Search Results (25)

Landslides present a significant global hazard, resulting in substantial socioeconomic losses and casualties each year. Traditional monitoring approaches, such as geodetic, geotechnical, and geophysical methods, have limitations in providing early warning capabilities due to their inability to detect precursory subsurface deformations. In contrast, the acoustic emission (AE) technique emerges as a promising alternative, capable of capturing the elastic wave signals generated by stress-induced deformation and micro-damage within soil and rock masses during the early stages of slope instability. This paper provides a comprehensive review of the fundamental principles, instrumentation, and field applications of the AE method for landslide monitoring and early warning. Comparative analyses demonstrate that AE outperforms conventional techniques, with laboratory studies establishing clear linear relationships between cumulative AE event rates and slope displacement velocities. These relationships have enabled the classification of stability conditions into “essentially stable”, “marginally stable”, “unstable”, and “rapidly deforming” categories with high accuracy. Field implementations using embedded waveguides have successfully monitored active landslides, with AE event rates linearly correlating with real-time displacement measurements. Furthermore, the integration of AE with other techniques, such as synthetic aperture radar (SAR) and pore pressure monitoring, has enhanced the comprehensive characterization of subsurface failure mechanisms. Despite the challenges posed by high attenuation in geological materials, ongoing advancements in sensor technologies, data acquisition systems, and signal processing techniques are addressing these limitations, paving the way for the widespread adoption of AE-based early warning systems. This review highlights the significant potential of the AE technique in revolutionizing landslide monitoring and forecasting capabilities to mitigate the devastating impacts of these natural disasters. Full article

As a prevalent geological hazard in underground engineering, the accurate prediction of mine earthquakes is crucial for ensuring operational safety and enhancing mining efficiency. The deformation localization method effectively predicts the instability of disaster rocks, yet the timing of mine earthquakes remains understudied. This study established a correlation between rock deformation localization and seismic activity within mines through theoretical derivations. A predictive model algorithm for forecasting mine earthquake timing was developed based on Saito’s theory, integrating optics, acoustics, and mathematical modeling theories. The “quiet period” was identified as a significant precursor; thus, the model used the initiation of deformation localization to accurately predict rock failure. Using the model, a coal mine in Inner Mongolia was selected as a case study to predict a historical mining earthquake. The results indicated that the following: (1) Deformation localization and the “quiet period” of microseismic (MS) and acoustic emission (AE) activities were identified as two key pre-cursory indicators. The model utilized the initiation time of deformation localization and the inflection point of the “quiet period” in MS and AE activity as primary parameters. (2) For predicting rock failure times, the earliest prediction time deviates from the actual failure time by 143 s. The accuracy rate of predicted time points falling within a 90% confidence interval of the actual failure times is 100%. The model achieved 60% in forecasting the occurrence times of mine earthquakes. (3) The model’s prediction accuracy improved as the starting time parameter more closely approximated the actual initiation time of deformation localization, with the accuracy increasing from 0% to 100%. Full article

Three-section landslides are renowned for their immense size, concealed development process, and devastating impact. This study conducted physical model tests to simulate one special geological structure called a three-section-within landslide. The failure process and precursory characteristics of the tested samples were meticulously analyzed using video imagery, micro-seismic (MS) signals, and acoustic emission (AE) signals, with a focus on event activity, intensity, and frequency. A novel classification method based on AE waveform characteristics was proposed, categorizing AE signals into burst signals and continuous signals. The findings reveal distinct differences in the evolution of these signals. Burst signals appeared exclusively during the crack propagation and failure stages. During these stages, the cumulative AE hits of burst signals increased gradually, with amplitude rising and then declining. High-amplitude burst signals were predominantly distributed in the middle- and high-frequency bands. In contrast, cumulative AE hits of continuous signals escalated rapidly, with amplitude monotonously increasing, and high-amplitude continuous signals were primarily distributed in the low-frequency band. The emergence of burst signals and high-frequency AE signals indicated the generation of microcracks, serving as early-warning indicators. Notably, the early-warning points of AE signals were detected earlier than those of video imagery and MS signals. Furthermore, the early-warning point of burst signals occurred earlier than those of continuous signals, and the early-warning point of the classification method preceded that of overall AE signals. Full article

