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Centrifugal model tests can accelerate the characterization of landslides and demonstrate the form of slope failure, which is an important measure to research its instability mechanisms. Simply observing the slope landslide before and after a centrifugal model test cannot reveal the processes involved in real-time deformation. Electromagnetic sensors have severed as an existing method for real-time measurement, however, this approach has significant challenges, including poor signal quality, interference, and complex implementation and wiring schemes. This paper aims to overcome the shortcomings of the existing measurement methods.

This work uses the advantages of fiber Bragg grating (FBG) sensors with their small form-factor and potential for series multiplexing in a single fiber to demonstrate a monitoring strategy for model centrifugal tests. A slope surface deformation displacement sensor, FBG anchor sensor and FBG anti-slide piling sensor have been designed. These sensors are installed in the slope models, while centrifugal acceleration tests under 100 g are carried out.

FBG sensors obtain three types of deformation information, demonstrating the feasibility and validity of this measurement strategy.

The experimental results provide important details about instability mechanisms of a slope, which has great significance in research on slope model monitoring techniques and slope stability.

Analysis of stability of slopes has been the subject of many research works in the past decades. Prediction of stability of slopes is of great importance in many civil engineering structures including earth dams, retaining walls and trenches. There are several parameters that contribute to the stability of slopes. This paper aims to present a new approach, based on evolutionary polynomial regression (EPR), for analysis of stability of soil and rock slopes.

EPR is a data‐driven method based on evolutionary computing, aimed to search for polynomial structures representing a system. In this technique, a combination of the genetic algorithm and the least square method is used to find feasible structures and the appropriate constants for those structures.

EPR models are developed and validated using results from sets of field data on the stability status of soil and rock slopes. The developed models are used to predict the factor of safety of slopes against failure for conditions not used in the model building process. The results show that the proposed approach is very effective and robust in modelling the behaviour of slopes and provides a unified approach to analysis of slope stability problems. It is also shown that the models can predict various aspects of behaviour of slopes correctly.

In this paper a new evolutionary data mining approach is presented for the analysis of stability of soil and rock slopes. The new approach overcomes the shortcomings of the traditional and artificial neural network‐based methods presented in the literature for the analysis of slopes. EPR provides a viable tool to find a structured representation of the system, which allows the user to gain additional information on how the system performs.

Over the last decade, latent growth modeling (LGM) utilizing hierarchical linear models or structural equation models has become a widely applied approach in the analysis of change. By analyzing two or more variables simultaneously, the current method provides a straightforward generalization of this idea. From a theory of change perspective, this chapter demonstrates ways to prescreen the covariance matrix in repeated measurement, which allows for the identification of major trends in the data prior to running the multivariate LGM. A three-step approach is suggested and explained using an empirical study published in the Journal of Applied Psychology.

This paper aims to develop an efficient algorithm combining straightforward response surface functions with Monte Carlo simulation to conduct seismic reliability analysis in a systematical way.

The representative slip surfaces are identified and based on to calibrate multiple response surface functions with acceptable accuracy. The calibrated response surfaces are used to determine the yield acceleration in Newmark sliding displacement analysis. Then, the displacement-based limit state function is adopted to conduct seismic reliability analysis.

The calibrated response surface functions have fairly good accuracy in predicting the yield acceleration in Newmark sliding displacement analysis. The seismic reliability is influenced by such factors as PGA, spatial variability and threshold value. The proposed methodology serves as an effective tool for geotechnical practitioners.

The multiple sources of a seismic slope response can be effectively determined using the multiple response surface functions, which are easily implemented within geotechnical engineering.

To solve the instability problem of Zhangjiayao landslide caused by rainfall, the internal mechanism of slope instability and the supporting effect of anti-slide piles are studied. The research results can provide theoretical basis for the prevention and control of loess landslides.

A three-dimensional finite element model of Zhangjiayao landslide is established by field geological survey, laboratory test and numerical simulation.

