1,721,044 research outputs found
Approaches of data analysis from multi‐parametric monitoring systems for landslide risk management
Full text linkIn the last decades, several approaches were proposed accounting for early warning
systems to manage in real time the risks due to fast slope failures where important
elements, such as structures, infrastructures and cultural heritage are exposed. The
challenge of these approaches is to forecast the slope evolution, thus providing alert
levels suitable for managing infrastructures in order to mitigate the landslide risk and
reduce the “response” time for interventions.
Three different strategies can be defined in this regard: an Observation‐Based
Approach (OBA), a Statistic‐Based Approach (SBA) and a Semi‐Empirical Approach
(SEA). These approaches are focused on searching relations among destabilizing
factors and induced strain effects on rock mass.
At this aim, some experiments are being performed at different scales in the
framework of consulting activities and research projects managed by the Research
Centre for the Geological Risk (CERI) of the University of Rome “Sapienza”. These
experiments are testing different kind of sensors including extensometers, strain
gauges, rock‐thermometers, interferometers, optical cams connected to Artificial
Intelligence (AI) systems, for detecting changes in rock properties and detecting stressstrain
changes, as well as pluviometers, anemometers, hygrometers, air‐thermometers,
micro‐ or nano‐ accelerometers and piezometers for detecting possible trigger of
deformational events.
The results of this Ph.D. thesis demonstrate that the data analysis methods allowed
the identification of destabilizing actions responsible for strain effects on rock mass at
different dimensional scale and over several time‐window, from short‐ to long‐ period
time scale. Furthermore, the three approaches were to be suitable to recognize
precursor signals of rock mass deformation and demonstrated the possibility to
provide an early warning
Detection of nanoseismic events related to slope instabilities in the quarry district of Coreno Ausonio (Italy)
Full text linkLe cave per l’estrazione di materiale roccioso rappresentano contesti in cui possono aver luogo eventi di instabilità gravitativa causati dalle continue sollecitazioni cui sono soggette le pareti produttive, principalmente connesse alle vibrazioni dovute alle esplosioni necessarie alle operazioni di disgaggio. La necessità di gestione del rischio da frana per la salvaguardia del personale impegnato nell’attività estrattiva ha portato, nel tempo, alla richiesta di attivare sistemi di monitoraggio nelle aree di coltivazione mineraria e di cava.
Nel presente lavoro il monitoraggio nanosismometrico, una tecnica di geofisica passiva recentemente sviluppata per le indagini di microsismicità, è stato impiegato nel distretto di cave a cielo aperto di Coreno Ausonio (in provincia di Frosinone). Il monitoraggio nanosismometrico consente l’individuazione e la localizzazione di deboli eventi sismici, fino a magnitudo locale (ML) nell’ordine di -3, attraverso l’impiego di quattro sensori sismometrici disposti secondo una specifica geometria di array detta SNS (Seismic Navigation System).
Dopo aver individuato una cava in cui erano programmate esplosioni per la volata delle pareti in roccia, nel corso del 2013 sono state organizzate 3 campagne di acquisizione durante tre giornate, pianificate in modo da monitorare l’area in un periodo compreso da qualche ora prima dell’esplosione alle 24 ore successive. Su una parete della cava non più produttiva è stato effettuato un rilevamento geologico-tecnico che ha permesso di individuare 4 principali sistemi di discontinuità e caratterizzarli in termini di giacitura, resistenza, rugosità, apertura, spaziatura e condizioni idrauliche secondo gli standard ISRM (1978). L’analisi di stabilità della parete in esame, tenuto conto della sua orientazione, ha restituito una scarsa propensione ad eventi di instabilità.
