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Unmanned Aerial Vehicle (UAV) technique has been widely utilized in geohazards assessment. In this work, the effectiveness of the UAV photogrammetry in the remote sensing and assessment of the landslide behavior is demonstrated through a case study of a landslide that occurred in Guizhou, China on 10 June 2018. The post-landslide assessments were conducted through a field investigation by a team of experts; and, two UAV photogrammetry-based surveys were carried out. On the basis of a detailed inspection of the high-resolution aerial photographs collected from the UAV photogrammetry and historical satellite imagery, subsurface stratigraphic configuration revealed from borehole explorations and the local rainfall data collected, the failure mechanism of this landslide is investigated. The occurrence of this landslide is probably attributed to the combined influence of the long-term rainfall and the engineering activities at this site. An automatic landslide cracks recognition model, which is based on the deep learning-based image recognition technique of RetinaNet, is further developed to map the cracks at the landslide site. The effectiveness of this automatic crack recognition model is validated through quantitative comparisons between the landslide cracks recognized and the field survey results. Based upon the landslide cracks identified on two different dates after this landslide event (by the field survey and automatic crack recognition model) and the subsurface displacement revealed from a drilled hole, the evolution behavior of this landslide is analyzed. The results show that the stability of this landslide was not achieved during the first slide in June 2018 and the limit of the landslide was increased much from June to November 2018. In such a situation, the elements at risk in the zones that are potentially impacted by this landslide are identified (with the aid of the UAV images collected), and a preliminary consequence assessment is conducted. • The failure mechanism of a landslide in Guizhou, China is investigated. • An automatic landslide cracks recognition model is developed using RetinaNet. • The landslide behavior is studied based on the cracks recognized on two dates. • A UAV images-based preliminary assessment of the landslide consequence is made. [ABSTRACT FROM AUTHOR]

Magnetic resonant wireless power transfer (MR-WPT) has several advantages over conventional wired underground power supply methods. However, MR-WPT inevitably encounters metal conductors, which reduce the system efficiency through the eddy loss induced in the conductor by high-frequency electromagnetic waves. In this paper, the effect of resonant frequency variations caused by metal tube interference with the aim of maximizing the system efficiency is studied. According to the variation in the resonant frequency, the system efficiency is analytically derived by an equivalent circuit model. Electromagnetic simulations are carried out to further analyze the metal tube interference on the system. The results demonstrate the existence of an optimal resonant frequency that maximizes the system efficiency. Aluminum tube interference produces a lower optimal resonant frequency and higher efficiency than a 304 stainless-steel tube. When the metal tube is slotted, the optimal slot width and number of slots enhance the maximum efficiency and reduce the optimal resonant frequency and frequency drift. With slot widths of 2 and 8 mm, the system efficiency reaches ∼67% at 40.1 kHz and 55% at 48 kHz, respectively. Finally, different types of slotted tubes are fabricated, and the theoretical results are experimentally verified. [ABSTRACT FROM AUTHOR]

Monitoring data show that many landslides in the Three Gorges region, China, undergo step-like displacements in response to the managed, quasi-sinusoidal annual variations in reservoir level. This behavior is consistent with motion initiating when the reservoir water level falls below a critical level that is intrinsic to each landslide, with the subsequent displacement rate of the landslide being proportional to the water depth below that critical level. Most motion terminates when the water level rises back above the critical level, so the annual step size is the time integral of the instantaneous displacement rate. These responses are incorporated into a differential equation that is easily calibrated with monitoring data, allowing prediction of landslide movement from actual or anticipated reservoir level changes. Model successes include (1) initiation and termination of the annual sliding steps at the critical reservoir level, producing a series of steps; (2) prediction of variable step size, year to year; and (3) approximate prediction of the shape and size of each annual step. Annual rainfall correlates poorly with step size, probably because its effect on groundwater levels is dwarfed by the 30 m annual variations in the level of the Three Gorges Reservoir. Viscous landslide behavior is suggested. [ABSTRACT FROM AUTHOR]

Magnetic resonant wireless power transfer (MR-WPT) has become a significant method for powering the measurement units in landslide monitoring boreholes. This paper focuses on the effects of quality factor, coupling distance and load on the power transfer stability, sensitivity and performance of an MR-WPT system. Firstly, through a numerical model of an MR-WPT, the effect of quality factor and coupling distance on the output power, transfer efficiency and frequency splitting phenomenon of MR-WPT systems have been comparatively analyzed. The relationship between the load and the coupling distance region corresponding to optimal transfer performance has been studied. Results show that improving the quality factor of the coils is beneficial for the transfer performance and stability of WPT system. Furthermore, through the selection of the load, a coupling distance region with high transfer stability and an optimal tradeoff between power and efficiency can be obtained. Finally, the above theoretical simulation results have been verified by experimental results. [ABSTRACT FROM AUTHOR]

The shear mechanical behaviour of slip zone soil is of great significance for the stability analysis of landslides. Based on the shear deformation-failure characteristics of slip zone soil and the statistical damage theory, a shear constitutive model is proposed to describe the shear stress - displacement relation of slip zone soil. Parameters in the proposed model have clear physical-mechanical meaning, and can be easily obtained by shear tests. The shear constitutive model is verified by comparing model results with ring-shear test results on the slip zone soil from the Huangtupo landslide in the Three Gorges Reservoir Area of China. It reveals that the model is capable of capturing the salient behaviour of the slip zone soil, such as the pre-peak and post-peak deformation characteristics. Moreover, utilizing limited ring-shear test data under given normal stresses, shear stresses at various shear displacements under untested normal stress are available by this model. Finally, a dynamic evaluation method of landslide stability, which incorporates the landslide displacement by presented constitutive model, is proposed and applied to analyze the stability of the Riverside Slump II# of the Huangtupo Landslide. • A new shear constitutive model is proposed to describe the mechanical properties of slip zone soil. • A set of ring-shear test results on the slip zone soil from an active landslide are well simulated by the model. • The proposed model is capable of predicting the shear stress - shear displacement curves. • A dynamic evaluation method of landslide stability is proposed. [ABSTRACT FROM AUTHOR]

The impact angle is an important but understudied factor that exerts a significant control on the propagation of granular flows. To investigate the influence of the impact angle on the motion and deposition of granular flows, flume experiments and numerical simulations were performed using impact angles ranging from 0° to 70°. Three-dimensional laser scanning and image analysis were employed to collect structural and kinetic information on these granular flows. Moreover, the evolution of the energy components of the granular flows was investigated at selected monitoring points and entire sliding mass using numerical simulations. A lower-velocity region in the middle portion of granular flows was observed in all cases. The area and shape of this region were found to be greatly influenced by the impact angle. An energy transfer from the middle and rear regions to the front of the granular flow was also observed, mediated by particle collisions. As a result, fluctuations in the velocity and energy of the particles in front region occurred, which in turn resulted in longer travel distance. The direction of movement and the travel distance changed when the granular flows encountered an obstacle along the horizontal chute. From the macroscopic point of view, the travel distance decreased as the impact angle increased. However, individual particles - especially in the front region - could travel longer distances even in the case of large impact angles owing to the collision-mediated energy transfer. • Noncontact measurement was used to study the motion and deposition of granular flows • A lower-velocity region in the middle portions of the granular flows was observed • The overall travel distance decreased with the impact angle • Collisions in the front region caused significant fluctuations in velocity and energy • Particles in the front region could travel long distances due to the energy transfer [ABSTRACT FROM AUTHOR]

