132 research outputs found
Fracture thickness from GPR measurements
Rock investigation is definitely not a recent application of Ground Penetrating Radar (GPR) technique, as first studies date back to the seventies. However, only in the last decade research activities have started to address GPR characterization of rock fracture parameters, namely aperture and filling material. Rock fractures can generally be considered as thin beds, i.e., two interfaces whose distance is smaller than radar range resolution. Most of the past studies analyzed thin-bed response in the time domain, addressing time resolution, the linear relationship between bed thickness and reflected amplitude, and the derivative effect upon the incident signal. Amplitude calibration might permit to estimate fracture features for arbitrarily thin beds, but it is difficult to achieve and could be applied only to favorable cases. In this paper we explore the possibility to estimate fracture thickness and filling in the frequency domain by means of GPR. After reviewing the theoretical aspects of thin-bed response, we processed GPR data collected on ornamental marble blocks, where fractures of known aperture were simulated. We also performed numerical modelling tests to support the analysis of real datasets. Our approach consists of a 4-step procedure in which deterministic deconvolution is used to retrieve magnitude and phase thin-bed response in the selected frequency band. The procedure provided satisfactory outcomes when applied to real as well as to modelled thin-bed reflections. Results are encouraging and suggest that, under favorable circumstances, GPR could be a fast and effective tool to determine fracture parameters in non-destructive manner. Further testing is needed in order to fine-tune the processing sequence and to extend the validity of our preliminary findings to more complex case studies
Analysis of thin fractures with GPR: from theory to practice
Whenever we perform a GPR survey to investigate a rocky medium, being the ultimate purpose of the survey either to study the stability of a rock slope or to determine the soundness of a quarried rock block, we would like mainly to detect any fracture within the investigated medium and, possibly, to estimate the parameters of the fractures, namely thickness and filling material. In most of the practical cases, rock fracture thicknesses are very small when compared to the wavelength of the electromagnetic radiation generated by the GPR systems. In such cases, fractures are to be considered as thin beds, i.e. two interfaces whose distance is smaller than GPR resolving capability, and the reflected signal is the sum of the electromagnetic reverberation within the bed. According to this, fracture parameters are encoded in the thin bed complex response and in this work we propose a methodology based on deterministic deconvolution to process amplitude and phase information in the frequency domain to estimate fracture parameters. We first present some theoretical aspects related to thin bed response and a sensitivity analysis concerning fracture thickness and filling. Secondly, we deal with GPR datasets collected both during laboratory experiments and in the facilities of quarrying activities. In the lab tests fractures were simulated by placing materials with known electromagnetic parameters and controlled thickness in between two small marble blocks, whereas field GPR surveys were performed on bigger quarried ornamental stone blocks before they were submitted to the cutting process. We show that, with basic pre-processing and the choice of a proper deconvolving signal, results are encouraging although an ambiguity between thickness and filling estimates exists when no a-priori information is available. Results can be improved by performing CMP radar surveys that are able to provide additional information (i.e., variation of thin bed response versus offset) at the expense of acquisition effort and of more complex and tricky pre-processing sequences
Experimental analysis of seasonal processes in shallow landslide in a snowy region through downscaled and in situ observation
The frequency and intensity of heavy precipitation events increased since the mid-20th century and, considering the climate crisis, it is important also to analyze the effects of processes and events that lead to faster snow mantle melting cycles in mountain areas.
Shallow landslides are induced by extreme hydrological events such as the occurrence of short and intense rainfall or by events of medium intensity but prolonged over time. Such slips involve generally reduced portions of land both in area and in thickness, however, they are dangerous due to the absence of warning signals and the lack of knowledge regarding their possible evolution.
This work deals with the experimental study of these landslides through the laboratory simulations on a small-scale slope, reproduced at the LIMAG Lab - Laboratory of mountain hydraulics and applied geology of the Lecco Campus and in situ seasonal processes observation at a mountain closed basin nearby Champoluc village in Aosta Valley region.
The central objective is to study the evolution of shallow landslides in reduced scale caused by external factor as snowmelt and rainfall and to compare the observations done in laboratory with the ones in situ. In order to investigate the behaviour of shallow landslides in these critical conditions, a series of sensors have been installed on the simulator. This technology includes three modified pressure transmitters for the pore water pressure evaluation which have been accompanied by other support instrumentation consisting of GoPro’s cameras, TDR (Time Domain Reflectometry) and georesistivimeter; all of them provide a cross check of phenomena processes.
Throughout the downscaled simulations with snow cover it was possible to observe several processes. The direct interaction between snow and ground does not favor the infiltration of a large amount of water. The protective role of snow lies in keeping the first film of soil at 0 degrees and loading the soil by decreasing its infiltrative capacity; this no longer occurs when the water melted by the snow flows downstream and begins to infiltrate into uncovered and warmer soils.
Without thermal or overload barriers, the water pours into the ground. Therefore, a potential susceptible area can be the subject of different filtering and infiltrative contributions from upstream, saturating quickly and collapsing.