Analizzando mediante il software NanoseismicSuite i dati sismometrici acquisiti è stato possibile ottenere i “supersonogrammi”, ovvero particolari spettrogrammi auto-adattanti alle variazioni del rumore sismico di fondo, dai quali sono state definite alcune caratteristiche specifiche di forma d’onda per diverse tipologie di eventi. In base ai supersonogrammi, è stato possibile individuare e localizzare 15 esplosioni, di cui 3 provenienti dalla cava di riferimento e 12 da cave adiacenti del distretto, e 27 deboli eventi di instabilità gravitativa, distinti in 23 eventi di collasso e 4 rotture legate alle fratturazione dell’ammasso roccioso. Le 3 esplosioni avvenute nella cava di riferimento, e quindi aventi coordinate di origine nota, sono state utilizzate per calibrare il modello di sottosuolo, successivamente impiegato per localizzare gli altri eventi registrati.
Le rotture sono risultate originate in diverse zone del distretto estrattivo, mentre gli eventi di collasso sono stati localizzati in una specifica area e risultano essere avvenuti prevalentemente in un limitato intervallo di tempo a seguito delle 9 esplosioni registrate nella campagna del 26-27 luglio 2013. Non è stato possibile, invece, individuare eventi riconducibili ad instabilità negli orari di attività di cava a causa dell’elevato livello di rumore apportato dagli strumenti per l’estrazione e la lavorazione del materiale roccioso. Si è escluso che gli eventi di collasso fossero riconducibili direttamente all’attività di estrazione sia perché registrati al di fuori dell’orario di lavorazione delle cave sia perché, analizzando l’intera registrazione per intervalli orari, le frequenze tipiche dei macchinari di lavorazione non sono risultate energizzante. La zona di origine è risultata essere un’area nella quale sono stati rinvenuti detrito sciolto costituito da blocchi eterometrici ed una parete non in coltivazione con medesime caratteristiche delle discontinuità rispetto alla parete sulla quale era stato effettuato il rilevamento geologico-tecnico, ma con diversa orientazione.
In definitiva, la fase di sperimentazione ha restituito dei risultati di indubbio interesse consentendo di mettere in evidenza alcune limitazioni del monitoraggio nanosismometrico nel contesto preso in esame, in particolare legate all’eccessiva rumorosità registrata nelle ore di attività di cava. La tecnica appare, comunque, un utile strumento di monitoraggio per i fenomeni gravitativi di debole intensità, in grado di contribuire alla gestione del rischio da frana in aree ad elevata attività antropica ed in ambienti naturalmente predisposti ad instabilità gravitative che possono interessare pareti in roccia.Nanoseismic monitoring is a passive geophysical technique used to identify and locate weak seismic events (down to local magnitudes, ML, around -3). This technique was applied in the open-pit quarry district of Coreno Ausonio (central Italy) to detect possible gravity-induced slope instabilities resulting from quarry rock blasting. After identifying an active quarry, an engineering-geological survey was carried out to characterise the jointed rock mass on an abandoned wall in front of the quarry. Four main joint sets were surveyed and their geometric and mechanical properties were measured in order to carry out stability analyses that evidenced scarce proneness to failure of the investigated wall. The analysis of seismic records obtained during three monitoring surveys, performed through the NanoseismicSuite software, made it possible to detect and characterise 15 blasts, of which 3 from the reference quarry and 12 from nearby quarries within the district, as well as 27 weak slope instability events (23 collapses and 4 failures). While failures originated from different areas of the quarry district, collapses occurred in a site characterised by an abandoned quarry having a wall more prone to gravity-induced instabilities than the one previously characterised
Rock falls impacting railway tracks. Detection analysis through an artificial intelligence camera prototype
Full text linkDuring the last few years, several approaches have been proposed to improve early warning systems for managing geological risk
due to landslides, where important infrastructures (such as railways, highways, pipelines, and aqueducts) are exposed elements.
