Estimation of the Critical Seismic Acceleration for Three-Dimensional Rock Slopes

An analytical approach for the estimating of critical seismic acceleration of rock slopes was proposed in this study. Based on the 3D horn failure model, the critical seismic acceleration coefficient of rock slopes was conducted with the modified Hoek–Brown (MHB) failure criterion in the framework of upper-bound theory for the first time. The nonlinear Hoek–Brown failure criterion is incorporated into the three-dimensional rotational failure mechanism, and a generalized tangent technique is introduced and employed to convert the nonlinear Hoek–Brown failure criterion into a linear criterion. The critical seismic acceleration coefficients obtained from this study were validated by the numerical simulation results based on finite element limit analysis. The agreement showed that the proposed method is effective. Finally, design charts were provided for exceptional cases for practical use in rock engineering.

Proof of Concept with Distributed Temperature Sensing for Crack Detection on Dikes

<p>Cracks occurring on dike surfaces due to droughts, are a big threat for the safety of flood defence infrastructure as they increase infiltration rates and reduce the resistance to mass rotational failure (slope stability). Hence, an effective and sustainable monitoring system for crack detection is of paramount importance given the increase in frequency of drought events. Conventional methods heavily rely on visual inspections by expert observers, drone technologies survey, or destructive techniques such as sampling and trenching. Most of them result sparse qualitative and labor-intensive assessments. In this project, we aim to develop a method which combines two different sensing techniques —distributed temperature sensing (DTS) and conventional video cameras— for detecting the cracks on the dike surface. In contrast to earlier studies using DTS to measure the temperature changes during high water levels in the riverside slope and to detect seepage changes, we will be measuring the superficial moisture content on the riverside and the landside slopes of the dike, and use it as a proxy for crack detection in combination with the camera images and deep learning techniques. It is expected that by including the DTS measurements, the detection of cracks may outperform the actual methods in an economically and more densely manner along several kilometers of dikes in real time.</p>

3D Limit Analysis of the Transient Stability of Slope during Pile Driving in Nonhomogeneous and Anisotropic Soil

To evaluate the stability of a slope subjected to pile driving in nonhomogeneous and anisotropic soils, an upper-bound limit analysis method is employed in this paper. A 3D rotational failure mechanism for soil slope is extended to account for different failure patterns (i.e., toe failure and base failure). In order to avoid missing the global minimum, an efficient optimization method is simultaneously employed to find the least upper bound to the factor of safety (FS). The effectiveness and accuracy of the proposed method is well demonstrated by comparing the results obtained from the proposed approach with the solutions from published literatures. The effects of key designing parameters are presented and discussed. The optimal pile location and the three-dimensional effect of the slope are discussed. In addition, these results highlight that the adverse effects of pile driving on slope stability should be highly concerned during the design of geotechnical infrastructures, rather than emphasizing the reinforcement effect of a pile only.

Stability Analysis of a Slurry Trench in Cohesive-Frictional Soils

The slurry trench has become increasingly common in underground engineering and the stability of a slurry trench has been an important design issue. Although many studies have focused on the overall stability of a slurry trench, few of that are related to its local stability. Based on the limit analysis, both two dimensional and three dimensional rotational failure mechanisms for the local failure of a slurry trench in a sandwiched weak layer are proposed, and the upper solutions of 2D and 3D safety factors for local failure mechanisms are derived to evaluate the stability of a slurry trench. Moreover, a numerical analysis combined with the strength reduction technique is performed to investigate the local stability and the local failure process of a slurry trench. The proposed analytical method is verified through the comparison with the results of FLAC3D. Finally, a parametric study on the influences of geometric and geologic parameters on the local stability of the slurry trench are investigated. The results show that the investigation on the local stability of a slurry trench is effective and reasonable, which can provide a reference for the engineers in the practical engineering.

Machine-learning identification of asteroid groups

ABSTRACT Asteroid families are groups of asteroids that share a common origin. They can be the outcome of a collision or be the result of the rotational failure of a parent body or its satellites. Collisional asteroid families have been identified for several decades using hierarchical clustering methods (HCMs) in proper elements domains. In this method, the distance of an asteroid from a reference body is computed, and, if it is less than a critical value, the asteroid is added to the family list. The process is then repeated with the new object as a reference, until no new family members are found. Recently, new machine-learning clustering algorithms have been introduced for the purpose of cluster classification. Here, we apply supervised-learning hierarchical clustering algorithms for the purpose of asteroid families identification. The accuracy, precision, and recall values of results obtained with the new method, when compared with classical HCM, show that this approach is able to found family members with an accuracy above 89.5 per cent, and that all asteroid previously identified as family members by traditional methods are consistently retrieved. Values of the areas under the curve coefficients below Receiver Operating Characteristic curves are also optimal, with values consistently above 85 per cent. Overall, we identify 6 new families and 13 new clumps in regions where the method can be applied that appear to be consistent and homogeneous in terms of physical and taxonomic properties. Machine-learning clustering algorithms can, therefore, be very efficient and fast tools for the problem of asteroid family identification.