Assessing the influence of the impact pressure exerted on surrounding rock mass by potential debris flows is one of the challenges in a mountain tunnel construction project. This paper proposes an effective mathematical model for the assessment of impact pressure exerted by debris flows on obstacles. The characteristics of the new model are analyzed, and the parameters determination method for the new model are deduced. Also, a new method for dynamic reliability analysis of the rock mass surrounding tunnels is proposed and is constituted into three key steps. First, by inputting impact pressure of debris flows generated by the aforementioned new model, the FLAC3D is used as the dynamic analysis engine to obtain the time-varying stress distribution of surrounding rock mass during the impact of debris flow. Second, the factor of safety (FOS) contours of surrounding rock mass are generated based on element states using the maximum tensile stress criterion and the Mohr-Coulomb yield criterion. Third, by using the time-varying contours of the FOS, a failure probability and a reliability index are obtained from a reliability perspective. A case study shows the complete analysis process and confirms the effectiveness of the above methodology. In sum, this paper provides new ideas, new methods, and a reference example for evaluating the influence of dynamic impact exerted by debris flows on the rock mass surrounding tunnels. • A novel mathematical model is proposed for the assessment of impact pressure exerted by debris flows on obstacles. • A new method is proposed for dynamic reliability analysis of the rock mass surrounding tunnels. • The instantaneous factor of safety (FOS) of each element of the rock mass surrounding tunnels is applied based on the maximum tensile stress criterion and the Mohr-Coulomb yield criterion. • The failure probability and the reliability index of the rock mass surrounding tunnels are obtained based on space-time-varied stress fields. [ABSTRACT FROM AUTHOR]

Although numerical methods based on strength reduction are becoming popular in slope stability analysis, they fail to provide a distinct critical slip surface and only provide a shear band. The widely used visualization techniques for defining the critical slip surface are susceptible to subjective judgment and are inefficient for batch analysis and three-dimensional analysis. When a slope fails, the displacements on the two sides of the critical slip surface will be substantially different. Based on this observation, an automatic identification method for locating the critical slip surface is proposed. The k-means clustering algorithm is first applied to automatically separate the nodal displacements into two categories representing the sliding mass and the stable block. Then, the scatters near the separation surface are obtained by constructing the alpha shape of the sliding mass. Finally, the critical slip surface is obtained by fitting the extracted scatters. A homogeneous slope, a slope with a thin weak layer and a real landslide are used to test the effectiveness of the proposed method. The results show that the proposed method can automatically and accurately identify two-dimensional and three-dimensional critical slip surfaces. • An automatic method for identifying the critical slip surface of slopes is proposed. • The proposed method is simple and not susceptible to subjective judgments. • The proposed method can accurately identify the distinct 2D/3D critical slip surface. [ABSTRACT FROM AUTHOR]

Interval prediction is an efficient approach to quantifying the uncertainties associated with landslide evolution. In this paper, a novel method, termed lower upper bound estimation (LUBE), of constructing prediction intervals (PIs) based on neural networks (NNs) is applied and extended to landslide displacement prediction. A random vector functional link network (RVFLN) is adopted as the NN used in the improved LUBE. A hybrid evolutionary algorithm, termed PSOGSA, that combines particle swarm optimization (PSO) and gravitational search algorithm (GSA) is utilized to train LUBE. The loss function of LUBE is redesigned by considering the quality of PI centre, which allows for a more comprehensive evaluation of PIs. The population initialization in the training process of LUBE is implemented by transferring the weights of a series of pre-trained RVFLNs. The performance of the improved LUBE method is validated by considering a comprehensive set of cases using seven benchmark datasets. In addition, a hybrid method that integrates ensemble empirical mode decomposition (EEMD) with the improved LUBE is proposed for the special case of landslide displacement prediction. Six real-world reservoir-induced landslides are considered to validate the capability and merit of the proposed hybrid method. [ABSTRACT FROM AUTHOR]

Data preprocessing is an indispensable step for landslide displacement forecasting, which is an effective approach for predicting the deformation and failure behaviors of landslides. However, most studies focus on the construction of displacement forecast models and ignore the influence of data preprocessing on the forecasting results. Data normalization is an important part of data preprocessing; however, the selection of a data normalization method is subjective and arbitrary. In this study, four types of normalization methods for data preprocessing are presented, and these methods are applied in forecasting the displacement of bank landslides in the Three Gorges Reservoir area with various deformation mechanisms for comparison. The results demonstrate that (1) the selected normalization method substantially influences the forecast performance; (2) the normalization method is closely related to the selected forecasting model and is less dependent on the landslide deformation mechanism; and (3) the commonly used max–min normalization approach is not the optimal method, and the zero-mean normalization method is optimal for the particle swarm optimizer of support vector machine (PSO-SVM) method, while the logarithmic normalization method is optimal for the extreme learning machine method. The obtained results suggest that the data preprocessing methods must be carefully selected in landslide displacement forecasting. [ABSTRACT FROM AUTHOR]

Advances in estimating the three-dimensional (3D) orientation distribution include i) the stereology-based Fouché estimator (FE); and ii) its recent modification (MFE), which has one less meshing step and has three modified components compared with the FE. One way to achieve an accurate estimate is by selecting the optimum estimator. Here, we developed a recognizer for the optimum estimator to help automatically select the most likely accurate estimator for use in the FE and MFE. Before this, we conducted a systematic comparison of the likelihood of obtaining an accurate estimation to clarify for which patterns FE and MFE are likely to perform accurately. The statistical comparison results showed that the MFE was more likely to perform accurately than the FE for patterns of moderately to strongly aligned fracture sets and for patterns of poorly aligned fracture sets with medium to wide intersection angles to the 1D probe, and thus, the MFE was the optimum estimator. For patterns of poorly aligned fracture sets with narrow intersection angles to the 1D probe, however, the FE was more likely to perform accurately than the MFE, and thus, the FE was the optimum estimator. On the basis of these comparison results, we developed a recognizer for the optimum estimator. This developed recognizer provided a simple, reliable tool for selecting the optimum estimator to accurately produce a 3D orientation distribution estimation, which is beneficial to realistic fracture network modelling. Weakness of the developed recognizer was also disclosed. • Clarified in which patterns FE and MFE are likely to produce accurate 3D estimates. • Found that variation in sample size does not affect the optimum estimator selection. • Fracture alignment and probe-fracture angle affect the optimum estimator selection. • Developed a recognizer for the optimum estimator to produce accurate 3D estimates. • The developed recognizer benefits realistic 3D fracture network geometry modelling. [ABSTRACT FROM AUTHOR]

Realistic discontinuity network modelling of rocks requires the accurate input of the three-dimensional discontinuity orientation distribution (3DDOD), but in practice, access to such three-dimensional information is limited. Fouché recently developed a method for estimating the 3DDOD from one-dimensional scanline-mapping observations. However, little is known about the error in such 3DDOD estimates. This study focuses on (1) the error and its possible contributors, (2) error prediction, and (3) error mitigation. An error investigation based on synthetic discontinuity geometry data reveals that the 3DDOD estimates are not always accurate. The error is significantly impacted by three factors: the Fisher constant (к), the angle between the major discontinuity plane and the mapping scanline (θ), and the discontinuity sample size (n), with larger к , θ , or n values contributing to lower errors. This к -, θ -, and n- dependent error appears to be inherently related to the sample density, which is defined as the pole number per unit cell (1° × 1°) in the Fouché method. Additionally, a predictor of the error based on an error-and-factors empirical relationship is developed to provide precise error prediction and optimize the scanline sampling for error mitigation. The weakness of the developed predictor is also disclosed. [ABSTRACT FROM AUTHOR]