Glacial Lake Outburst Flood (GLOF) events, particularly prevalent in Asia’s High Mountain regions, pose a significant threat to downstream regions. However, limited understanding of triggering mechanisms and inadequate observations pose significant barriers for early warnings of impending GLOFs. The 2018 Nyalam GLOF event in southern Tibet offers a valuable opportunity for retrospective analysis. By combining optical and radar remote sensing images, meteorological data, and seismicity catalogs, we examined the spatiotemporal evolution, triggering factors, and the outburst mechanism of this event. Our analysis reveals a progressive retreat of 400–800 m for the parent glaciers between 1991 and 2018, increasing the runoff areas at glacier termini by 167% from 2015 to 2018 and contributing abundant meltwater to the glacial lake. In contrast, the lake size shrunk, potentially due to a weakening moraine dam confirmed by SAR interferometry, which detected continuous subsidence with a maximum line-of-sight (LOS) rate of ~120 mm/a over the preceding ~2.5 years. Additionally, temperature and precipitation in 2018 exceeded the prior decade’s average. Notably, no major earthquakes preceded the event. Based on these observations, we propose a likely joint mechanism involving high temperatures, heavy precipitation, and dam instability. An elevated temperature and precipitation accelerated glacial melt, increasing lake water volume and seepage through the moraine dam. This ultimately compromised dam stability and led to its failure between 3 August 2018 and 6 August 2018. Our findings demonstrate the existence of precursory signs for impending GLOFs. By monitoring the spatiotemporal evolution of environmental factors and deformation, it is possible to evaluate glacial lake risk levels. This work contributes to a more comprehensive understanding of GLOF mechanisms and is of significant importance for future glacial lake risk assessments. Full article

The Austin metropolitan area has experienced unprecedented economic and population growth over the past two decades. This rapid growth is leading communities to settle in areas susceptible to landslides, necessitating a comprehensive analysis of landslide risks and the development of early warning systems. This could be accomplished with better confidence for slow-moving landslides, whose occurrences could be forecasted by monitoring precursory ground displacement. This study employed a combination of ground- and satellite-based observations and techniques to assess the kinematics of slow-moving landslides and identify the controlling and triggering factors that contribute to their occurrence. By closely examining landslide events in the Shoal Creek area, potential failure modes across the study area were inferred. The findings revealed that landslide-prone areas are undergoing creep deformation at an extremely slow rate (up to −4.29 mm/yr). These areas lie on moderate to steep slopes (>22°) and are predominantly composed of clay-rich units belonging to the Del Rio and Eagle Ford formations. Based on the incidents at Shoal Creek, episodes of intense rainfall acting on the landslide-prone areas are determined to be the main trigger for landslide processes in the region. Full article

Coalburst, a frequent and severe dynamic disaster, poses significant challenges to the safety and sustainable development of coal mines during deep excavation. To investigate the mechanical behaviors and precursory characteristics of coalburst subjected to in situ stress conditions, multiaxial cyclic loading experiments were conducted on cubic coal specimens, and the effects of different confining pressures on the mechanical parameters and energy evolution were analyzed. Acoustic emission (AE) technology was utilized to study the accumulation process of stress-induced damage and identify the source modes of microcracks. Then, nonlinear fractal theory and critical slowing theory were used to investigate the time-varying precursory characteristics of catastrophic failure in coalburst. The results show that as the confining pressure increases, the coal samples exhibit higher levels of elastic strain energy and dissipative energy, indicating an enhancement of plasticity. The AE count and accumulated energy show a strong correlation with cyclic loads. With an increasing number of cycles, the AE Felicity ratio gradually decreases, indicating a progressive increase in irreversible damage. Shear-mode microcracks also become more prominent with applied stress and confining pressures, as supported by varying AF/RA values of AE signals. The AE signals also follow the Hurst statistical law, and increasing applied stress and confining pressure strengthen this statistical pattern with a higher Hurst index. Throughout the cyclic loading process, certain AE varying trends were observed: the autocorrelation coefficient increased, the fractal dimension gradually decreased, and the variance suddenly increased. These trends serve as early, middle, and short–imminent warning signals, respectively, for the catastrophic failure of the loaded coal sample. These research findings contribute to a deeper understanding of coal failure evolution and provide a basis for early detection and warning of coalburst disasters, which are also essential for promoting the safe and sustainable development of deep coal mining operations. Full article

