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The main aim of this study is to propose a novel hybrid intelligent model named MBSVM which is an integration of the MultiBoost ensemble and a support vector machine (SVM) for modeling of susceptibility of landslides in the Uttarakhand State, Northern India. Firstly, a geospatial database for the study area was prepared, which includes 391 historical landslides and 16 landslide-affecting factors. Then, the sensitivity of different combinations of these factors for modeling was validated using the forward elimination technique. The MBSVM landslide model was built using the datasets generated from the best selected factors and validated utilizing the area under the receiver operating characteristic (ROC) curve (AUC), statistical indexes, and the Wilcoxon signed-rank test. Results show that this novel hybrid model has good performance both in terms of goodness of fit with the training dataset (AUC = 0.972) and the capability to predict landslides with the testing dataset (AUC = 0.966). The efficiency of the proposed model was then validated by comparison with logistic regression (LR), a single SVM, and another hybrid model of the AdaBoost ensemble and an SVM (ABSVM). Comparison results show that the MBSVM outperforms the LR, single SVM, and hybrid ABSVM models. Thus, the proposed model is a promising and good alternative tool for landslide hazard assessment in landslide-prone areas.

This paper presents recommended methodologies for the quantitative analysis of landslide hazard, vulnerability and risk at different spatial scales (site-specific, local, regional and national), as well as for the verification and validation of the results. The methodologies described focus on the evaluation of the probabilities of occurrence of different landslide types with certain characteristics. Methods used to determine the spatial distribution of landslide intensity, the characterisation of the elements at risk, the assessment of the potential degree of damage and the quantification of the vulnerability of the elements at risk, and those used to perform the quantitative risk analysis are also described. The paper is intended for use by scientists and practising engineers, geologists and other landslide experts.

Large squeezing deformation has always been a critical concern in the construction of deep-buried tunnels in soft-weak rock masses. This paper describes a case study on the large deformation mechanism and supporting method of the Maoxian tunnel in Sichuan Province, China, which is located in the core area influenced by the 2008 Wenchuan earthquake and suffered severe large deformation in broken phyllite under high geo-stress. Through a survey on the geological features, the deformation mechanism of surrounding rock and the failure characteristics of supporting structures of the Maoxian tunnel in F1 fault zone were studied. It was found that the occurrence of large deformation was due to the combined action of the high geo-stress and poor self-stability of carbonaceous phyllite. In order to control the squeezing deformation, single and double primary support methods were adopted in succession. A comparative field test was conducted to study their supporting mechanism and mechanical behavior in terms of surrounding rock pressure, internal stress of the steel arch, and axial force and bending moment of the secondary lining. The results revealed that the single primary support method cannot ensure the long-term safety of the tunnel, since many cracks in concrete occurred after about 180 days. The double primary support method, however, was able to control the large deformation and rheological effects of broken phyllite under high geo-stress effectively.

Geological discontinuities have a controlling influence for many rock-engineering projects in terms of strength, deformability and permeability, but their characterisation is often very difficult. Whilst discontinuities are often modelled as lacking any strength, in many rock masses visible rock discontinuities are only incipient and have tensile strength that may approach and can even exceed that of the parent rock. This fact is of high importance for realistic rock mass characterisation but is generally ignored. It is argued that current ISRM and other standards for rock mass characterisation, as well as rock mass classification schemes such as RMR and Q, do not allow adequately for the incipient nature of many rock fractures or their geological variability and need to be revised, at least conceptually. This paper addresses the issue of the tensile strength of incipient discontinuities in rock and presents results from a laboratory test programme to quantify this parameter. Rock samples containing visible, natural incipient discontinuities including joints, bedding, and mineral veins have been tested in direct tension. It has been confirmed that such discontinuities can have high tensile strength, approaching that of the parent rock. Others are, of course, far weaker. The tested geological discontinuities all exhibited brittle failure at axial strain less than 0.5 % under direct tension conditions. Three factors contributing to the tensile strength of incipient rock discontinuities have been investigated and characterised. A distinction is made between sections of discontinuity that are only partially developed, sections of discontinuity that have been locally weathered leaving localised residual rock bridges and sections that have been ‘healed’ through secondary cementation. Tests on bedding surfaces within sandstone showed that tensile strength of adjacent incipient bedding can vary considerably. In this particular series of tests, values of tensile strength for bedding planes ranged from 32 to 88 % of the parent rock strength (intact without visible discontinuities), and this variability could be attributed to geological factors. Tests on incipient mineral veins also showed considerable scatter, the strength depending upon the geological nature of vein development as well as the presence of rock bridges. As might be anticipated, tensile strength of incipient rock joints decreases with degree of weathering as expressed in colour changes adjacent to rock bridges. Tensile strengths of rock bridges (lacking marked discolouration) were found to be similar to that of the parent rock. It is concluded that the degree of incipiency of rock discontinuities needs to be differentiated in the process of rock mass classification and engineering design and that this can best be done with reference to the tensile strength relative to that of the parent rock. It is argued that the science of rock mass characterisation may be advanced through better appreciation of geological history at a site thereby improving the process of prediction and extrapolating properties.

Acoustic emission (AE) is dened as high-frequency elastic waves emitted from defects such as small cracks (microcracks) within a material when stressed, typically in the laboratory. AE is a similar phenomenon to microseismicity (MS), as MS is induced by fracture of rock at an engineering scale (e.g., rockbursts in mines), that is, in the eld. Thus, seismic monitoring can be applied to a wide variety of rock engineering problems, and AE is a powerful method to investigate processes of rock fracture by detecting microcracks prior to macroscopic failure and by tracking crack propagation. A basic approach involves using a single channel of data acquisition, such as with a digital oscilloscope, and analyzing the number and rate of AE events. Perhaps the most valuable information from AE is the source location, which requires recording the waveform at several sensors and determining arrival times at each. Thus, investing in a multichannel data acquisition system provides the means to monitor dynamics of the fracturing process. The purpose of this suggested method is to describe the experimental setup and devices used to monitor AE in laboratory testing of rock.

