropogenic activities, predominantly traffic noise from vehicles and trains, as the primary seismic source. To retrieve Virtual Shot Gathers (VSGs), we apply interferometric analysis based on the cross-correlation approach. Before stacking, we design a selection scheme to identify high-quality VSGs, thereby optimizing the resulting stacked VSG. Then, Multichannel Analysis of Surface Waves (MASW) is applied to derive 1D shear-wave velocity models across successive array segments. We construct a 2D velocity model of the subsurface through the concatenation of individual 1D velocity models obtained from overlapping array subsections. This expansion into 2D necessitates automatically identifying high-quality VSGs, achieved through unsupervised learning methods such as clustering. This process is crucial for excluding transient incoherent and localized noise sources during selective stacking. To implement clustering, we initially reduce the dimensionality of the VSGs using principal component analysis. We then cluster the features within this reduced-dimensional space. Finally, we stack the VSGs in each cluster and select the best-stacked VSGs. We initially test the clustering algorithm on synthetic VSGs before applying it to DAS ambient noise field data to ensure its reliability and effectiveness in real-world scenarios.
The clustering results reveal distinct groups of VSGs that demonstrate consistent patterns across synthetic and field DAS datasets. These distinct groupings offer valuable insights into the temporal variations in human activities and allow a better understanding and interpretation of the recorded DAS ambient noise data, enabling the identification of viable ambient noise signals for further processing. Ultimately, this approach enhances the accuracy of dispersion measurements, enabling improved subsurface imaging in urban areas.
How to cite: Ehsaninezhad, L., Wollin, C., Rodríguez Tribaldos, V., and Krawczyk, C.: Leveraging DAS Ambient seismic noise interferometry and machine learning for 2D subsurface seismic imaging in an urban area , Galileo conference: Fibre Optic Sensing in Geosciences, Catania, Italy, 16–20 Jun 2024, GC12-FibreOptic-13, https://doi.org/10.5194/egusphere-gc12-fibreoptic-13, 2024.
To guarantee precise standards of effectiveness, efficiency and safety of an airport, the coordination of land-side and air-side operations is considered pivotal. Consequently, the corresponding interface infrastructure (apron) poses critical challenges in airport engineering due to the specific procedures and regulations required for its design, construction, and management.
Due to the extensive dimensions of an apron and the constant needs of aircrafts’ ground operations, highly efficient and consistent monitoring techniques are required to assist facility managers in both airport expansion projects and maintenance of existing assets. To assess the rigid pavement conditions of an apron, it is recommended to carry out remote sensing and multi-source non-destructive testing (NDT) surveys (generally with ground penetrating radar (GPR), heavy weight deflectometer (HWD) and visual inspections). Then, by a back-calculation process, it is possible to evaluate the resulting shear stress and total cumulative damage factor (CDF) assuming a mix traffic load.
Given the complexity of airport operations and the amount of heterogenous information collected, an interoperable digital twin offers an optimal procedural framework to strategically archive, organize and integrate the sampled parameters measured by each survey. Therefore, a digital informative model of an apron feeds on the outputs of the monitoring techniques to evaluate the degrading conditions of the asset, thus improving the reliability and accuracy of any assessment and decision-making process at land-side/air-side interfaces.
However, such an extensive survey campaign is expensive and impacts greatly on the operability of the airport, often resulting in delay or rescheduling. In addition, stresses are estimated through rational methods, generally a finite element model (FEM) approach that, despite resulting very reliable in simulating the mechanical behaviour of rigid pavement, can be computationally onerous and sometimes not reasonably applicable. Eventually, if the monitoring routines are not frequent and, accordingly, the geometrical and mechanical inputs are non-adequately calibrated, the potential misestimate of the structural health monitoring (SHM) parameters may undermine the effectiveness of any strategic decision taken forward.
In this context, fiber optic sensors have been identified as a possible solution to directly measure the shear stress or strain in rigid pavements. Indeed, the actual stress-strain characteristics can be measured by embedding fiber optic sensors into rigid pavements. Since the mechanical performances are continuously and directly monitored, the dataset is easily updated with the aim of feeding an apron’s digital twin without the need for even scheduling an actual survey. Moreover, it is possible to investigate current and alternative failure mechanisms of rigid pavements (generally associated to underestimation of mechanical loads and environmental factors, inaccurate model-measurement calibration). On the other hand, the application of fiber optic sensors into rigid pavements still stands as an open challenge, due to construction- and management-related issues.
Concluding, this study aims at exploring benefits and open challenges in implementing fiber optic sensors into rigid pavement, by investigating the current state-of-the-art’s installation, embedding, resistance and outputting issues emerged in relevant scientific experiences. Finally, this study puts the basis for the pioneering implementation of a digital twin of apron that is theoretically updated in real time.
How to cite: Pinto, R., Bianchini Ciampoli, L., and Benedetto, A.: Application of fiber optic sensors to the digitalization and management of airport rigid pavement, Galileo conference: Fibre Optic Sensing in Geosciences, Catania, Italy, 16–20 Jun 2024, GC12-FibreOptic-64, https://doi.org/10.5194/egusphere-gc12-fibreoptic-64, 2024.
