Stress relaxation plays an important role in the design of underground stopes. The aim of this paper is to assess the stope stability in connection with the stress relaxation using a classification approach. Three types of stress relaxation were clearly defined, namely partial relaxation, tangential relaxation and full relaxation. A neural network classifier was implemented to assess the stability of the stopes on the basis of case histories of stope performances. The results of the classification were compared to existing empirical methods of quantifying the stress relaxation. Overall, the present study shows higher classification accuracies, especially when the stress relaxation was considered. The results suggested that the relaxation type can be a good predictor of stability. Relaxed stope (full and tangential stress relaxation) cases are the most critical in the sense that lower accuracies were obtained and the probability of correct classification is rather erratic.
AdokoA-C, JiaoY-Y, WuL, WangH, WangZ-H.2013. Predicting tunnel convergence using multivariate adaptive regression spline and artificial neural network. Tunnel Underground Space Technol. 38(0):368–376. doi: 10.1016/j.tust.2013.07.023
2.
AdokoAC, PhumaphiPT, ZvarivadzaT.2017. Quantifying rock mass behavior around underground excavations. The 51st US Rock Mechanics / Geomechanics Symposium, June 25–28; San Francisco, CA.
3.
ClarkLM.1998. Minimizing dilution in open stope mining with a focus on stope design and narrow vein longhole blasting [MSc thesis]. Vancouver: University of British Columbia.
4.
DiederichsMS.2003. Manuel Rocha medal recipient rock fracture and collapse under low confinement conditions. Rock Mech Rock Eng. 36(5):339–381. doi: 10.1007/s00603-003-0015-y
5.
DiederichsMS, KaiserPK.1999. Tensile strength and abutment relaxation as failure control mechanisms in underground excavations. Int J Rock Mech Min Sci. 36(1):69–96. doi: 10.1016/S0148-9062(98)00179-X
HashibaK, FukuiK.2016. Time-dependent behaviors of granite: loading-rate dependence, creep, and relaxation. Rock Mech Rock Eng. 49(7):2569–2580. doi: 10.1007/s00603-016-0952-x
8.
HudsonJA, HarrisonJP.1997. 13 - Rock dynamics and time-dependent aspects. In: HudsonJA, HarrisonJP, editors. Engineering rock mechanics. Oxford: Pergamon; p. 207–221.
9.
KaiserPK, FalmagneV, SuorineniFT, DiederichsMS, TannantDD.1997. Incorporation of rock mass relaxation and degradation into empirical stope design. The 99th CIM Annual General Meeting; Vancouver, Canada.
10.
KaiserPK, YaziciS, MaloneyS.2001. Mining-induced stress change and consequences of stress path on excavation stability — a case study. Int J Rock Mech Min Sci. 38(2):167–180. doi: 10.1016/S1365-1609(00)00038-1
11.
LamHK, EkongU, LiuH, XiaoB, AraujoH, LingSH, ChanKY.2014. A study of neural-network-based classifiers for material classification. Neurocomputing. 144:367–377. doi: 10.1016/j.neucom.2014.05.019
12.
MathewsK, HoekE, WyllieD, StewartS.1981. Prediction of stable excavation spans at depths below 1000 m in hard rock mines. CANMET Report, DSS Serial No OSQ80-00081.
13.
MawdesleyC, TruemanR, WhitenWJ.2001. Extending the Mathews stability graph for open–stope design. Min Technol. 110(1):27–39. doi: 10.1179/mnt.2001.110.1.27
14.
MilneD, YaoM, AllenG.2002. Quantifying the effect of hanging wall undercutting on stope dilution. The 104th CIM annual general meeting, Vancouver.
15.
MitriHS, HughesR, ZhangY.2011. New rock stress factor for the stability graph method. Int J Rock Mech Min Sci. 48(1):141–145. doi: 10.1016/j.ijrmms.2010.09.015
16.
PakalnisRT.1986. Empirical stope design at the Ruttan Mine, Sherritt Gordon Mines Ltd [PhD dissertation]. Vancouver: University of British Columbia.
17.
PakalnisRT, TenneyD, LangB.1991. Numerical modelling as a tool in stope design. CIM Bull. 84:64–73.
18.
ParaskevopoulouC, PerrasM, DiederichsM, AmannF, LöwS, LamT, JensenM.2017. The three stages of stress relaxation - observations for the time-dependent behaviour of brittle rocks based on laboratory testing. Eng Geol. 216:56–75. doi: 10.1016/j.enggeo.2016.11.010
19.
PotvinY.1988. Empirical open stope design in Canada [PhD dissertation]. The University of British Columbia.
20.
QiC, FourieA, MaG, TangX.2018. A hybrid method for improved stability prediction in construction projects: a case study of stope hangingwall stability. Appl Soft Comput. 71:649–658. doi: 10.1016/j.asoc.2018.07.035
21.
StewartPC.2005. Minimising dilution in narrow vein mines [PhD dissertation]. Queensland: The University of Queensland.
22.
StewartSBV, ForsythWW.1995. The Mathews method for open stope design. CIM Bull. 88(992):45–53.
23.
StewartPC, TruemanR.2004. Quantifying the effect of stress relaxation on excavation stability. Min Technol. 113(2):107–117. doi: 10.1179/037178404225004986
24.
SuorineniFT, TannantDD, KaiserPK, DusseaultMB.2001. Incorporation of a Fault factor into the stability graph method: Kidd mine case studies. Mineral Resour Eng. 10(01):3–37. doi: 10.1142/S0950609801000506
25.
VallejosJA, DeloncaA, FuenzalidaJ, BurgosL.2016. Statistical analysis of the stability number adjustment factors and implications for underground mine design. Int J Rock Mech Min Sci. 87(Supplement C):104–112. doi: 10.1016/j.ijrmms.2016.06.001
26.
VallejosJA, MirandaR, BurgosL, PerezE.2017. Development of new design tools for open stoping underground mines. The 51st US rock mechanics/geomechanics symposium; June 25–28; San Francisco, CA, USA.
27.
VeelenturfLPJ.1995. Analysis and applications of artificial neural networks. Midsomer Norton: Prentice Hall International (UK) Ltd.
28.
YangH, LiuJ, ZhouX.2017. Effects of the loading and unloading conditions on the stress relaxation behavior of pre-cracked granite. Rock Mech Rock Eng. 50(5):1157–1169. doi: 10.1007/s00603-016-1161-3
