화약ㆍ발파 (Explosives and Blasting)

대한화약발파공학회 (Korean Society of Explosives and Blasting Engineering)
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동시출현 핵심단어 분석을 활용한 암반발파 분야의 연구 동향 분석

Analysis of Research Trends in the Rock Blasting Field Using Co-Occurrence Keyword Analysis

  • 김민주 (인하대학교 에너지자원공학과) ;
  • 권상기 (인하대학교 에너지자원공학과)
  • 투고 : 2022.01.05
  • 심사 : 2022.01.24
  • 발행 : 2022.03.31
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초록

효과적이며 안전한 발파 기술을 개발하거나 국내에 도입하기 위해서는 세계 각국에서의 발파 분야 연구 동향을 파악하는 것이 필요하다. 국내외 발파 관련 연구 동향 분석은 일부 연구 논문들을 대상으로 제한적인 범위에서 수행되는 것이 일반적이다. 본 논문에서는 국제학술지에 게제된 전체 논문들을 대상으로 VOSviewer를 이용한 계량서지분석을 실시하여 발파 분야의 연구 동향 변화를 파악하고자 하였다. 시기별 핵심단어 분석 결과, 2000년대는 대체적으로 게재 논문의 수가 적고 전체적인 핵심단어 수도 적었지만, 2010년 이후 게재 논문 개수의 급격한 증가와 핵심단어의 다양화, 특히 인공지능과 관련된 핵심단어들이 등장하였다. 2017~2021년의 핵심단어 분석 결과, 다양한 하이브리드 인공지능 기법들이 발파 영향 평가에 활발하게 활용되고 있음을 알 수 있었다.

In order to develop effective and safe blasting techniques or to introduce foreign advanced blasting techniques to domestic industry, the analysis of research trend in blasting field in the world is essential. In generally, such a research trend analysis was carried out for limited number of published papers. In this study, a bibliometric analysis was performed using VOSviewer for the overall papers published in international journals to figure out the variation of research trend in blasting area. From the keyword analysis, it was found that the number of published papers and the number of overall keywords was limited in the 2000s. Since 2010, the number of published papers was increased rapidly and the keywords were diversified with the introduction of artificial intelligence(AI). The keyword analysis for 2017~2021 showed that various hybrid AI techniques were actively applied in the evaluation of blasting effect.

키워드

과제정보

이 논문은 한국연구재단의 이공분야기초연구사업 (NRF-2019R1D1A1060884)의 지원으로 수행되었습니다.