The results show that Zhangjiayao landslide is a loess-mudstone contact surface landslide, and rainfall leads to slope instability and traction landslide. The greater the rainfall intensity, the faster the pore water pressure of the slope increases and the faster the matrix suction decreases. The longer the rainfall duration, the greater the pore water pressure of the slope and the smaller the matrix suction. Anti-slide pile treatment can significantly improve slope stability. The slope safety factor increases with the increase of embedded depth of anti-slide pile and decreases with the increase of pile spacing.

Based on the unsaturated soil seepage theory and finite element strength reduction method, the failure mechanism of Zhangjiayao landslide was revealed, and the anti-slide pile structure was optimized and designed based on the pile-soil interaction principle. The research results can provide theoretical basis for the treatment of loess landslides.

1. A three-dimensional finite element model of Zhangjiayao landslide is established.

2. Zhangjiayao landslide is a loess-mudstone contact surface landslide.

3. The toe of Zhangjiayao slope is first damaged by heavy rainfall, resulting in traction landslide.

4. The deformation of Zhangjiayao slope is highly dependent on rainfall intensity and duration.

5. The anti-slide pile can effectively control the continuous sliding of Zhangjiayao slope.

A three-dimensional finite element model of Zhangjiayao landslide is established.

Zhangjiayao landslide is a loess-mudstone contact surface landslide.

The toe of Zhangjiayao slope is first damaged by heavy rainfall, resulting in traction landslide.

The deformation of Zhangjiayao slope is highly dependent on rainfall intensity and duration.

The anti-slide pile can effectively control the continuous sliding of Zhangjiayao slope.

Cemented conglomerate accumulation is a weak and heterogeneous medium that occurs in western China. It consists mainly of argillaceous cement that loses strength rapidly upon contact with water, leading to collapse instability failure. Its deformation failure mechanism is complex and poorly understood. In this paper, the erosion failure mechanism of cemented conglomerate accumulation is investigated.

The collapse failure process after erosion of the slope foot for typical cemented conglomerate accumulation is studied based on field investigation using the particle discrete element method. And how the medium composition, slope angle and cementation degree influence the failure mode and process of the cemented conglomerate accumulation is examined.

The foot erosion of slope induces a tensile failure that typically manifests as “erosion at the foot of slope – tensile cracking at the back edge of slope top – integral collapse.” The collapse failure is more likely to occur when the cemented conglomerate accumulation has a higher rock content, a steeper slope angle or a weaker cementation degree.

A model based on rigid blocks and disk particles to simulate the cemented conglomerate accumulation is developed. It shows that the hydraulic erosion at the foot of the slope resulted in a different failure mechanism than that of general slopes. The results can inform the stability management, disaster prevention and mitigation of similar slopes.

This paper aims to develop an effective framework which combines Bayesian optimized convolutional neural networks (BOCNN) with Monte Carlo simulation for slope reliability analysis.

The Bayesian optimization technique is firstly used to find the optimal structure of CNN based on the empirical CNN model established in a trial and error manner. The proposed methodology is illustrated through a two-layered soil slope and a cohesive slope with spatially variable soils at different scales of fluctuation.

The size of training data suite, T, has a significant influence on the performance of trained CNN. In general, a trained CNN with larger T tends to have higher coefficient of determination (R²) and smaller root mean square error (RMSE). The artificial neural networks (ANN) and response surface method (RSM) can provide comparable results to CNN models for the slope reliability where only two random variables are involved whereas a significant discrepancy between the slope failure probability (P_f) by RSM and that predicted by CNN has been observed for slope with spatially variable soils. The RSM cannot fully capture the complicated relationship between the factor of safety (FS) and spatially variable soils in an effective and efficient manner. The trained CNN at a smaller the scale of fluctuation (λ) exhibits a fairly good performance in predicting the P_f for spatially variable soils at higher λ with a maximum percentage error not more than 10%. The BOCNN has a larger R² and a smaller RMSE than empirical CNN and it can provide results fairly equivalent to a direct Monte Carlo Simulation and therefore serves a promising tool for slope reliability analysis within spatially variable soils.

