Investigation on the motion and fragmentation mechanism of rockfall based on PIV-seismic signal monitoring
ObjectiveRockfall represents a typical geological hazard in alpine canyon regions, often accompanied by intense dynamic fragmentation phenomena. It is characterized by suddenness, concealment, and severe disaster-inducing potential. In recent years, the frequency of rockfall disasters has been incre...
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Editorial Department of Journal of Sichuan University (Engineering Science Edition)
2025-01-01
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| Series: | 工程科学与技术 |
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| Online Access: | http://jsuese.scu.edu.cn/thesisDetails#10.12454/j.jsuese.202500242 |
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| author | Sui Zhende Zhang Ke Zhang Kai Lin Qibin |
| author_facet | Sui Zhende Zhang Ke Zhang Kai Lin Qibin |
| author_sort | Sui Zhende |
| collection | DOAJ |
| description | ObjectiveRockfall represents a typical geological hazard in alpine canyon regions, often accompanied by intense dynamic fragmentation phenomena. It is characterized by suddenness, concealment, and severe disaster-inducing potential. In recent years, the frequency of rockfall disasters has been increasing due to the influence of extreme weather and human activities. Therefore, in-depth research into the movement mechanisms and fragmentation mechanisms of rockfalls is of significant importance for the development of early warning systems and the study of disaster mitigation measures.MethodsTaking the high slope at Puerdu, Yunnan Province as the prototype, this study proposes a novel rock specimen preparation method combining 3D printing technology with traditional cast-iron techniques. A plexiglass panel construction is utilized to fabricate a physical test platform featuring complex slope surface geometry. Comprehensive indoor physical simulation experiments capturing the entire rockfall disaster process are conducted. Particle Image Velocimetry (PIV) is employed to dynamically capture the trajectories and velocity fields of unstable rock specimens during movement and fragmentation. Seismic signal monitoring technology, combined with Empirical Mode Decomposition (EMD) and Fast Fourier Transform (FFT), is applied to extract effective spectral characteristics associated with rock dynamic fragmentation, thereby investigating seismic signal evolution features throughout the experiment.Results and Discussions The movement process of complex unstable rock masses is broadly divided into three distinct stages: initial toppling, accelerated sliding and fragmentation, and decelerated sliding and accumulation. Intense impact-induced fragmentation primarily occurs during the second stage. At the onset of movement and post-fragmentation, larger blocks exhibit movement forms dominated by toppling and sliding, while smaller fragments resulting from fragmentation display complex dynamic behaviors including bouncing, rolling, and sliding. Through EMD, the original seismic signal is decomposed into 9 Intrinsic Mode Function (IMF) components and 1 residual. FFT is applied to convert these modal components and the residual signal into frequency spectra. Noise is predominantly concentrated in the IMF1 component. By removing IMF1 and reconstructing the signal using the remaining components and the residual, a denoised seismic signal is obtained. Analysis of the reconstructed signal reveals that impact events between the rock mass and the slope surface trigger sharp fluctuations in the seismic signal. In contrast, signals generated by the subsequent movement of fragmented rock blocks are relatively smoother. The reconstructed seismic signal spectrum displays a "triple-peak" pattern, characterized by three distinct frequency peaks: a low-frequency peak (approximately 36.99 Hz), a medium-low-frequency peak (approximately 72.98 Hz), and a high-frequency peak (approximately 134.46 Hz). These peaks correlate respectively with the initial rock mass impact, secondary impacts and friction from larger fragmented blocks, and dense collisions or friction involving smaller fragmented blocks. This study presents a novel rock specimen preparation methodology combining 3D printing and cast-iron processes, enabling precise replication of critical internal features of actual rock masses, such as structural planes and defects. Concurrently, a plexiglass panel-based test platform with intricate slope topography is designed to achieve high-fidelity physical simulation of complex terrain conditions. These innovations provide new experimental approaches and technical means for replicating the real-world movement and fragmentation evolution processes of rockfalls under laboratory settings, facilitating a more accurate understanding of their dynamic mechanisms. This research establishes a correlation between the scale of fragmented blocks and seismic spectral signatures during rockfall events. This correlation helps delineate the fragmentation degree and kinematic state of rockfall debris, offering valuable references for the development of monitoring