참고문헌

  1. 김민주, L. A. Isamil, 권상기, 2021, 발파 분야에서의 인공지능 활용 현황, 화약.발파, Vol. 39, No. 3, pp. 44-64. https://doi.org/10.22704/KSEE.2021.39.3.044
  2. 류창하, 2001, 발파공학의 국내.외 연구 동향 및 기술적 수준 분석, 화약.발파, Vol. 19, No. 3, pp. 7-25.
  3. 이상인, 서정일, 이요한, 김석우, 전근우, 2019, 산지하천을 대상으로 한 국내 연구 동향 분석: 국제 연구동향과의 비교, 한국환경생태학회지, Vol. 33, No. 2, pp. 216-227. https://doi.org/10.13047/KJEE.2019.33.2.216
  4. 임영협, 김석우, 남수연, 전근우, 김민석, 2020, 동시출현단어 분석을 이용한 토양침식 연구 동향 비교 분석, 한국환경생태학회지, Vol. 34, No. 5, pp. 413-424. https://doi.org/10.13047/KJEE.2020.34.5.413
  5. 정상규, 반영운, 2020, 계량서지 분석을 통한 생태산업단지의 국제적 연구 동향 규명, 한국생태환경건축학회 논문집, Vol. 20, No. 4, pp. 41-46.
  6. 진채령, 어수형, 2018, 텍스트마이닝과 동시출현단어분석을 이용한 국내 조류학 연구 동향, 한국조류학회지, Vol. 25, No. 2, pp. 126-132. https://doi.org/10.30980/kjo.2018.12.25.2.126
  7. Bahrami, A., Monjezi, M., Goshtasbi, K., and Ghazvinian, A., 2011, Prediction of rock fragmentation due to blasting using artificial neural network, Engineering with Computers, Vol. 27, No. 2, pp. 177-181. https://doi.org/10.1007/s00366-010-0187-5
  8. Chen, J. H., Zhang, J. S., and Li, X. P., 2016, Study of presplitting blasting parameters and its application based on rock blasting-induced damage theory, Rock and Soil Mechanics, Vol. 37, No. 5, pp. 1441-1450.
  9. Cho, S. H. and Kaneko, K., 2004, Rock fragmentation control in blasting, Materials Transactions, Vol. 45, No. 5, pp. 1722-1730. https://doi.org/10.2320/matertrans.45.1722
  10. Cho, S. H., Nakamura, Y., Mohanty, B., Yang, H. S. and Kaneko, K., 2008, Numerical study of fracture plane control in laboratory-scale blasting, Engineering Fracture Mechanics, Vol. 75, No. 13, pp. 3966-3984. https://doi.org/10.1016/j.engfracmech.2008.02.007
  11. Dehghani, H. and Ataee-pour, M., 2011, Development of a model to predict peak particle velocity in a blasting operation, International Journal of Rock Mechanics and Mining Sciences, Vol. 48, No. 1, pp. 51-58. https://doi.org/10.1016/j.ijrmms.2010.08.005
  12. Duan, B. F., Xia, H. L. and Yang, X. X., 2018, Impacts of bench blasting vibration on the stability of the surrounding rock masses of roadways, Tunnelling and Underground Space Technology, Vol. 71, pp. 605-622. https://doi.org/10.1016/j.tust.2017.10.012
  13. Dumakor-Dupey, N. K., Arya, S. and Jha, A., 2021, Advances in blast-induced impact prediction-a review of machine learning applications, Minerals, Vol. 11, No. 6, pp. 601. https://doi.org/10.3390/min11060601
  14. Fakhimi, A. and Lanari, M., 2014, DEM-SPH simulation of rock blasting, Computers and Geotechnics, Vol. 55, pp. 158-164. https://doi.org/10.1016/j.compgeo.2013.08.008
  15. Gao, Q. D., Lu, W. B., Yan, P., Hu, H. R., Yang, Z. W., and Chen, M., 2019, Effect of initiation location on distribution and utilization of explosion energy during rock blasting, Bulletin of Engineering Geology and the Environment, Vol. 78, No. 5, pp. 3433-3447. https://doi.org/10.1007/s10064-018-1296-4
  16. Girvan, M. and Newman, M. E. J., 2002, Community structure in social and biological networks, Proceedings of the National Academy of Sciences of the United States of America, Vol. 99, No. 12, pp. 7821-7826. https://doi.org/10.1073/pnas.122653799
  17. Hamdi, E. and du Mouza, J., 2005, A methodology for rock mass characterisation and classification to improve blast results. International Journal of Rock Mechanics and Mining Sciences, Vol. 42, No. 2, pp. 177-194. https://doi.org/10.1016/j.ijrmms.2004.07.005
  18. Hasanipanah, M., Amnieh, H. B., Arab, H. and Zamzam, M. S., 2018, Feasibility of PSO-ANFIS model to estimate rock fragmentation produced by mine blasting, Neural Computing & Applications, Vol. 30, No. 4, pp. 1015-1024. https://doi.org/10.1007/s00521-016-2746-1
  19. He, Q., 1999, Knowledge discovery through co-word analysis, Library Trends, Vol. 48, No. 1, pp. 133-159.