In this regard, an Artificial intelligence Camera Prototype (AiCP) for real-time monitoring has been integrated in a multisensor
monitoring system devoted to rock fall detection. An abandoned limestone quarry was chosen at Acuto (central Italy) as test-site
for verifying the reliability of the integratedmonitoring system. A portion of jointed rockmass, with dimensions suitable for optical
monitoring, was instrumented by extensometers. One meter of railway track was used as a target for fallen blocks and a weather
station was installed nearby. Main goals of the test were (i) evaluating the reliability of the AiCP and (ii) detecting rock blocks that
reach the railway track by the AiCP. At this aim, several experiments were carried out by throwing rock blocks over the railway
track. During these experiments, the AiCP detected the blocks and automatically transmitted an alarm signal
Investigating rock mass failure precursors using a multi-sensor monitoring system. Preliminary results from a test-site (Acuto, Italy)
Full text linkIn the last few years, several approaches and methods have been proposed to improve early warning systems for managing risks due to rapid slope failures where important infrastructures are the main exposed elements. To this aim, a multi-sensor monitoring system has been installed in an abandoned quarry at Acuto (central Italy) to realise a natural-scale test site for detecting rock-falls from a cliff slope. The installed multi-sensor monitoring system consists of: i) two weather stations; ii) optical cam (Smart Camera) connected to an Artificial Intelligence (AI) system; iii) stress- strain geotechnical system; iv) seismic monitoring device and nano-seismic array for detecting microseismic events on the cliff slope. The main objective of the experiment at this test site is to investigate precursors of rock mass failures by coupling remote and local sensors. The integrated monitoring system is devoted to record strain rates of rock mass joints, capturing their variations as an effect of forcing actions, which are the temperature, the rainfalls and the wind velocity and direction. The preliminary tests demonstrate that the data analysis methods allowed the identification of external destabilizing actions responsible for strain effects on rock joints. More in particular, it was observed that the temperature variations play a significant role for detectable strains of rock mass joints. The preliminary results obtained so far encourage further experiments
Comparison of approaches for data analysis of multi-parametric monitoring systems. Insights from the Acuto test-site (Central Italy)
Full text linkThis paper deals with monitoring systems to manage the risk due to fast slope failures
that involve rock masses, in which important elements (such as infrastructures or cultural heritages,
among the others) are exposed. Three different approaches for data analysis were here compared
to evaluate their suitability for detecting mutual relations among destabilising factors, acting on
different time windows, and induced strain effects on rock masses: (i) an observation-based approach
(OBA), (ii) a statistics-based approach (SBA) and (iii) a semi-empirical approach (SEA). For these
purposes, a test-site has been realised in an abandoned quarry in Central Italy by installing a
multi-parametric monitoring sensor network on a rock wall able to record strain effects induced by
natural and anthropic forcing actions (like as temperature, rainfall, wind and anthropic vibrations).
The comparison points out that the considered approaches allow one to identify forcing actions,
responsible for the strain effects on the rock mass over several time windows, regarding a specific
size (i.e., rock block dimensional scale). The OBA was more suitable for computing the relations over
short- to medium time windows, as well as the role of impulsive actions (i.e., hourly to seasonal
and/or instantaneous). The SBA was suitable for computing the relations over medium- to long time
windows (i.e., daily to seasonal), also returning the time lag between forcing actions and induced
strains using the cross-correlation statistical function. Last, the SEA was highly suitable for detecting
irreversible strain effects over long- to very long-time windows (i.e., plurennial)
3D Remote survey of a rock wall hosting a multi-sensor monitoring system in a test-site (Acuto, Italy)
No full textA multi-sensor monitoring system was installed in an abandoned quarry at Acuto (Frosinone - Central Italy) to test multi-sensing and multi-parametric remote techniques for early warning in case of rock failures threating strategic infrastructures. The multi-sensor monitoring system consist in: i) a meteo-climatic system, including a conventional weather stations and an innovative TSA-BOX one; ii) a geotechnical system, including thermometer for the rock mass temperature, strain-gauges for micro-fractures of rock mass, extensometers on open joints for detecting stress-strain conditions; iii) a nanoseismic monitoring system was also temporary installed to detect low magnitude vibrations to be regarded as precursors of rock failures. To correctly design the multi-parametric monitoring system, the rock wall was scanned to identify the main joint sets. Three GPS monographs were