Abstract. Nowadays, a wide range of site planning, field investigation and slope analysis need to be carried out for slope protection and landslide-related disaster reduction. To enhance the efficiency of topography modeling, unmanned aerial vehicle (UAV) has become a new surveying technique to obtain spatial information. This study aims to determine the topography of a slope by using a digital camera mounted on UAV to photograph with a high degree of overlap. The 3D point clouds data were generated through image feature point extraction integrated with accurate GPS ground control points. It is found in this study that the obtained Digital Surface Model (DSM) data, compared with the traditional field surveying techniques, has much superior performance. The resolution of the DSM has reached 1.58 cm. Also, the error of elevation and distance between DSM and actual 3D coordinates obtained by traditional total station survey is acceptance. It is clear that such a UAV surveying technique can replace conventional surveying methods and provide complete and accurate 3D topography information in automatic and highly efficient manner for most geotechnical applications.

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The generalized plasticity theory has evolved in the last decades and attracts the attention of different research groups, because of characteristics like the absence of an explicit flow surface formulation. This paper presents a detailed inspection of two sophisticated constitutive models for granular soils under monotonic loading: the Pastor‐Zienkiewicz‐Chan (P‐Z‐C) model[1] and the Manzanal‐Merodo‐Pastor (M‐M‐P) model.[2] Even though they are similar in mathematical framework, the P‐Z‐C model requires only eight parameters compared to the M‐M‐P model which requires 18 parameters to describe the material behavior under monotonic loading. Parameters of both models were calibrated based on the extensive experimental database available for monotonic triaxial tests performed on Karlsruhe fine sand by Wichtmann et al.[3] An objective discussion addressing the strengths and weaknesses of each model is presented. Finally, a procedure to identify the most relevant parameters that control different elements in the model like the stiffness, the evolution of dilatancy or the hardening variables is introduced, using the Monte Carlo Toolbox (MCAT) for simulations. Some interesting inferences could be obtained, like the conclusion that the MCAT is a helpful tool for identifying material parameters and their interaction, but it cannot replace the human factor, the experience and objective judgement of the modeller for the calibration of constitutive models.

In rock engineering, evaluating the post-peak strength and deformation of rock is necessary. To explore the elasto-plastic behavior of sandstone in the post-peak stage, a series of strain-controlled triaxial tests were conducted under different confining pressures. According to the post-peak characteristics, a constitutive model based on nonlinear elasticity and generalized plasticity is proposed. This proposed model is characterized by the following features: (1) Nonlinear elasticity is observed under hydrostatic and shear loading; (2) the associated flow rule is followed; (3) substantial plastic deformation occurs during shear loading; and (4) post-peak softening behavior is accurately predicted. This model requires twelve material parameters, three for elasticity and nine for plasticity. The proposed model was validated by comparing the triaxial test results of Mushan sandstone at different hydrostatic pressures under dry and saturated conditions. In addition, the model is versatile; it can simulate the deformational behavior of two other sandstones. In summary, the proposed model can reasonably predict the complete stress–strain curve of sandstone.

The material point method (MPM) is an extended finite element method that can be used to simulate large deformation scenarios. A massive translational landslide in Taiwan was adopted to validate the numerical technique as thorough investigations, including the digital terrain models (DTMs), laboratory experiments, and numerical analyses, were available in a forensic report. The MPM code Anura3D was used to mimic the landslide’s kinematics, post-failure, and run-off process. An unstable sandstone/shale interlayer was found to lead the slope sliding; therefore, the before-and-after DTMs from the report mentioned above were used to examine the run-off distance and deposition to determine the best fit of reduced material properties for this layer. The sliding paths, displacements, velocities of the sliding can be evaluated by dividing the material points into several groups to differentiate the kinematic among them. Meanwhile, the simulations were compared with different numerical methods. The landslide duration and possible maximum safety distance were also assessed. This study has demonstrated that the MPM can analyze the large deformation, post-failure, and run-off distance of landslides. The critical timing of a slope failure is possible to be an essential index on national spatial planning for future disaster reduction.