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The Monte Carlo simulation (MCS) is generally accepted as an accurate approximation method in slope reliability analysis. However, low efficiency hinders its use. Based on the online sequential extreme learning machine (OS-ELM), the OS-ELM-MCS method is proposed, which overcomes the requirement of calculating the safety factor, respectively, when using a conventional MCS for reliability analysis. Combined with the multi-initial points sequential quadratic programming (MSQP) algorithm, a search method for probabilistic critical slip surfaces with arbitrary shapes is introduced. It is possible to conduct both a reliability analysis and deterministic analysis under the same algorithm framework. Based on the proposed method, reliability and deterministic analyses of two cases are carried out. Compared with the results of other methods, the accuracy of the reliability and deterministic analysis method is verified. This verifies that the accuracy and time performance of the proposed method are better than those of conventional algorithms. The results of these case studies reveal the differences between the conclusions of the reliability and deterministic analyses. Therefore, it is necessary to combine reliability analysis and deterministic analysis to improve the credibility of stability analysis results.

In this work, we make a first attempt at performing a molecular dynamic simulation to gain insights into the transport characteristics of H2O molecules confined in sandwiched albite-quartz system, where a mechanical loading couples a thermal cycling was carried out·H2O molecules were placed within the vacuum gap of the albite-quartz slab to accomplish the sandwich model. Based on the viewpoint of energetics aspect, the coulombic interactions are the dominant contributors to the total potential energy. The diffusion coefficient, orientation parameter and hydrogen bonding were examined for analysis of the transport characteristics of confined H2O molecules. Not only the water–mineral interaction but also the substrate structure reflects the dynamics of confined H2O molecules, as evident by qualitatively analyzing the trajectories of some selected H2O molecules located in different regions. The cyclic thermal–mechanical (T-M) coupling contribute a wide band distribution after 1000th cycles instead of two distinct peaks after the 100th cycles. The decrease in amplitude occurring primarily around 1.7 A is indicative of a weaken H-Bond and a greater rotational freedom of those molecules, leading to the gathering of H2O molecules near quartz and albite slabs and a dense arrangement of the H2O molecules in the inter-spacing region, which could be ascribed to the interconnected aspect of diffusion process.

Ground Penetrating Radar (GPR) is a feasible remote sensing tool for surveying subsurface geo-structure. These structure characteristics are recorded in radar signal profiles by means of echo signal detection, amplitude and phase estimation. Besides the energy attenuation and absorption of GPR electromagnetic (EM) pulse during its propagating into subsurface from a transmitting antenna, the strong interferences such as multiples, background scatters, clutters and random noise often make the weak signal of structure signatures hardly distinguishable from them. This paper focuses on detecting rock fractures with multiple signal classification (MUSIC) under complex environment. By surveying data at experimental site it is shown that this method can efficiently achieve sparse representation of subsurface structures and yields discriminative fracture signature for geological interpretation.