  20. Hu, S. W. and Chen, S. H., 2019, Analytical solution of dynamic response of rock bolt under blasting vibration, Rock and Soil Mechanics, Vol. 40, No. 1, pp. 281-287.
  21. Hu, Y. G., Lu, W. B., Chen, M., Yan, P. and Yang, J. H., 2014, Comparison of blast-induced damage between presplit and smooth blasting of high rock slope, Rock Mechanics and Rock Engineering, Vol. 47, No. 4, pp. 1307-1320. https://doi.org/10.1007/s00603-013-0475-7
  22. Jang, H., Handel, D., Ko, Y. H., Yang, H. S. and Miedecke, J., 2018, Effects of water deck on rock blasting performance, International Journal of Rock Mechanics and Mining Sciences, Vol. 112, pp. 77-83. https://doi.org/10.1016/j.ijrmms.2018.09.006
  23. Jayasinghe, B., Zhao, Z. Y., Chee, A. G. T., Zhou, H. Y. and Gui, Y. L., 2019, Attenuation of rock blasting induced ground vibration in rock-soil interface, Journal of Rock Mechanics and Geotechnical Engineering, Vol. 11, No. 4, pp. 770-778. https://doi.org/10.1016/j.jrmge.2018.12.009
  24. Jeon, S., Kim, T. H. and You, K. H., 2015, Characteristics of crater formation due to explosives blasting in rock mass, Geomechanics and Engineering, Vol. 9, No. 3, pp. 329-344. https://doi.org/10.12989/gae.2015.9.3.329
  25. Jessu, K. V., Spearing, A. J. S. and Sharifzadeh, M., 2018, A parametric study of blast damage on hard rock pillar strength, Energies, Vol. 11, No. 7, pp. 77-83. https://doi.org/10.3390/en11010077
  26. Ji, F., Lu, J. F., Shi, Y. C. and Zhou, C. H., 2013, Mechanical response of surrounding rock of tunnels constructed with the TBM and drill-blasting method, Natural Hazards, Vol. 66, No. 2, pp. 545-556. https://doi.org/10.1007/s11069-012-0500-2
  27. Jiang, W. C., Arslan, C. A., Tehrani, M. S., Khorami, M. and Hasanipanah, M., 2019, Simulating the peak particle velocity in rock blasting projects using a neuro-fuzzy inference system, Engineering with Computers, Vol. 35, No. 4, pp. 1203-1211. https://doi.org/10.1007/s00366-018-0659-6
  28. Kahriman, A., 2002, Analysis of ground vibrations caused by bench blasting at Can Open-pit Lignite Mine in Turkey, Environmental Geology, Vol. 41, No. 6, pp. 653-661. https://doi.org/10.1007/s00254-001-0446-2
  29. Kang, S. S. and Jang, H., 2020, A case study on tunnel blasting design evaluation considering blast damage zone, Science and Technology of Energetic Materials, Vol. 81, No. 4, pp. 106-113.
  30. Kilic, A. M., Yasar, E., Erdogan, Y. and Ranjith, P. G., 2009, Influence of rock mass properties on blasting efficiency, Scientific Research and Essays, Vol. 4, No. 11, pp. 1213-1224.
  31. Kim, H., Fukuda, D., Ikezawa, J., Moriya, K., Cho, S. H. and Kaneko, K., 2013, Dynamic fracture process analysis in rock-like materials for axisymmetric problem, Science and Technology of Energetic Materials, Vol. 74, No. 3-4, pp. 73-79.
  32. Kim, H. M., Rutqvist, J., Jeong, J. H., Choi, B. H., Ryu, D. W. and Song, W. K., 2013, Characterizing excavation damaged zone and stability of pressurized lined rock caverns for underground compressed air energy storage, Rock Mechanics and Rock Engineering, Vol. 46, No. 5, pp. 1113-1124. https://doi.org/10.1007/s00603-012-0312-4
  33. Kim, Y. and Bruland, A., 2019, Analysis and evaluation of tunnel contour quality index, Automation in Construction, Vol. 99, pp. 223-237. https://doi.org/10.1016/j.autcon.2018.12.008
  34. Kulatilake, P., Qiong, W., Hudaverdi, T. and Kuzu, C., 2010, Mean particle size prediction in rock blast fragmentation using neural networks, Engineering Geology, Vol. 114, No. 3-4, pp. 298-311. https://doi.org/10.1016/j.enggeo.2010.05.008
  35. Lanari, M. and Fakhimi, A., 2015, Numerical study of contributions of shock wave and gas penetration toward induced rock damage during blasting, Computational Particle Mechanics, Vol. 2, No. 2, pp. 197-208. https://doi.org/10.1007/s40571-015-0053-8
