WANG Ying-chao, JING Hong-wen, ZHANG Qiang, et al. A normal cloud model-based study of grading prediction of rockburst intensity in deep underground engineering[J]. 2015, 36(4): 1189-1194.
WANG Ying-chao, JING Hong-wen, ZHANG Qiang, et al. A normal cloud model-based study of grading prediction of rockburst intensity in deep underground engineering[J]. 2015, 36(4): 1189-1194.DOI: 10.16285/j.rsm.2015.04.037.
Rockburst is a type of geologic hazards frequently occurring in the deep underground engineering construction. The prediction and classification of rockburst remains an unrsolved problem in underground rock engineering. To evaluate the rockburst intensity
a novel comprehensive evaluation model based on the normal cloud model and Delphi method is developed to overcome the issue of fuzziness and randomness in evaluating the rockburst intensity. Based on a comprehensive analysis of the controlling factors of rockburst
four factors are chosen as the indices for the intensity evaluation
including the ratio of uniaxial compressive strength and tensile strength
?c / ?t
the ratio of tangential stress and uniaxial compressive strength
?? /?c
the rock brittleness index
Is
and the elastic strain energy index
Wet. The Delphi method is adopted to determine the weighting coefficient for each evaluation index. The normal cloud model is used to calculate the cloud characteristics for each evaluation index in rockburst classification
which generates the normal cloud droplets
and the undetermined mapping between the rockburst intensity and the evaluation index are realized
keeping the randomness in the evaluation process. Finally
the proposed model is validated with a series of typical rock projects. The obtained results show a good agreement with practical rockburst classification
and the accuracy of cloud model is higher than that of the efficacy coefficient method and set pair analysis method. indicating that the normal cloud theory is applicable and effective for classifying the rockburst intensity.