The loose accumulation CAUSED by landslide, collapse, debris flow, and mine blasting, exerts considerable negative influence to human activities. Besides, it can easily trigger secondary disaster under inner and outer geological conditions. Extraction and measurement of the particle of loose accumulation is of importance for prediction of slope stability and mine blasting. In this paper, the 3D laser scanning is utilized to collect the point clouds of granular materials in physical model (three types of materials) and landslide accumulation in field, respectively. Then, the alpha shapes (AS) and hill climbing-region growing (HC-RG) algorithms are introduced for identifying particles and finding their dimensions (e.g., particle number and radii). Comparison between the recognition results and reality shows that both algorithms can provide a good performance in laboratory physical model, and acceptable results can be obtained when applying two algorithm to field survey. AS algorithm needs less time to process data than HC-GR algorithm; however, the recognition from HC-RG algorithm is more accurate than that by AS algorithm. [ABSTRACT FROM AUTHOR]

To better understand the shear mechanical behaviour, the information value (IV) and the fractal theory (FT) models are employed to determine the shear failure regions of rock joints under the low effective normal stress conditions. First, high density point clouds of rock joints at the initial stage (pre-shearing) were collected, using a laser scanning technology and four topography parameters (slope angle, horizontal orientation, elevation difference and curvature) were produced from point clouds, to represent the mesostructure features. Second, direct shear testing were conducted at the end stage (post-shearing), and shear striae on the rock joints were measured to assess shear failure regions, based on image segmentation. Third, by combining morphological features with experimental observations, correlation analyses are performed, to investigate the influences of topography parameters on shear failure behaviors of rock joints, based on IV and normalized weight W i. Similar findings are observed from the two algorithms, indicating that horizontal orientation has a larger impact on shear failure than the other three parameters. Furthermore, under the low normal loading, the shear failure of rock joints are more likely to occur in regions with a slope angle in the range of 30° to 40°, a horizontal orientation in the range of SE to SW (facing shear direction), an elevation difference in the range of 0.15 to 0.30 mm and a curvature in the range of −1000 to −200 mm−1 and 200 to 1000 mm−1. It is notable that the effect of normal loads level on shear failure regions should not be neglected. Eventually, a model is developed to predict the shear failure regions of rock joint and receiver operating characteristic (ROC) analyses show that shear failure determinations, based on the proposed model, match the actual situation. • Four topography parameters were produced from point clouds to represent the mesostructure features of rock joints. • Image segmentation was used to measure the shear failure regions of rock joints under low normal loads. • The relationships between the mesostructure parameters and shear failure regions were established based on IV and FT models. [ABSTRACT FROM AUTHOR]

Slip zone soils play a crucial role in the evolution of landslides. In this paper, slip zone soils of the Huangtupo Landslide in the Three Gorges Reservoir area, which is an ancient landslide affected by water level fluctuation, are taken as an example to research the influence of wetting–drying cycles on soil properties. The mercury intrusion porosimetry test is used to study the soil's microstructure, while the triaxial test is used to measure the mechanical parameters. The experimental results indicate that the wetting–drying cycles can change the micropore structures and macro-mechanical properties of the soils. Meanwhile, it is demonstrated that there is a certain relationship between the macro- and micro-properties. From the microcosmic perspective, the fractal structure unit formed in the long-term geological environment is the key factor affecting the mechanical properties of the slip zone soils. Then, based on fractal theory, a weakening model of slip zone soils during wetting–drying cycles is proposed. The correctness and reliability of the model are verified by the mechanical parameters from triaxial tests. Finally, it is indicated that the weakening model can be used to forecast the weakening coefficient of slip zone soils under wetting–drying action, which results from the periodic fluctuations of the reservoir level. [ABSTRACT FROM AUTHOR]

A rapid and long-traveling landslide was triggered by a monsoon rainfall of a total of 446.5 mm for 3 days in the Aranayake area, Sri Lanka. The landslide destroyed 75 houses and killed 127 persons along the course of this landslide. The mechanism of this landslide was investigated by a joint team of the International Consortium on Landslides (ICL) and the National Building Research Organization (NBRO) of the Government of Sri Lanka in 2017 and 2018; the investigation was part of the WCoE and IPL projects. Physical properties of soil samples taken from the source area of the Aranayake landslide were examined through a series of undrained ring-shear tests, and the measured properties were used in a numerical method, LS-RAPID, to simulate initiations and motions of landslides in this area. The authors then tried to first reproduce a landslide, which was considered, from available pieces of evidence, to have most likely happened in the past, then, to assess the risk of a potential future landslide that is expected to occur close to the 2016 Aranayake landslide. Two possible sliding surfaces were assumed to develop through the soil mass, one along the boundary between the weathered surface soil and the jointed bedrock and another along a potential aquiclude inside the soil. This attempt to estimate movements of both past and future landslides based on the numerical reproduction of the 2016 Aranayake landslide hazard will help develop landslide hazard assessment technologies. [ABSTRACT FROM AUTHOR]

A general discrete element method-based model is proposed to investigate the cyclic freezing-thawing induced damage of fractured rocks. A set of cracks is defined as an assembly of interparticle pores that are interconnected due to self-definition (pre-existing) or contact breaking (external force induced). During the freezing-thawing simulation, only the rock grains surrounding the cracks are subjected to frost heave pressure, which are expected to cause contact breaking and crack propagation. In this sense, most of the pores that do not form cracks in the numerical model will not participate in the calculation, so the computational cost and time are substantially reduced. The cracks connected to the atmosphere, i.e. the model boundaries, are classified as inactive cracks and their frost heave pressures are removed accordingly. Therefore, model convergence is recognized when all cracks are converted to inactive. Parametric analysis is further performed to show the influence of some important input parameters, including the unfrozen water content, calibration factor of frost heave pressure, crack density and dip. Finally, the freezing-thawing damage of rocks is quantified by the reduction in uniaxial compressive strength after a prescribed number of freezing-thawing cycles. The results are validated with an analytical solution. It is shown that the rock strength degradation, crack evolution, heave and settlement can be well simulated by the proposed model. This methodology can be extended to large-scale problems such as glacier slope instability or landslides. [ABSTRACT FROM AUTHOR]

Fluid flow in rock fractures is described by Darcy's law and its nonlinear extension, the Forchheimer equation in form of a quadratic polynomial. Since the nonlinearity of the Forchheimer equation, determining its key coefficient of inertial permeability (i.e., the quadratic coefficient representing inertial losses) requires a series of flow tests under different hydraulic gradients. However, how to choose the volumetric flux range for deriving inertial permeability is never scrutinized. Here we report a seemly irrational dependency of inertial permeability on volumetric flux range by massive direct numerical simulations of fluid flow in rock fractures. This variation presents traceability and is closely related to the evolution of microscale eddies and macroscale flow regimes. A concept of global inertial permeability is thus proposed from this traceable variation, which can reproduce the whole flow regime in rock fractures. Two parametrized criterion models are subsequently established for calculating global inertial permeability using the lowest cost and ensuring its accuracy: one in terms of minimum Reynolds number for practical purposes, and the other in terms of minimum eddy volume ratio for mechanistic interpretation. Further discussions indicate that the proposed global inertial permeability is of great importance to non-Darcian flow prediction and flow regime assessment. Moreover, the parameterized criterion models in the form of power-law function for determining global inertial permeability, drawn from 2D fracture simulations, can apply to 3D fractures and large-scale fractured rock aquifers. The findings and results in this study are of great significance for accurately evaluating the hydraulic conductivity of rock fractures, especially at relatively high flow rates, and are useful for many geophysical and industrial applications. • Variation of inertial permeability with flow ranges is manifested which results from evolving eddies and flow regime. • Global inertial permeability referring to stable value of the variation is proposed to reproduce the whole flow regime. • Practical and mechanistic criterion models for determining global inertial permeability are both established. [ABSTRACT FROM AUTHOR]