preliminary obtained in order to spatially geocoding the rock wall. From November 2015 to May 2016 remote scanning surveys were carried out on the quarry face by two different approaches: i) topographic 3D survey by Leica Total Station; ii) optical survey by 3D photos technique analyzed by Structure from Motion technique. The topographic survey provided high definition geocoded point clouds. These outputs were compared with the ones obtained by the SFM technique on 3D photos to test their reliability. At this aim, a Gaussian bi-modal distribution of the surveyed distances was obtained from each measurement; the comparison among the so derived distributions demonstrates that the computed errors are negligible and the main differences result at the boundaries of the sampled 3D domain. This comparison encourages the use of the photography technology by SfM technique to obtain multi-temporal geocoded point clouds for change detection analyses to point out evidences of scar zones due to slope failures. This approach guarantees a very quick and accurate practice with easy management hardware and low software costs
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
3D Thermal Monitoring of Jointed Rock Masses through Infrared Thermography and Photogrammetry
Full text linkThe study of strain effects in thermally-forced rock masses has gathered growing interest from engineering geology researchers in the last decade. In this framework, digital photogrammetry and infrared thermography have become two of the most exploited remote surveying techniques in engineering geology applications because they can provide useful information concerning geomechanical and thermal conditions of these complex natural systems where the mechanical role of joints cannot be neglected. In this paper, a methodology is proposed for generating point clouds of rock masses prone to failure, combining the high geometric accuracy of RGB optical images and the thermal information derived by infrared thermography surveys. Multiple 3D thermal point clouds and a high-resolution RGB point cloud were separately generated and co-registered by acquiring thermograms at different times of the day and in different seasons using commercial software for Structure from Motion and point cloud analysis. Temperature attributes of thermal point clouds were merged with the reference high-resolution optical point cloud to obtain a composite 3D model storing accurate geometric information and multitemporal surface temperature distributions. The quality of merged point clouds was evaluated by comparing temperature distributions derived by 2D thermograms and 3D thermal models, with a view to estimating their accuracy in describing surface thermal fields. Moreover, a preliminary attempt was made to test the feasibility of this approach in investigating the thermal behavior of complex natural systems such as jointed rock masses by analyzing the spatial distribution and temporal evolution of surface temperature ranges under different climatic conditions. The obtained results show that despite the low resolution of the IR sensor, the geometric accuracy and the correspondence between 2D and 3D temperature measurements are high enough to consider 3D thermal point clouds suitable to describe surface temperature distributions and adequate for monitoring purposes of jointed rock mass
Nanoseismic monitoring of gravity-induced slope instabilities for the risk management of an aqueduct infrastructure in Central Apennines (Italy)
No full textA monitoring system is operative in the Peschiera Springs slope (Central Apennines, Italy) to mitigate the landslide risk related to the hosted main drainage plant of Rome aqueducts by providing alert warning. Such a strategy allows to avoid out-of-service episodes so reducing extra-costs of water distribution management. The Peschiera Springs slope is involved in a rock mass creep characterized by an average steady strain rate of 1 mm year-1 and responsible for several landforms including sinkholes, subvertical scarps and trenches. Moreover, an average aquifer discharge of 19 m3 s-1 causes an intense limestone dissolution concentrated in correspondence with release bands and discontinuities that dislodge the jointed rock mass. Since 2008, an accelerometric network has been operating within the slope; about 1300 microseismic local events were recorded up to now, distinguished in failures and collapses. A control index, based on frequency of occurrence and cumulative energy of the recorded microseismic events was defined to provide three levels of alert. In 2013, a temporary nanoseismic Seismic Navigation System (SNS) array was installed inside a tunnel of the drainage plant to integrate the pre-existent seismic
monitoring system. This array allowed to record 37 microseismic events, which locations are in good agreement with the evolutionary geological model of the ongoing gravitational slope deformation. In 2014, a permanent nanoseismic SNS array was installed in the plant
and allowed to record several sequences of underground collapses including more than 500 events. The nanoseismic monitoring system is allowing to: (1) increase the detection level of the monitoring system; (2) locate hypocentres of the events; and (3) detect precursors of
the strongest events
- …