strategies within early warning systems. Compared to traditional monitoring methods focused solely on amplitude, this spectral analysis approach provides a more refined representation of the fragmentation state and changes in movement modality during rockfall. Furthermore, the results demonstrate that smaller fragments exhibit more intense motion concomitant with significant high-frequency energy release. This phenomenon underscores a close relationship between the degree of block fragmentation and the release of high-frequency energy during rockfall. Consequently, in subsequent optimization design of engineering protection structures, greater attention should be paid to the effects of particle size distribution resulting from rockfall fragmentation and the patterns governing high-frequency energy release. This necessitates strengthening research and development on devices specifically aimed at absorbing and dissipating high-frequency energy to ensure enhanced safety and reliability of the protective system in practical applications.ConclusionsParticle Image Velocimetry (PIV) successfully reconstructs the complex movement trajectories and velocity fields of rock blocks during collapse, highlighting the distinct non-linear dynamic behaviors (e.g., sliding, rolling, bouncing) of fragments, particularly smaller ones. The monitored seismic signals exhibit high spatiotemporal synchronicity with the instantaneous dynamic impacts of blocks during movement. By synergistically employing Fast Fourier Transform (FFT) and Empirical Mode Decomposition (EMD), high-frequency noise interference within the seismic signals is effectively mitigated, yielding more robust signal features. This process elucidates the distinct frequency components associated with different phases of block movement in the seismic signals, furnishing reliable data for accurately capturing the dynamic behaviors inherent in the collapse process. These research findings provide a theoretical foundation for the advancement of rockfall hazard monitoring and protective design. |
| format | Article |
| id | doaj-art-2dd0cd820afd44d7898b4111dadc9853 |
| institution | OA Journals |
| issn | 2096-3246 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Editorial Department of Journal of Sichuan University (Engineering Science Edition) |
| record_format | Article |
| series | 工程科学与技术 |
| spelling | doaj-art-2dd0cd820afd44d7898b4111dadc98532025-08-20T02:36:45ZengEditorial Department of Journal of Sichuan University (Engineering Science Edition)工程科学与技术2096-32462025-01-01116110864930Investigation on the motion and fragmentation mechanism of rockfall based on PIV-seismic signal monitoringSui ZhendeZhang KeZhang KaiLin QibinObjectiveRockfall represents a typical geological hazard in alpine canyon regions, often accompanied by intense dynamic fragmentation phenomena. It is characterized by suddenness, concealment, and severe disaster-inducing potential. In recent years, the frequency of rockfall disasters has been increasing due to the influence of extreme weather and human activities. Therefore, in-depth research into the movement mechanisms and fragmentation mechanisms of rockfalls is of significant importance for the development of early warning systems and the study of disaster mitigation measures.MethodsTaking the high slope at Puerdu, Yunnan Province as the prototype, this study proposes a novel rock specimen preparation method combining 3D printing technology with traditional cast-iron techniques. A plexiglass panel construction is utilized to fabricate a physical test platform featuring complex slope surface geometry. Comprehensive indoor physical simulation experiments capturing the entire rockfall disaster process are conducted. Particle Image Velocimetry (PIV) is employed to dynamically capture the trajectories and velocity fields of unstable rock specimens during movement and fragmentation. Seismic signal monitoring technology, combined with Empirical Mode Decomposition (EMD) and Fast Fourier Transform (FFT), is applied to extract effective spectral characteristics associated with rock dynamic fragmentation, thereby investigating seismic signal evolution features throughout the experiment.Results and Discussions The movement process of complex unstable rock masses is broadly divided into three distinct stages: initial toppling, accelerated sliding and fragmentation, and decelerated sliding and accumulation. Intense impact-induced fragmentation primarily occurs during the second stage. At the onset of movement and post-fragmentation, larger blocks exhibit movement forms dominated by toppling and sliding, while smaller fragments resulting from fragmentation display complex dynamic behaviors including bouncing, rolling, and sliding. Through EMD, the original seismic signal is decomposed into 9 Intrinsic Mode Function (IMF) components and 1 residual. FFT is applied to convert these modal components and the residual signal into frequency spectra. Noise is predominantly concentrated in the IMF1 component. By removing IMF1 and reconstructing the signal using the remaining components and the residual, a denoised seismic signal is obtained. Analysis