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Rock Mechanics and Rock Engineering

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16.02.2016 | Original Paper

A New Methodology for Open Pit Slope Design in Karst-Prone Ground Conditions Based on Integrated Stochastic-Limit Equilibrium Analysis

verfasst von: Ke Zhang, Ping Cao, Guowei Ma, Wenchen Fan, Jingjing Meng, Kaihui Li

Erschienen in: Rock Mechanics and Rock Engineering | Ausgabe 7/2016

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Abstract

Using the Chengmenshan Copper Mine as a case study, a new methodology for open pit slope design in karst-prone ground conditions is presented based on integrated stochastic-limit equilibrium analysis. The numerical modeling and optimization design procedure contain a collection of drill core data, karst cave stochastic model generation, SLIDE simulation and bisection method optimization. Borehole investigations are performed, and the statistical result shows that the length of the karst cave fits a negative exponential distribution model, but the length of carbonatite does not exactly follow any standard distribution. The inverse transform method and acceptance–rejection method are used to reproduce the length of the karst cave and carbonatite, respectively. A code for karst cave stochastic model generation, named KCSMG, is developed. The stability of the rock slope with the karst cave stochastic model is analyzed by combining the KCSMG code and the SLIDE program. This approach is then applied to study the effect of the karst cave on the stability of the open pit slope, and a procedure to optimize the open pit slope angle is presented.

Vorheriger Artikel Behavior of Fiber Glass Bolts, Rock Bolts and Cable Bolts in Shear

Nächster Artikel Ground Response to Tunnel Re-profiling Under Heavily Squeezing Conditions

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Titel: A New Methodology for Open Pit Slope Design in Karst-Prone Ground Conditions Based on Integrated Stochastic-Limit Equilibrium Analysis
verfasst von: Ke Zhang
Ping Cao
Guowei Ma
Wenchen Fan
Jingjing Meng
Kaihui Li
Publikationsdatum: 16.02.2016
Verlag: Springer Vienna
Erschienen in: Rock Mechanics and Rock Engineering / Ausgabe 7/2016
Print ISSN: 0723-2632
Elektronische ISSN: 1434-453X
DOI: https://doi.org/10.1007/s00603-016-0924-1

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