  36. Lawal, A. I., Kwon, S., Hammed, O. S., and Idris, M. A., 2021, Blast-induced ground vibration prediction in granite quarries: An application of gene expression programming, ANFIS, and sine cosine algorithm optimized ANN, International Journal of Mining Science and Technology, Vol. 31, No. 2, pp. 265-277. https://doi.org/10.1016/j.ijmst.2021.01.007
  37. Lawal, A. I., Kwon, S. and Kim, G. Y., 2021, Prediction of an environmental impact of tunnel blasting using ordinary artificial neural network, particle swarm and Dragonfly optimized artificial neural networks, Applied Acoustics, Vol. 181, pp. 108-122.
  38. Lawal, A. I., Kwon, S., and Kim, G. Y., 2021, Prediction of the blast-induced ground vibration in tunnel blasting using ANN, moth-flame optimized ANN, and gene expression programming, Acta Geophysica, Vol. 69, No. 1, pp. 161-174. https://doi.org/10.1007/s11600-020-00532-y
  39. Li, H. B., Xia, X. A., Li, J. C., Zhao, J. A., Liu, B. and Liu, Y. Q., 2011, Rock damage control in bedrock blasting excavation for a nuclear power plant, International Journal of Rock Mechanics and Mining Sciences, Vol. 48, No. 2, pp. 210-218. https://doi.org/10.1016/j.ijrmms.2010.11.016
  40. Raina, A., Murthy, V. and Soni, A., 2014, Flyrock in bench blasting: a comprehensive review, Bulletin of Engineering Geology and the Environment, Vol. 73, No. 4, pp. 1199-1209. https://doi.org/10.1007/s10064-014-0588-6
  41. Raina, A. K., Murthy, V. and Soni, A. K., 2015, Flyrock in surface mine blasting: understanding the basics to develop a predictive regime, Current Science, Vol. 108, No. 4, pp. 660-665.
  42. Saiang, D. and Nordlund, E., 2009, Numerical analyses of the influence of blast-induced damaged rock around shallow tunnels in brittle rock, Rock Mechanics and Rock Engineering, Vol. 42, No. 3, pp. 421-448. https://doi.org/10.1007/s00603-008-0013-1
  43. Shams, S., Monjezi, M., Majd, V. J. and Armaghani, D. J., 2015, Application of fuzzy inference system for prediction of rock fragmentation induced by blasting, Arabian Journal of Geosciences, Vol. 8, No. 12, pp. 10819-10832. https://doi.org/10.1007/s12517-015-1952-y
  44. Son, M. and Cording, E. J., 2007, Ground-liner interaction in rock tunneling, Tunnelling and Underground Space Technology, Vol. 22, No. 1, pp. 1-9. https://doi.org/10.1016/j.tust.2006.03.002
  45. Van Eck, N. J. and Waltman, L., 2011, Text mining and visualization using VOSviewer, arXiv preprint arXiv:1109.2058.
  46. Van Eck, N. J. and Waltman, L., 2013, VOSviewer manual, Leiden: Univeristeit Leiden, Vol. 1, No. 1, pp. 1-53.
  47. Wallin, J. A., 2005, Bibliometric methods: pitfalls and possibilities, Basic & clinical pharmacology & toxicology, Vol. 97, No. 5, pp. 261-275. https://doi.org/10.1111/j.1742-7843.2005.pto_139.x
  48. Wang, Z. L. and Konietzky, H., 2009, Modelling of blast-induced fractures in jointed rock masses, Engineering Fracture Mechanics, Vol. 76, No. 12, pp. 1945-1955. https://doi.org/10.1016/j.engfracmech.2009.05.004
  49. Xu, S. D., Chen, T. X., Liu, J. Q., Zhang, C. R. and Chen, Z. Y., 2021, Blasting vibration control using an improved artificial neural network in the Ashele copper mine, Shock and Vibration, Vol. 2021.
  50. Yan, C. Z., Sun, G. H., Zheng, H. and Ge, X. R., 2015, Simulation of explosive gas-driven rock fracture by FEM/DEM, Rock and Soil Mechanics, Vol. 36, No. 8, pp. 2419-2425.
  51. Zaid, M. and Sadique, M. R., 2021, Blast resistant behaviour of tunnels in sedimentary rocks, International Journal of Protective Structures, Vol. 12, No. 2, pp. 153-173. https://doi.org/10.1177/2041419620951211
  52. Zhang, Y. Q., Hao, H. and Lu, Y., 2003, Anisotropic dynamic damage and fragmentation of rock materials under explosive loading, International Journal of Engineering Science, Vol. 41, No. 9, pp. 917-929. https://doi.org/10.1016/S0020-7225(02)00378-6