Preliminary results on a near-real-time rock slope damage monitoring system based on relative velocity changes following the September 5,2022 M_(S) 6.8 Luding,China earthquake

Relative seismic velocity change(dv/v)is important for monitoring changes in subsurface material properties and evaluating earthquake-induced rock slope damage in a geological disaster-prone region.In this paper,we present a rapid damage assessment on three slow-moving rock slopes by measuring dv/v decrease caused by the 2022 M_(S) 6.8 Luding earthquake in Southwest China.By applying the stretching method to the cross-correlated seismic wavefields between sensors installed on each slope,we obtain earthquake-induced dv/v decreases of~2.1%,~0.5%,and~0.2%on three slopes at distances ranging from~86 to~370 km to the epicenter,respectively.Moreover,based on seismic data recorded by 16 sensors deployed on the rock slope at a distance of~370 km away from the epicenter,a localized dv/v decease region was observed at the crest of the slope by calculating the spatial dv/v images before and after the earthquake.We also derive an empirical in situ stress sensitivity of -7.29×10^(-8)/Pa by relating the dv/v change to the measured peak dynamic stresses.Our results indicate that a rapid dv/v assessment not only can help facilitate on-site emergency response to earthquakeinduced secondary geological disasters but also can provide a better understanding of the subsurface geological risks under diverse seismic loadings.

Dynamic failure mode and energy-based identification method for a counter-bedding rock slope with weak intercalated layers

The dynamic failure mode and energybased identification method for a counter-bedding rock slope with weak intercalated layers are discussed in this paper using large scale shaking table test and the Hilbert-Huang Transform(HHT) marginal spectrum.The results show that variations in the peak values of marginal spectra can clearly indicate the process of dynamic damage development inside the model slope.The identification results of marginal spectra closely coincide with the monitoring results of slope face displacement in the test.When subjected to the earthquake excitation with 0.1 g and 0.2 g amplitudes,no seismic damage is observed in the model slope,while the peak values of marginal spectra increase linearly with increasing slope height.In the case of 0.3 g seismic excitation,dynamic damage occurs near the slope crest and some rock blocks fall off the slope crest.When the seismic excitation reaches 0.4 g,the dynamic damage inside the model slope extends to the part with relative height of 0.295-0.6,and minor horizontal cracks occur in the middle part of the model slope.When the seismic excitation reaches 0.6 g,the damage further extends to the slope toe,and the damage inside the model slope extends to the part with relative height below 0.295,and the upper part(near the relative height of 0.8) slides outwards.Longitudinal fissures appear in the slope face,which connect with horizontal cracks,the weak intercalated layers at middle slope height are extruded out and the slope crest breaks up.The marginal spectrum identification results demonstrate that the dynamic damage near the slope face is minor as compared with that inside the model slope.The dynamic failure mode of counter-bedding rock slope with weak intercalated layers is extrusion and sliding at the middle rock strata.The research results of this paper are meaningful for the further understanding of the dynamic failure mode of counter-bedding rock slope with weak intercalated layers.

Damage Pattern Recognition of Spatially Distributed Slope Damages and Rainfall Using Optimal GIS Mesh Dimensions

Damage assessment for slopes using geographical information system(GIS) has been actively carried out by researchers working on several government organizations and research institutes in Korea. In this study, 596 slope damages were examined to identify the types of damage associated with dip angles, dip directions, and heavy rainfall resulting from typhoons in South Korea. Heavy rainfall of 100 mm to 300 mm resulted in 80% at the investigated slope damages. A GIS database was developed for highways, rainfall, soil or rock geometry, and types of damage. A grid of rainfall intensity was generated from the records of maximum daily rainfall. Contours for slope damages and heavy rainfall using optimal GIS mesh dimensions were generated to visualize damage patterns and show substantially strong correlation of rainfall with slope damages. The combination of remote sensing with the GIS pattern recognition process described in this work are being expanded for a new generation of emergency response and rapid decision support systems.

Optimal CNN-based semantic segmentation model of cutting slope images

This paper utilizes three popular semantic segmentation networks,specifically DeepLab v3+,fully convolutional network(FCN),and U-Net to qualitively analyze and identify the key components of cutting slope images in complex scenes and achieve rapid image-based slope detection.The elements of cutting slope images are divided into 7 categories.In order to determine the best algorithm for pixel level classification of cutting slope images,the networks are compared from three aspects:a)different neural networks,b)different feature extractors,and c)2 different optimization algorithms.It is found that DeepLab v3+with Resnet18 and Sgdm performs best,FCN 32s with Sgdm takes the second,and U-Net with Adam ranks third.This paper also analyzes the segmentation strategies of the three networks in terms of feature map visualization.Results show that the contour generated by DeepLab v3+(combined with Resnet18 and Sgdm)is closest to the ground truth,while the resulting contour of U-Net(combined with Adam)is closest to the input images.