Abstract Geological disasters have occurred frequently in the Three Gorges Reservoir area. Therefore, the stability and failure mode research on riverside landslides has become increasingly important. Taking the toe of Liangshuijing landslide as a case study and combining the geological conditions of the Three Gorges Reservoir area, a centrifuge slope model is constructed. In addition, the fluctuation of the water level is simulated in the centrifuge model test. Based on the digital photography, laser displacement sensors (LDS), pore pressure transducers (PPT) and earth pressure sensors (E), multi-physical data are obtained. Finally, numerical simulation is carried out to analyze the stability and deformation characteristics of the slope model. The results indicate that: (1) At the water level rise stage, the model is dominated by the vertical displacement. And the horizontal displacement is much larger than the vertical displacement at the drainage stage. (2) Cracks first appear at the toe of the slope and extend to the middle and rear of the model gradually. Then, deformation occurs in the middle platform of the slope. (3) At the water level rise stage, the factor of safety increases rapidly. When the reservoir water level remains stable, the stability of the slope decreases slowly. And at the drainage stage, the factor of safety decreases first and then increases. (4) There is a significant positive linear correlation between the decline rate of the safety factor and the drainage rate over a certain test range. And the stability of the landslides on the reservoir banks would become worse gradually during the long-term cyclic operation of the Three Gorges Reservoir. Highlights • The fluctuation of the water level is simulated in the centrifuge model test. • Qualitative and quantitative method are combined to analysis the evolution of the landslide. • The failure mode and the deformation mechanism of the slope are revealed by the centrifuge model test. [ABSTRACT FROM AUTHOR]

Convolutional neural networks are widely used for solving image recognition and other classification problems in which the whole image is considered as a single object. In this paper, we take the pansharpening problem of remote sensing images as an example to discuss how to establish pixel-wise regression models using convolutional neural networks. In order to meet the requirements of pixel-wise analysis on both the localization accuracy and the abstraction ability of the regression process, a U-shaped architecture is applied in our study to construct the network model. By establishing direct connections between convolution layers at the front end and the back end of the network, image features corresponding to different resolution levels can be retained. Then a regression relationship between these multi-resolution image features and the target image pixel values can be obtained. Experimental results show that the proposed regression model can effectively accomplish pansharpening, with better performance in controlling geometric deformation and color distortion, as compared to some state of the art methods. [ABSTRACT FROM AUTHOR]

In this study, to investigate the variability of mechanical parameters of rock, a three-dimensional (3D) discrete element model (DEM) with the consideration of random microcracks was proposed. The random microcracks follow the negative power-law distribution with upper and lower limits of microcrack size. The results showed that coefficient of variations (COVs) and average values of elastic modulus, Poisson's ratio, unconfined compression strength and tensile strength of Lac du Bonnet granite are well matched through the present model. The present simulations indicate that the large COVs were induced by the interconnected large microcracks. The parametric study clearly indicates that the random microcracks significantly affect COVs, while the effect of grain size variation can be ignored. The size of microcracks determines the variability of mechanical parameters, and the volume density of microcracks can significantly influence the COVs. The correlation between the fractal dimension of microcrack size distribution and COVs is not linear. The increasing variability of microcrack density can result in the increase of COVs. Finally, a calibration procedure was proposed to determine the present model's parameters. [ABSTRACT FROM AUTHOR]

Earthquake-induced rock slope failure is one of the most destructive geohazards, posing serious threats to human lives and properties. The potential hazard of a rock slope, under the loading of earthquakes, can be assessed from its failure and runout characteristics, which are however affected by inherent fractures. To simulate the randomness of these inherent fractures, the discrete fracture network (DFN) modeling technique that is based on the Monte Carlo simulation (MCS) is often employed. It is worthwhile noting that different realizations of DFN can be sampled from different MCSs; however, only one realization of DFN is considered and studied in the conventional analysis. There exist differences between the arbitrarily selected DFN and true DFN; as such, the conventional deterministic analysis could cause uncertainty in DFN modeling and the potential hazard of a rock slope cannot be accurately evaluated. In such a circumstance, this paper proposes a probabilistic analysis of earthquake-induced failure and runout behaviors of fractured rock slopes, in which multiple realizations of DFN that are systematically generated with MCS are taken as inputs to the discrete element method (DEM) modeling of slope behaviors, thus, the uncertainty induced by DFN modeling can be explicitly considered and evaluated. [ABSTRACT FROM AUTHOR]

Due to the inherent spatial variability of the geological bodies, limited boreholes (constrained by budget), and data interpretation errors, the subsurface conditions (in terms of the stratigraphic configuration and associated geo-properties) at a site are hard to ascertain, and considerable stratigraphic and geo-properties uncertainties are induced. The stratigraphic and geo-properties uncertainties could complicate the engineering design. One way to reduce the uncertainties is to adopt an optimal site exploration program under constraints. This paper presents a novel framework for optimizing the site exploration program based on a coupled characterization of the stratigraphic and geo-properties uncertainties. Within the context of the proposed framework, a conditional random field approach, recently advanced by the authors, is employed to characterize the stratigraphic and geo-properties uncertainties simultaneously. Here, the spatial correlation of stratum existence (depicting stratigraphic configuration) and that of geo-properties are estimated with a Bayesian updating scheme. Then, the 'influence zone' at the concerned site, which is often problem-specific, is selected based on a geotechnical performance evaluation. The derived influence zone can be taken as the candidate zone for boreholes. Finally, the optimal locations and depths of boreholes are determined based on the stratigraphic and geo-properties uncertainties characterized within the influence zone. To depict the effectiveness and versatility of the presented framework, two problems (i.e., a shallow foundation problem and a slope stability problem) are analyzed. • A novel framework for optimizing the site exploration program is proposed. • Site characterization and geotechnical performance evaluation are integrated. • Characterizations of stratigraphic and geo-properties uncertainties are coupled. • The spatial correlation structure is estimated with a Bayesian updating scheme. • Geological model characterization is updated in a step-by-step manner. [ABSTRACT FROM AUTHOR]

Flexural toppling is one of the main failure modes of natural and manmade anti-dip layered rock slopes. Based on cantilever slab tensile theory, the failure mechanism of flexural toppling was analyzed. A toppling slope is divided into three parts: the stability, tensile and shear zones. By considering this failure mechanism, a new stability analysis method for slopes against flexural toppling failure is proposed using equilibrium theory. In addition, a sensitivity analysis is performed to investigate the locations of possible failure surfaces and zones as well as changes in the stability of anti-dip rock slopes under different conditions. The results show that the positions of the inter-column forces have almost no effect on the stability factor but affect the areas of the tensile zone and the shear zone. The angle of the most dangerous potential failure surface increases with increasing dip angle and slope height, whereas the stability factor is negatively correlated with the dip angle and slope height but is positively correlated with the layer thickness. The failure mode is essentially flexural toppling when the layer thickness is small, but the failure mode gradually transitions to shear-sliding with increasing layer thickness. Finally, a real case study is analyzed using this method, and the calculated results are consistent with the actual conditions. [ABSTRACT FROM AUTHOR]