Dynamic failure of surrounding rock often causes many casualties and financial losses. Predicting the precursory characteristics of rock failure is of great significance in preventing and controlling the dynamic failure of surrounding rock. In this paper, a triaxial test of granite is carried out, and the acoustic emission events are monitored during the test. The fractal characteristics of acoustic emission events’ energy distribution and time sequence are analyzed. The correlation dimension and the b value are used to study the size distribution and sequential characteristics. Furthermore, a rock failure prediction method is proposed. The correlation dimension is chosen as the main index and the b value is chosen as a secondary index for the precursor of granite failure. The study shows that: (1) The failure process can be divided into an initial stage, active stage, quiet stage, and failure stage. (2) The b value and correlation dimension both can describe the process of rock failure. There is a continuous decline before failure. Because of the complexity of the field, it is difficult to accurately estimate the stability of surrounding rock using a single index. (3) The combination of the b value and correlation dimension to establish a new method, which can accurately represent the stability of the surrounding rock. When the correlation dimension is increasing, the surrounding rock is stable with stress adjusting. When the correlation dimension is decreasing and the b value remains unchanged after briefly rising, the surrounding rock is stable, and stress is finished adjusting. When the correlation dimension and b value are both decreasing, the surrounding rock will be destroyed. Full article

The application of load on rock materials stimulates a weak current known as Pressure Stimulated Current (PSC). This study focuses on investigating the damage evolution of granite rocks through the analysis of PSC responses. Uniaxial loading experiments were conducted on granite samples, and the accompanying PSC was measured in real-time. The relationship between PSC characteristics and mechanical behaviors of granite was examined to explore precursory information related to granite failure. The damage evolution of granite was assessed using a damage variable defined as the cumulative charge (time integral of PSC). The results clearly demonstrate a close correlation between the variation of PSC and the mechanical behaviors of rock. Specifically, during the compaction and elastic deformation stages, PSC exhibits a slow and linear increase. However, once deformation enters the plastic stage, PSC demonstrates an accelerated upward trend. Additionally, it was observed that a stress drop coincides with an abnormal increase in PSC, which is followed by a rapid decay. The fluctuation observed after the abnormal increase in PSC during the accelerated growth phase can serve as a precursor of rock failure. Furthermore, the cumulative charge quantity effectively correlates with the damage process of granite samples. The stress–strain curve obtained from a theoretical constitutive model, established based on the damage variable represented by normalized cumulative charge, aligns reasonably well with the experimental results, affirming that the defined damage variable accurately reflects the damage evolution process of rocks. It is hypothesized that PSCs are carried by electrons within the rocks, which are stimulated by electron diffusion during deformation and experience a sharp increase upon rock fracturing. The research findings hold theoretical significance for predicting rockburst incidents using the PSC method. Full article

During the process of rock deformation and failure, a significantly large number of charge signals are generated as a result of fracture appearance and crack expansion. The generation of charge signal is the comprehensive embodiment of the coal-failure behavior. The study of charge signal in the process of fractured-rock deformation and failure is of great significance to the prediction of rock dynamic disasters such as tunnel-engineering stability, slope instability and earthquake. In this work, a surveillance system utilizing charge induction is employed to extract precursory information related to the instability and failure of precracked syenogranite. The results reveal a significant influence of fractures on the strength of syenogranite specimens and the number of charge-induction signal events. The position of the charge signal generated is related to the crack dip angle. Furthermore, with the increase of the crack inclination, the number of events and the amplitude and power value of the charge-induced signal increase and reach the maximum in the instability-failure phase. The syenogranite specimen has a relatively large value, medium correlation, or even high correlation charge-induction signal in the phase of rack propagation, which can make an early warning of the deformation and failure risk of syenogranite; with the increase of the fracture degree, the charge-induction signal with large values and high correlations gradually increases. Full article

