Search

During tunnel construction, a substantial volume of data is generated. However, presently, there is a challenge in effectively integrating those data to conduct a precise risk assessment of water inrush. This study develops a novel multisource information fusion method that merges a probabilistic support vector machine, cloud model, evidential reasoning (ER) rule, and Monte Carlo (MC) simulation method to support water-inrush risk assessment under uncertainty. Different models train a variety of information sources to analyze the water-inrush risk value. The evaluation of each model's judgment is based on its performance, which is determined by its reliability and the significance of its weights. Finally, these multiple assessment results are fused at the decision level to achieve an overall water-inrush risk evaluation using the ER rule. The MC simulation method was used to model the uncertainty and randomness underlying the limited number of observations. The Heshan tunnel case in China is used to demonstrate the feasibility and effectiveness of the developed method. The outcomes suggest that the multisource information fusion technique proposed is capable of (1) demonstrating a good ability to handle high conflict information; (2) exhibiting an outstanding assessment performance (90% accuracy) compared to that of single-source assessment models (lower than 70% accuracy); and (3) performing strongly with bias, as it can achieve acceptable assessment accuracy under 5% bias. Therefore, the newly proposed method for fusing multiple sources of information can serve as a practical reference for water-inrush risk assessment and management. [ABSTRACT FROM AUTHOR]

AbstractTensile stresses may lead to cracks forming at the crest of coastal slopes and subsequent slope failure, particularly under seismic load conditions. Traditional shear strength failure criteria often overestimate the tensile strength of geomaterials, and in turn the factor of safety against sliding. This paper presents an improved nonlinear analysis method for assessing the stability of slopes, while considering tension cut-off in the failure criterion as well as the detrimental effects of inertial seismic loading and pore water pressure. The method employs the principle of energy consumption to obtain solutions for the geometry of the potential sliding surface and stress distribution, while the critical slope height and the stability factor are determined by means of a particle swarm optimization algorithm. Comparison with existing methods is conducted to validate the effectiveness and accuracy of this method. Results showed that the tensile strength of geomaterials had a significant impact on the stability of the slope and its associated failure mechanism, particularly for the vertical slope. This study could avoid the assumptions of the dilatancy angle on the velocity discontinuity and critical slope sliding surface, and reflect the tensile and nonlinear characteristics of the geomaterials well. [ABSTRACT FROM AUTHOR]

Landslides are frequent and devastating geological hazards that cause significant economic and human losses annually. The selection of appropriate shear strength parameters is crucial for evaluating and preventing landslide failure. Considering the nonlinear characteristics of rock-mass material, a rock slope stability analysis model was built using the nonlinear Hoek‒Brown failure criterion. A Geological Strength Index–material constant (GSI–mi) curve, based on a deterministic method, was proposed to back analyzed the Geological Strength Index (GSI), which is consistent with a trial-and-error method, but simpler to implement. The back analysis can be extended to other parameters in addition to the GSI. Furthermore, considering the randomness and uncertainty, a reliability-based back analysis method for nonlinear strength parameters of the sliding surface was proposed. The optimal parameter combination that corresponded to the minimum reliability index was determined, which could serve as reasonable values of the nonlinear strength parameters for landslides. A comparison of different failure criteria also suggested that the stress level at the sliding surface should be accounted for in landslides using the significant nonlinear characteristics of strength parameters. [ABSTRACT FROM AUTHOR]

Shear dilation occurs during the failure of geomaterials subjected to shear stress. To account for the dilatancy and nonlinearity of geomaterials, a nonlinear upper-bound analysis method was proposed for evaluating the stability of homogeneous slopes based on the coaxial nonassociated flow rule. The rotational failure mechanism of a homogeneous slope was established within the kinematic approach of limit analysis, using the Davis approach to convert the nonassociated flow rule into an associated one. By applying the variation principle, ordinary differential equations of the potential sliding surface and its corresponding stress were derived, which were then solved using a fourth-order Runge–Kutta method in conjunction with appropriate boundary conditions. Furthermore, the balance equation was derived from the virtual power principle, and the critical height of the slope was calculated using a particle swarm optimization algorithm. The strength reduction technique was then introduced to determine the factor of safety of the slope. The accuracy and effectiveness of the proposed nonlinear upper-bound variation method for evaluating the stability of homogeneous slopes under nonassociated flow rule and nonlinear failure criteria were verified when compared with existing studies and techniques, such as the finite-element limit analysis and the finite difference method. This study accurately reflects the nonlinearity and dilatancy of geomaterials and avoids assumptions regarding the sliding surface and its corresponding stress, making it a valuable reference for future research. [ABSTRACT FROM AUTHOR]