This paper proposes a new hybrid approach for constructing high-quality prediction intervals (PIs) for landslide displacements. In the first stage, we develop an improved method to optimize bootstrap-based PIs. The improved method uses part of the selected neural networks (NNs) rather than all of the NNs to construct PIs. To guarantee computational efficiency, random vector functional link networks (RVFLNs) are adopted as predictors. In the second stage, to handle the mutational points in landslide displacement prediction, the improved method is integrated with a NN switched method. The effectiveness of the proposed hybrid method has been validated through comprehensive cases using two benchmark data sets and three real-world landslide data sets. [ABSTRACT FROM AUTHOR]

The red mudstone sediments are widely encountered in earthquake region northwestern China which is vulnerable to the occurrence of landslides. Previous studies focused on rain-induced shallow landslides. Some deep-seated landslides in red clay with a gentle inclination are still not well understood. A fatal landslide named as Zhengjiamo landslide, located in Tianshui, China, was investigated. The aim of this study was to study mechanism of shear surface development under earthquake using a series of cyclic triaxial tests. The test results of the red clay from the Zhengjiamo landslide revealed that the undrained shear strength and excess pore pressure increase with increasing confining stresses σ 3 and OCR. It is also observed that those stress–strain behaviors on the deviatoric stress, axial strain and pore water pressure, subsequent to the initial contractive response, the saturated clay exhibited dilation upon continued shearing. The dilated tendency of the clay becomes more prevalent with increasing confining stresses σ 3 and OCR during the dynamic response. The reduction of shear strength of the red clay is substantially caused by the increasing number of cycles N. Under earthquakes, the sliding zone may behave in a brittle- ductile pattern. [ABSTRACT FROM AUTHOR]

A field investigation of the Huangtupo landslide in the Three Gorges Reservoir area, China, indicated that the particle-size distribution—characterized by an index termed the fractal dimension—varied along the main sliding direction: the fractal dimension tended to increase in this direction. A preliminary study of the spatial variability of the slip zone based upon the fractal dimension was performed. Remolded soil samples with various fractal dimensions obtained from the Huangtupo landslide were prepared for laboratory testing that was carried out to determine the effect of the fractal dimension on the micro and macro behavior of the soils. The microstructure of each soil sample was determined using scanning electron microscopy, while its macromechanical properties were evaluated via consolidated undrained triaxial tests. The results showed that there were close relationships of the fractal dimension with the microstructure, stress-strain behavior, and shear strength. The test results were also consistent with the results of the field investigation of the Huangtupo landslide. Thus, the fractal dimension can be used as an indicator of the spatial variability of the slip zone of a landslide. [ABSTRACT FROM AUTHOR]

Because of the inherent spatial variability of soil properties and the limited number of boreholes that can be afforded in a typical project, the soil properties at given geotechnical sites could not be known with certainty, which leads to an uncertainty in the predicted performance of a geotechnical system. For such uncertain system, probabilistic analysis is often used to assess its performance considering uncertainty. This paper presents a new framework for the probabilistic analysis of tunnel longitudinal performance. Within this framework, the conditional random field theory is adopted to simulate the spatial variation of soil properties along the tunnel longitudinal direction, in which the soil properties at borehole locations can be explicitly considered. Then, the tunnel longitudinal performance is analyzed with an advanced tunnel performance model, in which the influence of tunnel longitudinal behavior on the circumferential behavior of the tunnel cross section can be explicitly considered. With the aid of Monte Carlo simulation (MCS), tunnel longitudinal performance can readily be analyzed in a probabilistic manner; and, the variation of the tunnel performances (i.e., the structural safety and serviceability of the cross section) along the tunnel longitudinal direction could be assessed. The novelty and significance of this proposed framework, compared to the existing methods, are demonstrated through an illustrative example. Further, the influence of the borehole density (i.e., the number of boreholes per tunnel length) on the prediction of the tunnel longitudinal performance is analyzed through a parametric study. [ABSTRACT FROM AUTHOR]

Deep-seated mudstone landslides are widely distributed in northwest China. The Zhengjiamo landslide occurred in 734 CE near Taijing, Tianshui region. It was triggered by the main shock of the historical Ms = 7.0734 CE earthquake. The earthquake also induced a wide range of landslides in this area, with hundreds of fatalities and many houses destroyed by landslide debris. Based on a detailed field survey, borehole data, and mapping, a detailed geological reconstruction of the slope was achieved and the geo-mechanical features of the claystone involved in the landslide were obtained. Using the Particle Flow Code to simulate the mechanism of the Zhengjiamo landslide, the features of the landslide dynamics were obtained using a 5-stage model. During the landslide process, the slip mass at the front and upper edges exhibited higher mobility than at the rear and bottom edges. Furthermore, the contact bond strength of the sliding body gradually weakened. The model indicates that the particle bond strength has a larger influence on the maximum runout distance and landslide debris morphology than the type of weak intercalated layers. The slip mass presented a rotational slide pattern and remained on the slip plane throughout the sliding process. Finally, the earthquake uplifted the slope toe, which prevented the slip mass from gliding. The modelled scenario provided a reasonably good fit to the actual topography, verifying the modelling results. After the historical earthquake, with the clay minerals swelling and shrinking under rainfall and efflorescence conditions, the structure of the soft rock changed, contributing to the weakening of the sliding rock mass. The landslide gradually crept and evolved to its current topography. [ABSTRACT FROM AUTHOR]

The deformation and failure mechanism of landslides caused by reservoir water operations is a significant problem that is being addressed by researchers. The Xiaochatou Landslide in the Wudongde Reservoir area is taken as an example for the performance of centrifugal model tests under gravel conditions with the rapid drawdown of the reservoir water level. The data concerning the displacement and pore water pressure during this process show that the Xiaochatou Landslide, which is a complex landslide containing a shallow slide mass, middle slide mass and deep slide mass, is extremely sensitive to the rapid drawdown of the water level. The centrifuge tests show that the shallow slide mass will fail and that the middle slide mass will suffer a large displacement after a rapid decrease in the reservoir water level. Furthermore, the Xiaochatou Landslide exhibits the characteristics of retrogressive failure. [ABSTRACT FROM AUTHOR]

The response of a loess-mudstone landslide model to seismic activity is examined using centrifuge shaking table tests and 2D seismic input waves. The physical model of a dormant landslide is subjected to simulated seismic signals of different input amplitudes, and the dynamic response is analyzed in terms of relative peak ground acceleration (PGA), which is used to assess deformation and failure mechanisms of the slope. Relative PGA increases with increasing landslide height, reaching maximum values at the crest, while values at the toe are slightly larger than those in the middle of the slope. Relative PGA is the highest along the outer surface and weakest along the sliding surface. Horizontal values are generally larger than vertical values, and the amplitude of the seismic input strongly affects the landslide dynamic response. The PGA amplification factors increase considerably with increasing input amplitude, reaching maximum values at 0.3-0.4 g, and then decrease. The largest displacement is observed at the crest, while displacements in the middle part and at the toe increase steadily with higher input amplitudes, and displacement at the crest increases at a higher, irregular rate. Deformation is most apparent at the crest, developing from cracks into collapsed soil deposited at the toe. Local shallow sliding is observed along the landslide surface, and the dormant sliding body may generate displacement along the sliding surface caused by earthquake reactivation. A numerical model of the landslide provides results consistent with centrifuge model testing; both indicate similarity in seismically induced dynamic responses and failure characteristics. [ABSTRACT FROM AUTHOR]