Rock failure generally leads to serious consequences, and it is significant to obtain the precursor information prior to failure using associated techniques. Thus, it is essential to acquire and probe the relevant precursor information. In this study, true triaxial tests are performed on red sandstone specimens under varying intermediate principal stress conditions. The thermal infrared image evolution and the temperature-induced change characteristics of rock failure are also analyzed using infrared thermal imaging technology. In addition, with the assistance of a high-speed photography technique, these characteristics during the true triaxial compression and unloading processes are systematically investigated to determine how the intermediate principal impacts on thermal image, temperature, and fracture propagation. Finally, the evolution mechanism of the specimens is summarized, and a non-contact thermal infrared rock failure precursor indicator is proposed, which can give significant advance notice of rock collapse before the abnormal temperature change. The results show that there exist thermal infrared temperature precursors, thermal image precursors, and rapid development of rock macroscopic cracks before rock failure. Abnormal thermal images are prior to the abnormal temperature changes. As the intermediate principal stress increases, thermal abnormalities will change accordingly. Both temperature changes and thermal image anomalous patches can be utilized as precursor information of rock collapse, and the mechanism and specific information of thermal infrared failure precursors can be preliminarily determined in time and space. Our results can function as a significant frame of reference for the analysis and prevention of rock failure due to sudden instability. Full article

Quantifying the kinematic evolution patterns of mountain glaciers near Yarlung Tsanpo River performs a major role in evaluating the glacial instability and the secondary disasters. For the Sedongpu Basin near the Yarlung Tsanpo River Valley, the dramatic geomorphic landscape variations triggered by the ice-rock avalanche events were visually identified as the dominant texture deficiencies in time-series optical images. To improve the image correlation quality broken by these image texture deficiencies, the Landsat-8/Sentinel-2 optical images were divided into different groups, then a stepwise combination strategy was innovatively proposed to derive the glacier time-series displacement velocities in different temporal stages. The standard deviations (STD) of the optical measurements in the stable area maintained around 0.04 m/yr for the normalized displacement velocity and maintained from 0.6 to 1.7 m for the cumulative displacement time series. The obvious variations in glacier displacement velocity were identified before each collapse event. Subsequently, the offset-tracking procedures were performed on 7 Sentinel-1A Synthetic Aperture Radar (SAR) images to acquire the range and azimuth displacement velocities. To better reveal the dynamic mechanism of the glacier activity, the three-dimensional (3D) glacial displacement velocity was also derived by using optical and SAR results. The precipitation, temperature, and seismic activities were assumed as the main triggering factors of controlling the glacial dynamic mechanism and final collapse events. Additionally, the dynamic mechanism of the active glaciers in Sedongpu Basin conformed to a power law, which was limited by the changes of the internal stress friction force on the sliding base surface. The aim of this study is to shed a light on interpreting the precursory displacement patterns and their implicit failure mechanism of these ice-rock avalanche events with the conventional freely optical and SAR observations. Full article

Acoustic emissions (AEs) and weak electrical signals, also known as pressure stimulated currents (PSCs), were concurrently recorded in order to investigate their behavior and detect precursory indicators when cement mortar specimens were subjected to mechanical compressive loading, emphasizing the behavior of the AEs and the PSC signal in the vicinity of fracture. The axial compressive loading protocol incorporated a constantly increasing stress, from early stress values up to the vicinity of fracture and a sequential stress stabilization until the time the specimen collapses, due to severe growing internal damages. Concurrent recordings of the electrical and acoustic emissions were performed. The AE recordings were analyzed, by incorporating the recently introduced F- and P-functions, and the well-known b-value. The experimental results highlight strong similarities regarding the variations of the PSC signal, the AE hits occurrence rate (F-function), and the AE hits energy release rate (P-function). The above was also confirmed with another similar experiment in an identical specimen. It is noteworthy that, during the stay of the specimens under a constant load regime near their strength levels, a peak appears in the above quantities, which is directly related to an increased rate of axial deformation. The temporal evolution of the b-values is also presented. Results show that the local minima appearing at values close to b ≈ 1.0 correspond to the local maxima of the PSC signal. It is straightforwardly concluded that when both the PSC signal and the AE data are combined, they provide clear pre-failure indicators. Full article

