scholarly journals Safety Evaluation of Underground Caverns Based on Monte Carlo Method

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Qifeng Guo ◽  
Zhihong Dong ◽  
Meifeng Cai ◽  
Fenhua Ren ◽  
Jiliang Pan

In order to study the influence of joint fissures and rock parameters with random characteristics on the safety of underground caverns, several parameters affecting the stability of surrounding rock of underground caverns are selected. According to the Monte Carlo method, random numbers satisfying normal distribution characteristics are established. A three-dimensional model of underground caverns with random characteristics is established by discontinuous analysis software 3DEC and excavation simulations are carried out. The maximum displacement at the numerical monitoring points of arch and floor is the safety evaluation index of the cavern. The probability distribution and cumulative distribution function of the displacement at the top arch and floor are obtained, and the safety of a project is evaluated.

2011 ◽  
Vol 250-253 ◽  
pp. 3934-3940
Author(s):  
Yi Fang Feng ◽  
Hua Zhi Zhang ◽  
Yu Wang ◽  
Qing Jun Zuo

Based on the Yuwangbian high loess slope, which is located in Xi'an Yanta District, the basic principle of Monte-Carlo method is presented. By means of geotechnical engineering and geotechnical environment emulation software Geostudio-slope/w and based on Morgenstern-Price slope stability analysis method, the reliability and stability of the slope are analyzed under different kinds of working condition. The stability factor, reliability index and failure probability under the corresponding working conditions has been obtained. The results coincide with the actual condition, which makes the Geostudio software combine with the Monte-Carlo method and provides reference for the reliability analysis of loess slope.


Author(s):  
M. V. Fomin ◽  
I. M. Fomina

An algorithm for modeling and an example of calculating gas release flows from the surfaces of the flow part of a turbomolecular pump by the Monte Carlo method in a three-dimensional setting low-density gas flow is considered.


Author(s):  
Sandip Mazumder

The Binary Spatial Partitioning (BSP) algorithm has found prolific usage within the computer graphics community for efficient tracing of rays. In this paper, the BSP algorithm is described and demonstrated in the context of the Monte Carlo method for surface-to-surface radiation transport. In the BSP algorithm the computational domain is recursively bisected into a set of hierarchically linked boxes that are then made use of to narrow down the number of ray-surface intersection calculations. The geometric information pertaining to these hierarchically linked boxes is stored in the form of a binary tree or table. The algorithm is tested for two classical problems, namely an open box, and a box in a box, in both two-dimensional (2D) and three-dimensional (3D) geometries with various mesh sizes, and is found to result in orders of magnitude gains in computational efficiency over direct calculations that do not employ any acceleration strategy. In theory, the BSP algorithm is expected to scale logarithmically, i.e., the CPU time is expected to increase logarithmically with increase in the number of discrete surface elements (or faces) that the boundaries of the computational domain are broken into. In practice, however, it was found that balancing of the binary tree is critical for logarithmic scaling of the algorithm. Without balancing of the binary tree, only super-linear scaling can be attained.


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