Dynamic behavior and failure mechanism of slope during earthquake are hot topics in geotechnical engineering community. In Tianshui area, Northwest of China, the deformation features of loess-mudstone slopes induced by earthquakes are still not well understood. The current study aims to discuss the dynamic behavior of the slope under earthquake, by performing a series of centrifuge shaking table tests and numerical simulations. The results are processed for PGA amplificatory effect study and to evaluate the earthquake induced deformation mechanism. Better agreement is obtained between the results of numerical simulations and centrifuge tests. The results indicated that the acceleration response of the loess-mudstone slope showed several amplifying characteristic: the height effect, lithologic effect and surface effect. It also proves that the displacements in the loess layer are much larger than mudstone. As the input amplitude increased, the shear plastic zone developed along a further slide surface. Tension plastic zone mainly occurred at the crest. Roughly, the regions of earthquake induced deformation state increased with the increase in amplitude of earthquake wave. Deformations occurred at the upper part of the slope. Tensile cracks evolved on the crest and the upper part of slope in loess layer, moreover, failures occurred at slope surface, and only slight deformation at slope toe. Deformations with continuous shear cracks and slope surface upheavals developed at the middle part of slope. [ABSTRACT FROM AUTHOR]

In this paper, we study the effect of the amplitude of input shaking on the dynamic response of a loess-mudstone slope through a series of staged centrifuge tests, including different amplitude earthquake excitations, in which the seismic performance of the slope models was analyzed and investigated. The derived outputs were processed to study the earthquake acceleration amplification effect and to assess the induced deformation mechanism in terms of the resulting displacements and deformation mode. The test results indicated that the amplification factors of peak ground acceleration (PGA) increased with increasing slope height, reaching maximum values at the crest. The amplification effect was also demonstrated on the slope surface. In addition, the predominant amplitude of the input seismic excitation was critical to the response of the slope. The results proved that the displacements in the loess layer were much larger than those in the weathered mudstone. Tensile cracks were formed mainly on the crest and the upper part of the slope, and failure modes were dominant at the slope surface. The location of the slide plane in the model was consistent with the location of maximum acceleration. A continuous shallow slide plane was formed in the loess layer. The analysis provides good information for identifying both surface movement and mass movement. [ABSTRACT FROM AUTHOR]

Tianshui City is located in a seismically active region of China. Historically, many earthquakes with magnitudes of 6.0-8.0 have been reported in this area, and most of loess-red mudstone landslides in this area are known to have been triggered by earthquakes. However, the soil dynamics under earthquakes in the Tianshui area have been little studied. Therefore, to understand the dynamic stress-strain behavior of undisturbed soils during the earthquake, cyclic and shear strength tests were conducted on soil samples (loess and weathered red mudstone) obtained from Tianshui in a cyclic triaxial test system. Two types of laboratory tests were carried out on two kinds of soils. The first type involved the tests with different cyclic stress ratios applied and the number of cycles N more than 20, while the second type are series of stress-controlled undrained reverse-shear tests. By doing so, the differences on stress condition on the behavior of Young's modulus E , stress-strain and shear strength were measured. In addition, tests modeling natural seismic loading were also carried out for comparative purposes. Some residual shear behaviors were also recognized. The results of a series of tests designed to study the stress-strain behavior of undisturbed soils under repeated loading are presented. These tests will provide useful parameters (e.g. λ and E ) for analysis of slope stability during earthquakes and earthquake-resistant design. [ABSTRACT FROM AUTHOR]

• Flow behaviors are associated with fracture heterogeneity and the filling conditions. • Filling particles result in two competing mechanisms impacting flow regime in fractures. • Fracture walls confining the fluid flow significantly reduce the media permeability. • A semi-empirical model for predicting water flow in filled fractures is proposed. Fluid flow through filled rock fractures is relevant to numerous engineering applications and geophysical processes. However, a proper understanding of the flow behaviors in filled fractures is still far from being completed. To investigate the fluid flow in a rough-walled fracture filled with a porous medium, we systematically compare the micro- and macroscopic flow behaviors within filled fractures and corresponding open fractures and porous media based on a series of pore-scale simulation results. We find that the filling medium has a dual role in altering the flow regime, as the filling particles can not only cut the flow domain into several pore channels and thus limit the generation of large-span eddies, but also force the fluid to flow around them and promote the generation of local eddies. Compared with porous media, the fluid flow within filled fractures is confined by fracture walls, which greatly alters the media permeability and the flow nonlinearity therein. By introducing the hydraulic radius and Darcy-Weisbach equation, we develop a new semi-empirical model to estimate the fluid flow through filled fractures using phenomenological coefficients of corresponding open fractures and porous media. The proposed model, satisfying dimensional consistency, shows high fidelity in predicting water flow through filled fractures. More importantly, this model can be successfully reduced to the typical form of the Forchheimer equation applied to open fractures and porous media. The results and findings are expected to be useful in predicting and evaluating the fluid flow in complex geological setting. [ABSTRACT FROM AUTHOR]

Earthquake waves influence rock toppling stability, and the effects of local earthquake propagation and topographic also affect slope deformation. Detailed engineering geology conditions of slopes are obtained and a geomechanical characterization of rock topplings is performed. To study the input earthquake waves and slope interactions, a dynamic analysis is performed using the UDEC 4.0 discrete element method (DEM) numerical code under viscoplastic conditions. The earthquake signals are representative of different peak ground acceleration, Arias intensities, and frequencies, and are used in the study of different rock topplings with different height, slope angle, and strata dip angle. The derived outputs are processed for the earthquake propagation study and to assess the induced deformation mechanisms in terms of resulting displacements, plastic zone features, and deformation mode. The results prove that an interaction exists between stratigraphic and topographic effects on earthquake wave propagation, and that these effects cannot be assessed independently. The obtained results describe the effect of topography and geological settings in rock topplings, amplifying or de-amplifying earthquake ground motion, and demonstrate that the tensile state dominates at the slope surface but evolves with depth. A shear state dominates at the toe or in the deep part of rock topplings. The rock toppling deformation mode may develop into a composite of tension fractures at the crest and sliding at depth. Compared with the static scenario, under earthquake load, tensile deformation evolves over a larger area at the crest and develops a shear zone at the toe and in the substrata. The necessary earthquake-induced toppling conditions are discussed, and the UDEC 4.0 DEM method and conventional pseudostatic approach are compared. This study shows there are a broader range of deformations inside the slope. [ABSTRACT FROM AUTHOR]

Evaluation of uncertainties associated with landslide displacement prediction is essential for improving the reliability of landslide early warning systems. An efficient probabilistic forecasting method for the construction of prediction intervals (PIs) using bootstrap and kernel-based extreme learning machine (ELM) is proposed. To overcome the drawbacks of artificial neural networks (ANNs) in predicting mutational displacement points with time lags, this paper proposes an ANNs switched prediction scheme to construct PIs with a three-stage formulation. In the first stage, K-means clustering is applied to divide the whole training dataset into two sub-training sets: the stationary points and the mutational points. In the second stage, a weighted ELM classifier is applied to construct the switched rules. In the third stage, bootstrap- and kernel-based ELMs are applied to construct candidate PIs for each sub-training set. The final PIs are constructed by switching between these two candidate PIs. The effectiveness of the proposed ANNs switched prediction method has been validated through comprehensive tests using three real-world landslide datasets from the Three Gorges region of China. [ABSTRACT FROM AUTHOR]