Seismic precursors prior to the failure of rocks are essential for probing the nucleation process and mitigating hazards. However, such precursory events before large landslides are rarely reported possibly due to the lack of near-source observations. The 2017 Nuugaatsiaq, Greenland landslide that was preceded by an abundance of small earthquakes and captured by a local seismic station is a notable exception and offers us a valuable opportunity to investigate how a large landslide initiated. Prior work suggests that accelerated creeping plays an important role during the landslide nucleation process. However, by analyzing the temporal evolution of the waveform similarities, waveform amplitudes, and inter-event times of the seismic precursors, we find that the Nuugaatsiaq landslide was very likely triggered by a series of accelerated and migratory small earthquakes approaching the nucleation area of the upcoming landslide, thus providing important insights into the failure initiation of massive landslides. Full article

Across the world, coal resource is widely utilized in industrial production. During coal mining activities, dynamic disasters may be induced, such as coal and gas outbursts, or rock burst, resulting in serious accidents or disasters. Previous studies have shown that electric potential (EP) signals can be produced during the deformation and fracture process of coal and rock mass under load. The abnormal response characteristics of EP can reveal the damage evolution and failure feather of coal mass. In this paper, the response characteristics of EP signals are analyzed with high gas testing during mining activities within deep coal seams, and the relationship between the EP response and outburst disaster hazard is studied. The results show that: (1) Under the comprehensive action of mining stress and gas effect, the coal mass was damaged and fractured, which can produce abundant EP signals, while the temporal EP response characteristics can reflect the loading state and damage evolution process inside the coal seam. (2) When coal cannon and a sudden increase of gas concentration occurred in the coal mass, the EP signal was at a high level and fluctuated violently. This can be regarded as precursory information for an outburst risk, which was verified by monitoring the results of mining stress and electromagnetic radiation (EMR). (3) Based on the unilateral inversion imaging method, EP spatial distribution law was studied and abnormal zones with high-value were identified. The zone is close to, or coincident with, the high value interval of EMR intensity and count indexes, which revealed the distribution characteristics of coal damage localization. Hence, EP monitoring results can forecast precursor information of outburst hazards temporally, and identify local zones with outburst hazard spatially. This study provides a new idea and application basis for using the EP method to monitor and prevent coal and rock dynamic disaster hazards in the field. Full article

The accuracy of the monitoring information is particularly important for exploring fractured rock mass deformation and failure mechanisms and precursor characteristics. Appropriate monitoring methods can not only timely and effectively reflect the failure laws of fractured rock masses but also play an early warning role. To explore more reasonable monitoring methods, uniaxial compression experiments and real-time non-destructive monitoring on prefabricated fractured rock specimens through DIC, AE, and IRT were conducted; the strain field, temperature field, ringing frequency, standard deviation, etc. were analyzed; and correlation between the three methods in the information of audience was explored. The results show the following. (1) The failure evolution process of fractured rock mass can be divided into four stages. DIC can detect the initiation and propagation of cracks near the fractures of the specimen at the earliest stages. (2) The order of occurrence of precursor phenomena in multi-source monitoring information is different, which is vertical strain field > shear strain field > horizontal strain field > temperature field > ringing times. (3) The dispersion degree of standard deviation of each field is obviously different; the infrared temperature field is greater, but the strain field and temperature field show the same trend. (4) There are obvious precursors before the specimen is on the verge of instability; acoustic emission detected two consecutive increases in the cumulative number of ringing before destruction, which means the most obvious precursors. The research results can provide a theoretical basis for the precursory information capture and damage early warning of the fractured rock mass destruction process. Full article