of the reconstructed signal reveals that impact events between the rock mass and the slope surface trigger sharp fluctuations in the seismic signal. In contrast, signals generated by the subsequent movement of fragmented rock blocks are relatively smoother. The reconstructed seismic signal spectrum displays a "triple-peak" pattern, characterized by three distinct frequency peaks: a low-frequency peak (approximately 36.99 Hz), a medium-low-frequency peak (approximately 72.98 Hz), and a high-frequency peak (approximately 134.46 Hz). These peaks correlate respectively with the initial rock mass impact, secondary impacts and friction from larger fragmented blocks, and dense collisions or friction involving smaller fragmented blocks. This study presents a novel rock specimen preparation methodology combining 3D printing and cast-iron processes, enabling precise replication of critical internal features of actual rock masses, such as structural planes and defects. Concurrently, a plexiglass panel-based test platform with intricate slope topography is designed to achieve high-fidelity physical simulation of complex terrain conditions. These innovations provide new experimental approaches and technical means for replicating the real-world movement and fragmentation evolution processes of rockfalls under laboratory settings, facilitating a more accurate understanding of their dynamic mechanisms. This research establishes a correlation between the scale of fragmented blocks and seismic spectral signatures during rockfall events. This correlation helps delineate the fragmentation degree and kinematic state of rockfall debris, offering valuable references for the development of monitoring strategies within early warning systems. Compared to traditional monitoring methods focused solely on amplitude, this spectral analysis approach provides a more refined representation of the fragmentation state and changes in movement modality during rockfall. Furthermore, the results demonstrate that smaller fragments exhibit more intense motion concomitant with significant high-frequency energy release. This phenomenon underscores a close relationship between the degree of block fragmentation and the release of high-frequency energy during rockfall. Consequently, in subsequent optimization design of engineering protection structures, greater attention should be paid to the effects of particle size distribution resulting from rockfall fragmentation and the patterns governing high-frequency energy release. This necessitates strengthening research and development on devices specifically aimed at absorbing and dissipating high-frequency energy to ensure enhanced safety and reliability of the protective system in practical applications.ConclusionsParticle Image Velocimetry (PIV) successfully reconstructs the complex movement trajectories and velocity fields of rock blocks during collapse, highlighting the distinct non-linear dynamic behaviors (e.g., sliding, rolling, bouncing) of fragments, particularly smaller ones. The monitored seismic signals exhibit high spatiotemporal synchronicity with the instantaneous dynamic impacts of blocks during movement. By synergistically employing Fast Fourier Transform (FFT) and Empirical Mode Decomposition (EMD), high-frequency noise interference within the seismic signals is effectively mitigated, yielding more robust signal features. This process elucidates the distinct frequency components associated with different phases of block movement in the seismic signals, furnishing reliable data for accurately capturing the dynamic behaviors inherent in the collapse process. These research findings provide a theoretical foundation for the advancement of rockfall hazard monitoring and protective design.http://jsuese.scu.edu.cn/thesisDetails#10.12454/j.jsuese.202500242rockfalllaboratory experimentParticle image velocimetrydynamic fragmentationseismic signal |
| spellingShingle | Sui Zhende Zhang Ke Zhang Kai Lin Qibin Investigation on the motion and fragmentation mechanism of rockfall based on PIV-seismic signal monitoring 工程科学与技术 rockfall laboratory experiment Particle image velocimetry dynamic fragmentation seismic signal |
| title | Investigation on the motion and fragmentation mechanism of rockfall based on PIV-seismic signal monitoring |
| title_full | Investigation on the motion and fragmentation mechanism of rockfall based on PIV-seismic signal monitoring |
| title_fullStr | Investigation on the motion and fragmentation mechanism of rockfall based on PIV-seismic signal monitoring |
| title_full_unstemmed | Investigation on the motion and fragmentation mechanism of rockfall based on PIV-seismic signal monitoring |
| title_short | Investigation on the motion and fragmentation mechanism of rockfall based on PIV-seismic signal monitoring |
| title_sort | investigation on the motion and fragmentation mechanism of rockfall based on piv seismic signal monitoring |
| topic | rockfall laboratory experiment Particle image velocimetry dynamic fragmentation seismic signal |
| url | http://jsuese.scu.edu.cn/thesisDetails#10.12454/j.jsuese.202500242 |
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