Complexity of analysis of landslide hazard is due to uncertainty. In this study, a novel approach multi-gene genetic programming based on separable functional network (MGGPSFN) is presented for predicting landslide displacement. Moreover, Pearson's cross-correlation coefficients and mutual information are adopted to look for the potential input variables for a forecast model in the paper. The performance of new model is verified through one case study in Baishuihe landslide in the Three Gorges Reservoir in China. In addition, we compared it with two methods, back-propagation neural network and radial basis function, and MGGPSFN got the best results in the same measurements. [ABSTRACT FROM AUTHOR]

To evaluate the possibility of utilizing commercially available devices for making joint roughness estimates, a digital single-lens reflex (DSLR) camera and a smartphone were used to reconstruct the three-dimensional models of 10 rock-joint specimens. The accuracy and efficiency were considered in investigating the performance of photogrammetry on the point clouds production and joint roughness estimation in the laboratory. Additionally, a handheld laser scanner was used in collecting high-resolution point clouds of the same specimens as reference data for evaluating the photogrammetry measurement accuracy. The interval for image capture was set at 8° with consideration for the data quality, point density, and computation time. The iterative closest point (ICP) algorithm was used to compare the surface topographies of the rock joints produced via photogrammetry and laser scanning. The point clouds generated by photogrammetry agreed with the laser-scanning results, with a small average difference (0.005 mm for the DSLR camera and 0.006 mm for the smartphone). Furthermore, two- and three-dimensional surface parameters were calculated using the three different sources of point clouds, which were in good agreement in the joint roughness estimates when comparing photogrammetry and laser scanning results. Comparative analyses revealed that both DSLR camera photogrammetry and smartphone photogrammetry can produce accurate point clouds of rock joints for roughness assessment; however, point clouds generated by the DSLR camera had higher accuracies than those generated by the smartphone. • The lens parameters determined in camera calibration differ from the nominal ones. • Interval between two camera positions affects the data accuracy and computation time. • Point clouds from photogrammetry are in good agreement with laser scanning data. • Similar estimates of joint roughness from photogrammetry and laser scanning data. • DSLR camera photogrammetry outperforms the smartphone for rock joint reconstruction. [ABSTRACT FROM AUTHOR]

Complex block-flexure slope toppling is observed in interbedded sandstone and slate in the upper Yellow River, China. Block toppling is observed in the relatively hard sandstone and flexural toppling is observed in the relatively soft slate. The evolution of toppling slope deformation is characterized by long-term progress and spatial variability. In order to study these characteristics, field investigations, adit prospecting, borehole drilling, sonic tests and numerical simulation were carried out. In addition, the effect of the structure, the composite mode of the rock mass, the unloading fissures and geomorphology are discussed. Furthermore, we explored the toppling mechanisms and simulated it numerically; on this basis, the slope evolution is divided into four stages. Results obtained from the numerical simulation compared well with field investigation data (investigation data, rock sonic survey and strata dip statistics). Comparative studies have demonstrated that the analytical methods presented in this paper are appropriate for back analysis of the toppling evolution process. The result showed that this toppling slope has not yet entered the later progressivity failure stage and is currently limited to collapse at shallow levels, whereas the deep-seated rock mass will remain stable for a long time. This study might provide reference for a stability evaluation and hazard prevention analysis for rock toppling. [ABSTRACT FROM AUTHOR]

Landslide early warning systems can be implemented based on the monitoring and prediction of landslide displacements. The internal mechanisms of landslides are very complex, and precise mechanistic models of landslides are difficult to obtain; therefore, data-driven models are usually applied. From the perspective of dynamic system theory, landslide development should be considered a dynamic process. Because traditional models, such as feed-forward neural networks, can only express static relationships, the applicability of these static models is quite limited in landslide prediction tasks. In our study, recurrent neural networks are established and trained into dynamic predictors of landslide displacement using a training algorithm named reservoir computing. A shortcoming of the reservoir computing algorithm is that the models will not perform well with insufficiently large training sets. Because practical landslide displacement recordings are usually quite short, interpolation techniques are employed to enhance the training of the dynamic predictors. The method proposed in this paper is applied to predict the developments of three landslides in the Three Gorges area, and the predicted values are close to the actual measurements. Improvements relative to sophisticated static predictors and basic dynamic predictors are obvious. [ABSTRACT FROM AUTHOR]

Landslide prediction is always the emphasis of landslide research. Using global positioning system GPS technologies to monitor the superficial displacements of landslide is a very useful and direct method in landslide evolution analysis. In this paper, an EEMD-ELM model [ensemble empirical mode decomposition (EEMD) based extreme learning machine (ELM) ensemble learning paradigm] is proposed to analysis the monitoring data for landslide displacement prediction. The rainfall data and reservoir level fluctuation data are also integrated into the study. The rainfall series, reservoir level fluctuation series and landslide accumulative displacement series are all decomposed into the residual series and a limited number of intrinsic mode functions with different frequencies from high to low using EEMD technique. A novel neural network technique, ELM, is employed to study the interactions of these sub-series at different frequency affecting landslide occurrence. Each sub-series extracted from accumulative displacement of landslide is forecasted respectively by establishing appropriate ELM model. The final prediction result is obtained by summing up the calculated predictive displacement value of each sub. The EEMD-ELM model shows the best accuracy comparing with basic artificial neural network models through forecasting the displacement of Baishuihe landslide in the Three Gorges reservoir area of China. [ABSTRACT FROM AUTHOR]

Landslide hazard is a complex nonlinear dynamical system with uncertainty. The evolution of landslide is influenced by many factors such as tectonic, rainfall and reservoir level fluctuation. Using a time series model, total accumulative displacement of landslide can be divided into the trend component displacement and the periodic component displacement according to the response relation between dynamic changes in landslide displacement and inducing factors. In this paper, a novel neural network technique called ensemble of extreme learning machine (E-ELM) is proposed to investigate the interactions of different inducing factors affecting the evolution of landslide. Grey relational analysis is used to sieve out the more influential inducing factors as the inputs in E-ELM. Trend component displacement and periodic component displacement are forecasted, respectively; then, total predictive displacement is obtained by adding the calculated predictive displacement value of each sub. Performances of our model are evaluated by using real data from Baishuihe landslide in the Three Gorges Reservoir of China, and it provides a good representation of the measured slide displacement behavior. [ABSTRACT FROM AUTHOR]

