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The probabilistic key‐group method
Author(s) -
Yarahmadi Bafghi A. R.,
Verdel T.
Publication year - 2004
Publication title -
international journal for numerical and analytical methods in geomechanics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.419
H-Index - 91
eISSN - 1096-9853
pISSN - 0363-9061
DOI - 10.1002/nag.339
Subject(s) - probabilistic logic , key (lock) , monte carlo method , block (permutation group theory) , group (periodic table) , context (archaeology) , computer science , moment (physics) , mathematical optimization , stability (learning theory) , algorithm , mathematics , artificial intelligence , machine learning , statistics , paleontology , chemistry , geometry , computer security , organic chemistry , physics , classical mechanics , biology
Key‐block approaches are widely used in the analysis of rock slopes. The key‐group method improves such analyses by taking into account groups of blocks instead of single blocks. Nevertheless, these stability analyses are usually carried out within a context where uncertainty may be a difficult problem to overcome. In the present paper, we propose introducing probabilistic approaches into the key‐group method in order to account for uncertainty in the mechanical parameters of the problem to be solved. Both the first‐order, second‐moment method (FOSM) and the advanced second‐moment method (ASMM) are considered herein and compared with Monte‐Carlo simulations through the use of five theoretical case studies. Lastly, the probabilistic key‐group method (PKGM) is qualified. Copyright © 2004 John Wiley & Sons, Ltd.