These laboratory experiments are the starting point for the in-situ analyses and provide a comparison with the observations made by means of ad hoc instrumentation set up at the Champoluc station. Highly detailed information is obtained concerning the density and thickness of the snowpack during seasonal processes. These contribute to defining the hydrogeological processes within the terrain, already studied in the laboratory, and to establishing the water balance
The risk of collapse in abandoned mine sites: the issue of data uncertainty
Ground collapses over abandoned underground mines constitute a new environmental risk in the world. The high risk associated with subsurface voids, together with lack of knowledge of the geometric and geomechanical features of mining areas, makes abandoned underground mines one of the current challenges for countries with a long mining history. In this study, a stability analysis
of Montevecchia marl mine is performed in order to validate a general approach that takes into account the poor local information and the variability of the input data. The collapse risk was evaluated through a numerical approach that, starting with some simplifying assumptions, is able to provide an overview of the collapse probability. The nal results is an easy-accessible-transparent summary graph that shows the collapse probability. This approach may be useful for public administrators called upon to manage this environmental risk. The approach tries to simplify this complex problem in order to achieve a roughly risk assessment, but, since it relies on just a small amount of information, any nal user should be aware that a comprehensive and detailed risk scenario can be generated
only through more exhaustive investigations
The risk of collapse in abandoned mine sites: the issue of data uncertainty
Ground collapses over abandoned underground mines constitute a new environmental risk in the world. The high risk associated with subsurface voids, together with lack of knowledge of the geometric and geomechanical features of mining areas, makes abandoned underground mines one of the current challenges for countries with a long mining history. In this study, a stability analysis
of Montevecchia marl mine is performed in order to validate a general approach that takes into account the poor local information and the variability of the input data. The collapse risk was evaluated through a numerical approach that, starting with some simplifying assumptions, is able to provide an overview of the collapse probability. The nal results is an easy-accessible-transparent summary graph that shows the collapse probability. This approach may be useful for public administrators called upon to manage this environmental risk. The approach tries to simplify this complex problem in order to achieve a roughly risk assessment, but, since it relies on just a small amount of information, any nal user should be aware that a comprehensive and detailed risk scenario can be generated
only through more exhaustive investigations
Understanding slope behavior through microseismic monitoring
It is well known that microseismic activity originates as an elastic stress wave at locations where the material is mechanically unstable. Monitoring techniques focusing on this phenomenon have been studied for over seventy years and are now employed in a wide range of applications. As far as the study of unstable slope is concerned, microseismic monitoring can provide real-time information about fracture formation, propagation and coalescence and may be an appropriate solution to reduce the risk for human settlements when structural mitigation interventions (e.g., rock fall nets and ditches) cannot cope with large rock volumes and high kinetic energies. In this work we present the datasets collected in a 4-year period with a microseismic monitoring network deployed on an unstable rock face in Northern Italy. We mainly focus on the classification and the interpretation of collected signals with the final aim of identifying microseismic events related to the kinematic and dynamic behavior of the slope. We have analyzed signal parameters both in time and frequency domains, spectrograms, polarization of 3-component recordings supported by principal component analysis. Clustering methodologies have been tested in order to develop an automatic classification routine capable to isolate a cluster with most of the events related to slope behavior and to discard all disturbances. The network features both geophones and meteorological sensors so that we could also explore the correlation between microseismic events and meteorological datasets, although no significant relationships emerged. On the contrary, it was found that the majority of the events collected by the network are short-time high-frequency signals generated by electromagnetic activity caused by near and far thunderstorms. Finally, we attempted a preliminary localization of the most promising events according to an oversimplified homogeneous velocity model to get a rough indication about the regions of the monitored area that could be prone to collapse
Analysis of microseismic signals collected on an unstable rock face in the Italian Prealps
In this work we present the analysis of more than 9000 signals collected from February 2013 to January 2016 by a microseismic monitoring network installed on a 300 m high limestone cliff in the Italian Prealps. The investigated area was affected by a major rockfall in 1969 and several other minor events up to nowadays. The network features five three-component geophones and a weather station and can be remotely accessed thanks to a dedicated radio link. We first manually classified all the recorded signals and found out that 95 per cent of them are impulsive broad-band disturbances, while about 2 per cent may be related to rockfalls or fracture propagation. Signal parameters in the time and frequency domains were computed during the classification procedure with the aim of developing an automatic classification routine based on linear discriminant analysis. The algorithm proved to have a hit rate higher than 95 per cent and a tolerable false alarm rate and it is now running on the field PC of the acquisition board to autonomously discard useless events. Analysis of lightning data sets provided by the Italian Lightning Detection Network revealed that the large majority of broad-band signals are caused by electromagnetic activity during thunderstorms. Cross-correlation between microseismic signals and meteorological parameters suggests that rainfalls influence the hydrodynamic conditions of the rock mass and can trigger rockfalls and fracture propagation very quickly since the start of a rainfall event. On the other hand, temperature seems to have no influence on the stability conditions of the monitored cliff. The only sensor deployed on the rock pillar next to the 1969 rockfall scarp typically recorded events with higher amplitude as well as energy. We deem that this is due to seismic amplification phenomena and we performed ambient noise recording sessions to validate this hypothesis. Results confirm that seismic amplification occurs, although we were not able to identify any spectral peak with confidence because the sensors used are not suitable for this task. In addition, we found out that there is a preferential polarization of the wave field along the EW direction and this is in agreement with the geological analysis according to which the pillar is overhanging towards the 1969 rockfall scarp and may preferentially evolve in a wedge failure. Event location was not possible because of the lack of a velocity model of the rock mass. We tried to distinguish between near and far events by analysing the covariance matrix of the three-component recordings. Although the parameters and the outcomes of this analysis should be evaluated very carefully, it seems that about 90 per cent of the considered microseismic signals are related to the stability conditions of the monitored area
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