Development of Bishop and Diagram Methods in order to Slope Stability Analysis Considering the Intermediate Principal Stress

Document Type : Research Article

Authors

1 Dept. of Mining, Shahid Bahonar University of Kerman, Iran

2 Dept. of Mining, Vali-e-Asr University of Rafsanjan, Iran

Abstract

Summary
The recent studies have shown the importance of the role of intermediate principal stress in design process of geomechanics projects. Therefore in this paper, considering the triaxial unified strength failure criterion, the Bishop method was developed. Moreover, based on the numerical modeling results, two diagrams for slope stability analysis were presented.
 
Introduction
In large-scale open pit mines, one of the major issues during design is maximizing the net present value of the mine. One of the most important factors in this regard is the optimum slope angle of the mine. Generally, in rock slope stability analyses, the considered failure criteria are biaxial, thus in analysis process, only the maximum and minimum principal stresses of medium are considered. Actually, in most cases, the effect of intermediate principal stress is ignored completely, while recent researches have shown that the design and calculation of safety factor, regardless of the intermediate principal stress effect, is conservative and can have a significant effect on the economic conditions of the project. One of the triaxial failure criteria is the unified strength failure criterion. It consists of a wide range of solutions based on different failure criteria such as the Mohr-Coulomb failure criterion and Generalized Twin Shear Stress yield. In reality, based on this failure criterion, considering the intermediate principal stress effect, the amount of geomechanical properties of rock mass; such as internal friction angle and cohesion are increased and consequently, the safety factor of stability condition will be larger than the obtained safety factor from biaxial failure criterion. Therefore, the main purpose of this paper is development of a slope stability analysis method that considers the effect of intermediate principal stress.
 
Methodology and Approaches
In this research, considering the circular failure conditions for soil and rock slopes, the Bishop's equilibrium method was extended based on the triaxial unified strength failure criterion. Also, for analyzing the stability and calculating the optimum slope angle, new diagrams were presented.
 
Results and Conclusions
The results showed that, without the intermediate principal stress effect, calculation of safety factor for investigating the slope stability condition is conservative and the net present value of mine is decreased consequently. Moreover, the sensitivity analyses showed that the amount of intermediate principal stress effect on the safety factor is not a function of the resistance properties of rock and soil.

Keywords

Main Subjects

Full Text

مطالعه‌های انجام شده برای بررسی وضعیت پایداری شیروانی­ها در معادن روباز از دو جنبه اهمیت فراوان دارد. جنبه اول جلوگیری از وقوع ناپایداری است که در صورت وقوع آن، مسائلی همچون تحمیل خسارت‌های جانی، وارد شدن خسارت‌های مالی به ماشین آلات و همچنین تحمیل خسارت‌های مالی ناشی از دست رفتن مواد معدنی و زمان در پی خواهد داشت. جنبه دوم، جنبه اقتصادی پروژه است. در اثر اعمال یک زاویه شیب محافظه کارانه، علاوه بر اینکه باعث از دست رفتن بخشی از ماده معدنی می‌شود، نسبت باطله برداری را نیز افزایش داده و در نتیجه ارزش خالص فعلی معدن دچار کاهش می­شود[3-1]. این درجه اهمیت، تا جایی پیش رفته است که اخیراً برخی از معادن روباز بزرگ دنیا و ایران با تحمل هزینه­های سنگین و با استفاده از فناوری رادار، اقدام به پایش و رفتارنگاری شرایط پایداری شیب دیواره­های معادن نموده­اند، اگرچه این روش­ها فقط زنگ خطری برای امکان وقوع ناپایداری هستند و قادر به افزایش پایداری یا افزایش ارزش خالص فعلی معدن نخواهند بود. بنابراین برای داشتن بالاترین ارزش خالص فعلی، باید زاویه شیب بهینه و ضریب ایمنی قبل از اجرای پروژه محاسبه شود.

References

[1]           Honarkhah, M., (2011), Stochastic Simulation of Patterns Using Distance-Based Pattern Modeling, Caers, J., Department of Energy Resources Engineering, Stanford University.
[2]           Strebelle,S. (2002). Conditional Simulation of Complex Geological Structures Using Multiple-Point Statistics, Mathematical Geology, 34(1), 1-21.
[3]           Mariethoz G, Renard P, Caers J (2010) Bayesian inverse problem and optimization with iterative spatial resampling. Water Resour Res 46.
[4]           Zhang, T.( 2006). Filter-based Training Pattern classification for spatial Pattern simulation , Switzer,P., The Department of Geological and Environmental Sciences, Stanford University.
[5]           Wua ,J. , Boucherb, A., Zhang, T.( 2008) , A SGeMS code for pattern simulation of continuous and categorical variables: FILTERSIM, Computers & Geosciences, 34(1) ,1863–1876,
[6]           Wua ,J. , Zhang, T., Journel, A. (2008), Fast FILTERSIM Simulation with Score-based Distance, Math Geosci, 40(1) , 773–788.
[7]           Mariethoz, G. ,Caers, J.(2015) , Multiple-point geostatistics, John Wiley & Sons, Ltd, USA.
[8]           Carvalho PRM, Costa JFCL, Rasera LG, Varella LES (2016) Geostatistical facies simulation with geometric patterns of a petroleum reservoir. Stoch Environ Res Risk Assess:1-18. doi: 10.1007/s00477–016–1243–5
[9]           Zhang T, Du Y, Li B, Zhang A (2017) Stochastic reconstruction of spatial data using LLE and MPS. Stoch Environ Res Risk Assess:1-14.
[10]         Zhang T, Du Y, Huang T, Yang J, Lu F, Li X (2016) Reconstruction of porous media using ISOMAP-based MPS. Stoch Environ Res Risk Assess. 30(1):395–412.
[11]         Wu, J.(2007), 4D Seismic and Multiple-Point Pattern Data Integration Using Geostatistics, Journel, A.G. Department of Energy Resources Engineering, Stanford University.
[12]         Burc,G.,Caers,J.(2004) , A Multiple-scale, Pattern-based Approach to Sequential Simulation, springer, Quantitative Geology and Geostatistics, 14(1), 255-264.
[13]         Zhang, T., Switzer, P., Journel, A.,(2006) , Filter-Based Classification of Training Image Pattern for Spatial Simulation, Mathematical Geology, 38(1), 63-80.
[14]         Duda, R., Hart, P., Seork,D., ( 2001). Pattern Classification, the Electrical Engineering Department at San Jose State University, San Jose, California.
[15]         Shannon, C.E.,(1948) A Mathematical Theory of Communication. Bell System Technical Journal, 27(1) 379-423.
[16]         Cover TM., Thomas JA.,( 1991). Elements of information theory.Wiley, New York.
[17]         Tibshirani, R., G. Walther, and T. Hastie. Estimating the number of clusters in a data set via the gap statistic. Journal of the Royal Statistical Society: Series B. Vol. 63, Part 2, 2001, pp. 411–423.
[18]         Maimon O. and Rokach L., (Ed). 2010, Data Mining and Knowledge Discovery Handbook, Second Edition, Springer
Journal of Analytical and Numerical Methods in Mining Engineering
Volume 9, Issue 18
May 2019
Pages 117-127

Files

History

  • Receive Date: 19 November 2017
  • Revise Date: 21 November 2018
  • Accept Date: 30 August 2018

Share

How to cite

Statistics