Joints and fissures with similar orientation or characteristics are common in natural rocks; the inclination and density of the fissures affect the mechanical properties and failure mechanism of the rock mass. However, the strength, crack coalescence pattern, and failure mode of rock specimens containing multi-fissures have not been studied comprehensively. In this paper, combining similar material testing and discrete element numerical method (PFC2D), the peak strength and failure characteristics of rock-like materials with multi-fissures are explored. Rock-like specimens were made of cement and sand and pre-existing fissures created by inserting steel shims into cement mortar paste and removing them during curing. The peak strength of multi-fissure specimens depends on the fissure angle α (which is measured counterclockwise from horizontal) and fissure number ( N f ). Under uniaxial compressional loading, the peak strength increased with increasing α . The material strength was lowest for α  = 25°, and highest for α  = 90°. The influence of N f on the peak strength depended on α . For α  = 25° and 45°, N f had a strong effect on the peak strength, while for higher α values, especially for the 90° sample, there were no obvious changes in peak strength with different N f . Under uniaxial compression, the coalescence modes between the fissures can be classified into three categories: S-mode, T-mode, and M-mode. Moreover, the failure mode can be classified into four categories: mixed failure, shear failure, stepped path failure, and intact failure. The failure mode of the specimen depends on α and N f . The peak strength and failure modes in the numerically simulated and experimental results are in good agreement.

Globally, and in China, landslides constitute one of the most important and frequently encountered natural hazard events. In the present study, landslide susceptibility evaluation was undertaken using novel ensembles of bivariate statistical-methods-based (evidential belief function (EBF), statistical index (SI), and weights of evidence (WoE)) kernel logistic regression machine learning classifiers. A landslide inventory comprising 222 landslides and 15 conditioning factors (slope angle, slope aspect, altitude, plan curvature, profile curvature, stream power index, sediment transport index, topographic wetness index, distance to rivers, distance to roads, distance to faults, NDVI, land use, lithology, and rainfall) was prepared as the spatial database. Correlation analysis and selection of conditioning factors were conducted using multicollinearity analysis and classifier attribute evaluation methods, respectively. The receiver operating characteristic curve method was used to validate the models. The areas under the success rate (AUC_T) and prediction rate (AUC_P) curves and landslide density analysis were also used to assess the prediction capability of the landslide susceptibility maps. Results showed that the EBF-KLR hybrid model had the highest predictive capability in landslide susceptibility assessment (AUC values of 0.814 and 0.753 for the training and validation datasets, respectively; AUC_T value of 0.8511 and AUC_P value of 0.7615), followed in descending order by the SI-KLR and WoE-KLR hybrid models. These findings indicate that hybrid models could improve the predictive capability of bivariate models, and that the EBF-KLR is a promising hybrid model for the spatial prediction of landslides in susceptible areas.

Early warning of rockbursts remains a worldwide challenge in rock engineering. In this work, a microseismicity-based method of rockburst warning in tunnels is proposed to warn of and reduce the risk of rockburst. The method uses real-time microseismic data and an established rockburst warning formula to provide dynamic warning of rockburst risk during excavation of a tunnel. The establishment of the rockburst warning formula involves several key parts. These include a rockburst database, selection of typical rockburst cases, functional relationships between microseismicity and rockbursts, optimal weighting coefficients, and dynamic updating. By using the proposed method, the probability of strain and strain-structure slip rockbursts of different intensity (extremely intense, intense, moderate, slight, and none) can be warned of in real time. The method has been successfully applied to rockburst warning in deeply buried tunnels at the Jinping II hydropower project (about 11.6 km in total for D & B tunnels). This success illustrates the applicability of the proposed method. In addition, it is found that during the rockburst development process, the microseismic eigenvalues for strainbursts are bigger than in strain-structure slip rockbursts of the same intensity.

A major consideration in urban tunnel design is to estimate the ground movements and surface settlements associated with the tunnelling operations. Excessive ground movements may result in damage to adjacent buildings and utilities. Numerous empirical and analytical solutions have been proposed to relate the shield tunnel characteristics and surface/subsurface deformation. Numerical analyses, either 2D or 3D, have also been applied to such tunnelling problems. However, substantially fewer approaches have been developed for earth pressure balance (EPB) tunnelling. Based on instrumented data on ground deformation and shield operation from three separate EPB tunnelling projects in Singapore, this paper utilizes a multivariate adaptive regression splines (MARS) approach to establish relationships between the maximum surface settlement and the major influencing factors, including the operation parameters, the cover depth and the ground conditions. Since the method has the ability to map input to output patterns, MARS enables one to map all influencing parameters to surface settlements. The main advantages of MARS over other soft computing techniques such as ANN, RVM, SVM and GP are its capacity to produce a simple, easy-to-interpret model, its ability to estimate the contributions of the input variables, and its computational efficiency.

During the past decade’s exploitation of coal seams in Muchengjian Mine in Jingxi Coalfield, there were nearly thirty rock burst events, which hindered the safe and efficient coal production. Two typical mining areas were selected for analysis where almost half of rock burst events occurred. The research was aimed at finding connections between the occurrence of rock bursts and geological characteristics. The temporal and spatial characteristics of rock bursts were described in detail, the geological characteristics were investigated carefully, and the possible reasons for rock bursts were analyzed. The details documented in these cases not only provide an essential reference value for understanding the development mechanism of rock bursts, but also provide a basis for selecting control measures and optimizing related technical parameters during tunneling or mining under complicated geological conditions.