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A continuum mechanics‐based framework for optimizing boundary and finite element meshes associated with underground excavations‐framework
Author(s) -
Zsáki Attila M.,
Curran John H.
Publication year - 2005
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.459
Subject(s) - computation , polygon mesh , excavation , rock mechanics , computer science , finite element method , rock mass classification , continuum mechanics , closure (psychology) , algorithm , engineering , structural engineering , geotechnical engineering , mechanics , computer graphics (images) , economics , market economy , physics
Many field problems, from stress analysis, heat transfer to contaminant transport, deal with disturbances in a continuum caused by a ‘source’ (defined by its discrete geometry) and a ‘region of interest’ (where a solution is sought). Depending on the location of ‘regions of interest’ in relation to the ‘sources’, the level of geometric detail necessary to represent the ‘sources’ in a model can vary considerably. A practical application of stress analysis in mining is the evaluation of the effects of continuous excavation on the states of stress around mine openings. Labour intensive model preparation and lengthy computation coupled with the interpretation of analysis results can have considerable impact on the successful operation of an underground mine, where stope failures can cost tens of millions of dollars and possibly lead to closure of the mine. A framework is proposed based on continuum mechanics principles to automatically optimize the level of geometric detail required for an analysis by simplifying the model geometry using expanded and modified algorithms that originated in computer graphics. This reduction in model size directly translates to savings in computational time. The results obtained from an optimized model have accuracy comparable to the uncertainty in input data (e.g. rock mass properties, geology, etc.). This first paper defines the optimization framework, while a companion paper investigates its efficiency and application to practical mining and excavation‐related problems. Copyright © 2005 John Wiley & Sons, Ltd.