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Integrating unascertained measurement and information entropy theory to assess blastability of rock mass

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Abstract

Due to the complex features of rock mass blastability assessment systems, an evaluation model of rock mass blastability was established on the basis of the unascertained measurement (UM) theory and the actual characteristics of the project. Considering a comprehensive range of intact rock properties and discontinuous structures of rock mass, twelve main factors influencing the evaluation blastability of rock mass were taken into account in the UM model, and the blastability evaluation index system of rock mass was constructed. The unascertained evaluation indices corresponding to the selected factors for the actual situation were solved both qualitatively and quantitatively. Then, the UM function of each evaluation index was obtained based on the initial data for the analysis of the blastability of six rock mass at a highway improvement cutting site in North Wales. The index weights of the factors were calculated by entropy theory, and credible degree identification (CDI) criteria were established according to the UM theory. The results of rock mass blastability evaluation were obtained by the CDI criteria. The results show that the UM model assessment results agree well with the actual records, and are consistent with those of the fuzzy sets evaluation method. Meanwhile, the unascertained superiority degree of rock mass blastability of samples S1–S6 which can be calculated by scoring criteria are 3.428 5, 3.453 3, 4.058 7, 3.675 9, 3.516 7 and 3.289 7, respectively. Furthermore, the proposed method can take into account large amount of uncertain information in blastability evaluation, which can provide an effective, credible and feasible way for estimating the blastability of rock mass. Engineering practices show that it can complete the blastability assessment systematically and scientifically without any assumption by the proposed model, which can be applied to practical engineering.

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References

  1. KAUSHIK D, PHALGUNI S. Concept of blastability—An update [J]. The Indian Mining & Engineering Journal, 2003, 42(8/9): 24–31.

    Google Scholar 

  2. XUE Jian-gang, ZHOU Jian, SHI Xiu-zhi, WANG Huai-yong, HU Hai-yan. Assessment of classification for rock mass blastability based on entropy coefficient of attribute recognition model [J]. Journal of Central South University: Science and Technology, 2010, 41(1): 251–256. (in Chinese)

    Google Scholar 

  3. LATHAM J P, LU P. Development of an assessment system of blastability for rock masses [J]. International Journal of Rock Mechanics and Mining Sciences, 1999, 36(1): 41–55.

    Article  Google Scholar 

  4. RAKISHEV B R. A new characteristics of the blastability of rock in quarries [J]. Soviet Mining Science, 1982(17): 248–251.

  5. HEINEN R H, DIMOCK R R. The use of sonic measurements to determine the blastability of rocks [C]// Proceedings of the Second Conference on Explosive and Blasting Techniques. Luisville, Kentucky, 1976: 234–248.

  6. LILLY P. An empirical method of assessing rock mass blastability [C]// Large open pit mines Conference. Newman, Australia, 1986: 89–92.

  7. FENG X T. A neural network approach to comprehensive classification of rock stability, blastability and drillability [J]. International Journal of Mining, Reclamation and Environment, 1995, 9(2): 57–62.

    Article  Google Scholar 

  8. AZIMI Y, OSANLOO M, AAKBARPOUR-SHIRAZI M, AGHAJANI BAZZAZI A. Prediction of the blastability designation of rock masses using fuzzy sets [J]. International Journal of Rock Mechanics and Mining Sciences, 2010, 47(7): 1126–1140.

    Article  Google Scholar 

  9. HAN J, WEIYA X, SHOUYI X. Artificial neural network method of rock mass blastability classification [C]// Proceedings of the Fifth International Conference on GeoComputation. London, UK, 2000: 23–28.

  10. WANG Guang-yuan. Mathematics treatment of unascertained information [J]. Journal of Civil Engineering Institute of Harbin, 1990, 23(4): l–9. (in Chinese)

    Google Scholar 

  11. LIU K D, CAO Q K, PANG Y J. A method of fault diagnosis based on unascertained set [J]. Acta Automatic Sinica, 2004, 30(5): 747–756.

    Google Scholar 

  12. SHI Xiu-zhi, ZHOU Jian, DONG Lei, HU Han-yan. WANG Huai-yong, CHEN Shou-ru. Application of unascertained measurement model to prediction of classification of rockburst intensity [J]. Chinese Journal of Rock Mechanics and Engineering, 2010, 29(S1): 2720–2727. (in Chinese)

    Google Scholar 

  13. LIU Ai-hua, DONG Lei, DONG Long-jun. Optimization model of unascertained measurement for underground mining method selection and its application [J]. Journal of Central South University of Technology, 2010, 17(4): 949–961.

    Google Scholar 

  14. SHI Xiu-zhi, ZHOU Jian. Application of uncertainty average clustering measurement model to classification of tunnel surrounding rock [J]. Journal of Civil, Architectural & Environmental Engineering, 2009, 31(2): 62–67. (in Chinese)

    Google Scholar 

  15. Li Y C, SUO J J. Safety assessment of platform loadout procedures based on unascertained measures [J]. Chinese Journal of Oceanology and Limnology, 2007, 25(4): 354–358.

    Article  Google Scholar 

  16. JAYNES E T. Information theory and statistical mechanics [J]. Physical Review, 1957(106): 620–630.

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Correspondence to Jian Zhou  (周健).

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Foundation item: Project(50934006) supported by the National Natural Science Foundation of China; Project(2010CB732004) supported by the National Basic Research Program of China; Project(2009ssxt230) supported by the Central South University Innovation Fund, China; Project(CX2011B119) supported by the Graduated Students’ Research and Innovation Fund of Hunan Province, China

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Zhou, J., Li, Xb. Integrating unascertained measurement and information entropy theory to assess blastability of rock mass. J. Cent. South Univ. 19, 1953–1960 (2012). https://doi.org/10.1007/s11771-012-1231-y

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  • DOI: https://doi.org/10.1007/s11771-012-1231-y

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