Site characterization, which aims to characterize the subsurface stratigraphic configuration and the associated geo-properties, has long been a significant challenge in geological and geotechnical practice. Due to the complexity and inherent spatial variability of the geological bodies and the limited availability of borehole data, uncertainty is unavoidable in the characterized subsurface stratigraphic configuration and the associated geo-properties. In previous studies, the stratigraphic uncertainty and the geo-properties uncertainty were characterized separately. This paper proposes a conditional random field approach for a coupled characterization of stratigraphic and geo-properties uncertainties. The spatial correlation of the stratum existence between different subsurface elements and the spatial correlation of geo-properties are characterized by two autocorrelation functions, determined with the maximum likelihood principle. With the knowledge of the spatial correlation of the stratum existence, the stratigraphic configuration can be sampled using a modified random field approach. Then, the spatial correlation of the geo-properties is updated based on the sampled stratigraphic configuration. With the updated spatial correlation of the geo-properties, the spatial distribution of the geo-properties can readily be simulated with the conditional random field theory. The effectiveness of the proposed approach is demonstrated through a case study of probabilistic site characterization of an offshore wind farm site in Taiwan. To extend the applicability of the proposed approach, a probabilistic evaluation of liquefaction potential at this site under a given seismic shaking level is performed. • A probabilistic method for characterizing the geological model is proposed. • Characterizations of stratigraphic and geo-properties uncertainties are coupled. • Stratigraphic configuration is simulated with modified random field approach. • Spatial variability of geo-properties is simulated with conditional random field. • The spatial correlation structure is estimated with maximum likelihood principle. [ABSTRACT FROM AUTHOR]

• Solute transport in fractures with slip BC was studied by pore-scale simulations. • Effect of slip BC on solute transport was manifested over the entire flow regime. • Influencing mechanisms of slip BC were elucidated under different flow regimes. Fundamental understanding of solute transport behaviors in rock fractures is of great importance to many hydrogeological processes. The fate of fluid-borne solutes is inherently linked to fluid flow process in rock fractures, which is usually theoretically and numerically analyzed under the assumption of classic no-slip boundary condition. However, fluid slippage at rock surfaces is possibly present in some geological environments, such as hydrophilicity change in rock surfaces exposed to organic substances, or the immobile wetting film covering rock surfaces. These situations would induce a non-zero velocity at the boundary walls for flowing fluid, i.e., fluid slippage, which leads to a violation of the no-slip assumption. Nonetheless, the effect of slippery boundary on fluid-borne solute transport is poorly understood for rock fractures. This study systematically investigated the slippery boundary effect on solute transport in rough-walled rock fractures under different flow regimes. A series of pore-scale simulation results showed that the slippery boundary has a profound influence on both microscale and macroscale solute transport behaviors in rock fractures. Such an influence became more significant with increasing hydraulic gradient, accompanied by the flow regime transitioning from Darcy to non-Darcian. For Darcy flow regime, the slippery boundary exerted its influence on solute transport by altering velocity distribution pattern in rock fracture; while for non-Darcian flow regime, the enlarged eddy volume and promoted mass transfer process by the slippery boundary profoundly affected solute transport behaviors. Further discussion indicated that the predictive models with parameters estimated from the conventional no-slip boundary condition cannot directly apply to the slip one. Moreover, the effect of slippery boundary would possibly have an impact on larger-scale fractured rock aquifers which requires further verification. The results and findings enrich the understanding of solute transport in fractured rocks where the slippery boundary is prevalently present, and contribute to developing predictive models for complex geological environments. [ABSTRACT FROM AUTHOR]

Accurate and precise characterization of the subsurface stratigraphic configuration (geological model) at a given site is crucial to geotechnical engineering work. The uncertainty in the derived stratigraphic configuration can be significant, due to the strata's complexity and inherent spatial variability coupled with the limited availability of borehole data. The characterization and reduction of this uncertainty should be part of any site characterization project. This paper presents a method for characterization of the subsurface stratigraphic configuration with limited borehole data. Within the framework of the proposed method, the spatial correlation between the existence of a stratum in one subsurface zone and that in the other subsurface zone (or the spatial correlation of the existence of the stratum) is captured by an autocorrelation function determined with the maximum likelihood principle. The initial stratigraphic configurations are first sampled with the conditional random field theory. Next, the maximum-a-posteriori (MAP) estimates of the initial stratigraphic configurations are derived using Markov Chain Monte Carlo (MCMC) and taken as the final stratigraphic realizations. The effectiveness of the proposed method and its advantages over the existing stratigraphic characterization methods are demonstrated through a series of comparative analyses. The versatility of the new approach in modeling the 3-D stratigraphic configuration is further revealed through a case study of a site in Western Australia. This paper adds to the literature on stratigraphic uncertainty characterization and provides a basis for a risk-based geotechnical assessment that considers geological and geotechnical uncertainties. • A probabilistic method for characterizing stratigraphic configuration is proposed. • The spatial correlation of strata is estimated with maximum likelihood principle. • Conditional random field theory and MCMC method are included in this method. • Versatility of this method in modeling 3-D stratigraphic configurations is studied. [ABSTRACT FROM AUTHOR]

• Water inflow into a tunnel under non-Darcian flow regime is numerically investigated. • A semi-empirical model for predicting tunnel inflow is proposed based on Forchheimer law. • Necessity of considering non-Darcian effect for tunnel inflow is proven in a large number of engineering cases. Water inflow into a tunnel is usually estimated by assuming that the flow follows the linear Darcy's law. However, fluid flow in fractured-rock aquifers is prone to deviation from Darcy's law and gives rise to nonlinear flow phenomena due to significant inertial losses. This non-Darcian effect is seldom considered when evaluating water inflow into the tunnel in a fractured-rock aquifer. In this study, we investigated an analytical method for predicting water inflow into a tunnel considering the non-Darcian effect. A series of numerical simulations for water inflow into a tunnel were conducted with different combinations of parameters, where non-Darcian flow was considered and characterized by the Forchheimer's law. Based on the numerical results and an ingenious parameter integration method, a semi-empirical model was developed to analytically predict water inflow into a tunnel where the flow is under non-Darcian flow regime. The semi-empirical model includes the classic theoretical formula for predicting water inflow and the Forchheimer equation for describing non-Darcian flow. In this context, the non-Darcian effect on water inflow into a tunnel can be quantitatively estimated. This developed model has a concise expression satisfying dimensional consistency with the parameters having sound physical meanings, and it can be successfully reduced to the classic formula under the Darcy flow regime. The validity of this semi-empirical model was confirmed by numerical results, showing a high fidelity in predicting water inflow into a tunnel. By means of this proposed model, the error induced by neglecting non-Darcian effect was estimated for a large number of real engineering cases, which rapidly increased as a power function with the magnitude of water inflow into the tunnel. The necessity of considering the non-Darcian effect when calculating water inflow was thus proven, especially for massive tunnel gushing. The proposed model and the method used in this study can provide guidance for accurately predicting water inflow into a tunnel under a complex non-Darcian flow regime. [ABSTRACT FROM AUTHOR]

The interferometric synthetic aperture radar (InSAR) technique is widely adopted for detecting and monitoring landslides, but its effectiveness is often degraded in mountainous terrains, due to geometric distortions in the synthetic aperture radar (SAR) image input. To evaluate the terrain effect on the applicability of InSAR in landslide monitoring, a variety of visibility evaluation models have been developed, among which the R-index models are quite popular. In consideration of the poor performance of the existing R-index models in the passive layover region, this study presents an improved R-index model, in which a coefficient for improving the visibility evaluation in the far passive layover regions is incorporated. To demonstrate the applicability of the improved R-index model, the terrain visibility of SAR images in Fengjie, a county in the Three Gorges Reservoirs region, China, is studied. The effectiveness of the improved R-index model is demonstrated through comparing the visibility evaluation results with those obtained from the existing R-index models and P-NG method. Further, the effects of the line-of-sight (LOS) parameters of SAR images and the resolution of the digital elevation model (DEM) on the terrain visibility are discussed. [ABSTRACT FROM AUTHOR]