A geotechnical engineer could use the proposed method to perform slope reliability analysis.

Slope reliability can be efficiently and accurately analyzed by the proposed framework.

The purpose of this paper is to attempt to generate a better, systematic and scientific understanding of the basic reasons behind slope instability to help in developing the basic principles of landslide hazard zonation, monitoring and forecasting of landslide hazards for better and more effective landslide hazard mitigation and management.

The study is based on extensive field observations and intensive reviews of literature from secondary sources.

Mass movements especially landslides as they are known to common man are a recurring natural phenomenon and are an integral part of any geological/geomorphological circle of landform development through sequential development of slopes in any elevated region and especially in young fold mountain chains.

The paper presents a valuable insight into the basic reasons behind a landslide to spread awareness, to educate and sensitize people towards better and effective landslide hazard mitigation and thereby ensure people's participation in disaster management. It also aims to initiate and encourage research in the field of landslide management.

Landslides occur frequently and without any appreciable warning as such causing havoc and often insurmountable damage to life and property but despite their uncertainty, their causative factors and indicators of slope instability are very well known to an extent that the magnitude of these events, susceptible areas, the timing of such events and their potential impact can be studied, analyzed and evaluated on the basis of past occurrences and existing knowledge to mitigate their impact. The real value of the present study is to minimize losses due to landslides through better knowledge and enhanced levels of understanding of the phenomenon and its management by simply avoiding those particular reasons that could lead to slope instability problems.

Mass movements, especially landslides, are a recurring natural phenomenon and are an integral part of any geological/geomorphological cycle of landform development through sequential development of slopes in any elevated region and especially in young fold mountain chains. The purpose of this paper is to develop and evolve cheap, affordable, environment friendly and ecologically sustainable techniques of landslide disaster management and prevention.

The study is based on extensive research and field observations of various landslide management projects over the past decade and includes an intensive review of literature from secondary sources.

Landslide management aims to facilitate, and as far as possible accelerate the ongoing process of development on a sustainable basis, by preventing (reducing) the loss of lives and property by applying modern science and technology and taking appropriate measures and safety precautions at the right place at the right time. Landslide management, even in the most developed countries, has suffered from lack of adequate financial resources. Bioengineering offers an environment friendly and highly cost and time effective solution to the slope instability problems in mountainous and hilly areas.

The paper aims to initiate and encourage research in the field of landslide management with the viewpoint that green technology is a clean and affordable technology (both financially and ecologically).

The paper shows that bioengineering is highly cost effective and has very high cost‐benefit ratio. Bioengineering techniques when used in combination with civil and social engineering measures reduce the overall cost of landslide mitigation considerably which is the key factor for developing nations. Bioengineering has a very high success rate and is much more sustainable, eco‐friendly and affordable than other available options.

The purpose of this study is to investigate the deformation characteristics and failure modes of the right bank slope of Xiluodu Hydropower Station after excavation.

Micro-seismic monitoring technology is applied to obtain the microfracture information and study the internal damage evolution law of the slope rock mass. A numerical model for discontinuous deformation analysis (DDA) is established to analyse the deformation characteristics and failure mode of the slope. Micro-seismic monitoring and DDA can verify and supplement each other's results in the investigation of slope failure.

The results show that the slope has a downhill displacement along the weathered zone under natural conditions; the maximum resultant displacement at the monitoring point is 380 mm. The micro-seismic events are concentrated in an area located 30–100 m horizontally away from the slope surface and at an elevation of 390–470 m. The distribution of these micro-seismic events is consistent with the location of the unloading and weathered zones; it is the same as the DDA simulation result.

The study is anticipated to be used as reference for the stability analysis of rock slopes. By combining the continuous (micro-seismic monitoring technology) and discontinuous (DDA) methods, the entire process starting from the gradual accumulation of internal rock micro-damage to the macroscopic discontinuous deformation and failure of the slope can be investigated.