Wedge failure analysis of anchored rock slopes subjected to surcharge and seismic loads

Slope stability in mining and civil engineering projects is always a problem of great concern. Because the rock mass behavior is significantly governed by the presence of joints or other discontinuities, several types of slope failure, such as plane failure, wedge failure, toppling failure, buckling failure and circular failure, are often observed. The present work focuses on the study of the wedge failure, which occurs as sliding of a mass of rock on two intersecting planes, generally discontinuity planes. Recently, the factor of safety of rock slopes against the wedge failure has been studied in a number of investigations under static and/or dynamic conditions by different methods such as the limit equilibrium method, numerical modeling method, reliability method and stereographic method. However, the anchored rock slope against the wedge failure subjected to surcharge and seismic load has not yet been studied in detail in earlier studies. In this thesis, the rock slope subjected to the generalized loads such as surcharge and seismic/dynamic loads is analyzed against the wedge failure by the limit equilibrium method. The expression for the factor of safety was derived for the cases with anchors and without anchors separately. In addition, a parametric study is carried out to demonstrate the effects of the most relevant governing parameters on the stability of rock slope. The parameters include geometrical parameters, joint material properties, unit weight of rock, anchor inclination and hydraulic parameters. Several special cases of the developed generalized expression result in the expressions for the factor of safety for simplified field situations as reported in the literature. The parametric study shows that most parameters as mentioned above affect the factor of safety ( FS ) of the rock slope against the wedge failure significantly. In order to find an easy way to work on the parametric analysis, the “ * ” indicates dimensionless parameters. It is observed that the surcharge would always be a destabilizing force when the cohesion (c* ) is not zero; the FS decreases with an increase in surcharge. However, when c* = 0, the FS increases slightly with an increase in surcharge. The anchor forces (T* ) would always be a stabilizing force that makes the FS increase with an increase in T*. As the angle of inclination of the joint plane/failure plane to the horizontal ( p y ) increases, the FS increases nonlinearly; it increase sharply by 60% from 42° to 45° while it deceases nonlinearly by 67% with an increase in the slope angle (yf ) from 40° to 60°. It is also observed that the FS decreases with an increase in horizontal seismic acceleration coefficient (k h ) and the vertical seismic acceleration coefficient (k v ), separately, while it increases linearly with an increase in the following parameters: the cohesion (c* ) and the angle of shearing resistance ( f ), separately. The FS increases with an increase in inclination of stabilizing force to the normal at the failure plane (a ); it becomes maximum when a increases to 80°. However, the unit weight of rock (g* ) does not affect the FS significantly

Design of Electronic Voltage Transformer Error Pattern Recognition and Classification Algorithm Based on Data Mining

With the development of smart grids, electronic voltage transformer (EVT) has gradually entered the stage of large-scale applications. Accurately identifying errors in electronic voltage transformers is crucial for the stability of power systems. Strengthening the measurement accuracy of EVT is of great significance for the operation of power systems and measurement and protection devices. However, due to the limitations of traditional verification methods, there are still challenges. To better improve the accuracy of transformer identification, a data-driven method for enhancing transformer error evaluation and prediction was developed. Based on the low accuracy of traditional EVT error verification and the difficulty of monitoring, data mining technology is proposed for EVT error analysis and evaluation. Recursive principal component analysis is used to separate errors from EVT measurement data, and feature statistics are used to monitor its operating status. Then, regression analysis under support vector machines is added to predict errors for active error correction and better evaluation of its status. The evaluation of the transformer monitoring dataset shows that the classification accuracy of error detection of the proposed method exceeds 93%, and the deviation between the predicted error value and the actual error value is less than 0.05%. Compared with methods such as artificial neural networks and ARMA, the average error rate has been reduced by more than 18%. The accuracy and average accuracy of the algorithm proposed in the study exceeded 80%, with values of 96.23% and 85.12%, respectively. The average error of the ratio difference feature of the EVT is only 0.023, and the average error of the angle difference is less than 0.01, which is much smaller than the algorithm used for comparison. The application response time is less than 0.1 s and the evaluation threshold can better identify data anomalies, with high application accuracy. This method can effectively provide real-time evaluation tools for the operational status of electronic voltage transformers and more accurately and proactively identify transformer errors from conventional data. This study provides an important data-driven solution for improving power grid reliability

An optical fiber tip micrograting thermometer

An ~12 µm long Bragg grating was engraved in an ~5 µm diameter optical fiber tip by focused ion beam (FIB) milling. An ~10-dB extinction was achieved at 1570 nm with only 11 indentations. The grating was used for temperature sensing, and it exhibited a temperature sensitivity of ~22 pm/°C

Two-Dimensional Inversion Asymmetric Topological Insulators in Functionalized III-Bi Bilayers

The search for inversion asymmetric topological insulators (IATIs) persists as an effect for realizing new topological phenomena. However, so for only a few IATIs have been discovered and there is no IATI exhibiting a large band gap exceeding 0.6 eV. Using first-principles calculations, we predict a series of new IATIs in saturated Group III-Bi bilayers. We show that all these IATIs preserve extraordinary large bulk band gaps which are well above room-temperature, allowing for viable applications in room-temperature spintronic devices. More importantly, most of these systems display large bulk band gaps that far exceed 0.6 eV and, part of them even are up to ~1 eV, which are larger than any IATIs ever reported. The nontrivial topological situation in these systems is confirmed by the identified band inversion of the band structures and an explicit demonstration of the topological edge states. Interestingly, the nontrivial band order characteristics are intrinsic to most of these materials and are not subject to spin-orbit coupling. Owning to their asymmetric structures, remarkable Rashba spin splitting is produced in both the valence and conduction bands of these systems. These predictions strongly revive these new systems as excellent candidates for IATI-based novel applications.Comment: 17 pages,5figure

Proximity Enhanced Quantum Spin Hall State in Graphene

Graphene is the first model system of two-dimensional topological insulator (TI), also known as quantum spin Hall (QSH) insulator. The QSH effect in graphene, however, has eluded direct experimental detection because of its extremely small energy gap due to the weak spin-orbit coupling. Here we predict by ab initio calculations a giant (three orders of magnitude) proximity induced enhancement of the TI energy gap in the graphene layer that is sandwiched between thin slabs of Sb2Te3 (or MoTe2). This gap (1.5 meV) is accessible by existing experimental techniques, and it can be further enhanced by tuning the interlayer distance via compression. We reveal by a tight-binding study that the QSH state in graphene is driven by the Kane-Mele interaction in competition with Kekul\'e deformation and symmetry breaking. The present work identifies a new family of graphene-based TIs with an observable and controllable bulk energy gap in the graphene layer, thus opening a new avenue for direct verification and exploration of the long-sought QSH effect in graphene.Comment: 4 figures in Carbon, 201