A Systematic Literature Review on the Influence of Geology and Geotechnical Parameters in Blast Design Optimization
DOI:
https://doi.org/10.29303/goescienceed.v7i1.1763Keywords:
Blast design optimization, geological parameters, geotechnical parameters, rock fragmentation, blasting performance, systematic literature reviewAbstract
Blasting is a critical operation in mining and civil engineering projects, and its effectiveness is strongly influenced by both blasting parameters and the geological characteristics of the rock mass. However, conventional blast design approaches often rely mainly on empirical guidelines and explosive parameters, while the variability of geological and geotechnical conditions is frequently underrepresented in the design process. Therefore, this study aims to systematically review and synthesize existing scientific literature on the influence of geological and geotechnical parameters in blast design optimization in order to identify key controlling factors, research trends, and technological developments that support more efficient and environmentally responsible blasting practices. This research adopts a systematic literature review approach based on established review procedures. Relevant scientific publications were collected from major academic databases, particularly Scopus indexed journals, using structured search strings applied to article titles, abstracts, and keywords. The selected studies were screened and analyzed, and the findings were synthesized into several thematic categories related to geological conditions, rock mass properties, blasting performance, environmental impacts, and emerging technologies in blast design optimization. The results show that geological and geotechnical parameters such as rock strength, discontinuity characteristics, structural geology, and rock mass classification significantly influence blasting outcomes, including rock fragmentation, explosive energy distribution, ground vibration, and flyrock generation. The findings also highlight the importance of the interaction between blast design parameters and geological variability in determining blasting efficiency. In addition, recent technological developments, including Measurement While Drilling systems, numerical modeling techniques, and machine learning based predictive models, have improved the integration of geological information into blast design optimization. The novelty of this study lies in its comprehensive synthesis of interdisciplinary research that integrates geological characterization, geotechnical analysis, and blasting engineering within a unified conceptual framework. This study contributes to the advancement of blasting research by providing an integrated understanding of the role of geological and geotechnical parameters in blast design optimization and by highlighting the transition toward data driven and geology informed blasting strategies in modern mining operations.
References
Azizi, A., & Moomivand, H. (2021). A new approach to represent the impact of discontinuity spacing and rock mass description on the median fragment size of blasted rocks using image analysis of rock mass. Rock Mechanics and Rock Engineering, 54(4), 2013–2038. https://doi.org/10.1007/s00603-020-02337-3
Bhatawdekar, R., Bhandari, S., & Singh, T. N. (2021). Application of rock mass classification systems for evaluating blastability of rock masses. Journal of Mines, Metals and Fuels, 69(4), 150–158. https://doi.org/10.18311/jmmf/2021/28954
Chandrahas, S., Choudhary, B. S., Krishna Prasad, N. S. R., Musunuri, V., & Rao, K. K. (2021). An investigation into the effect of rock mass properties on mean fragmentation. Archives of Mining Sciences, 66(4), 561–578. https://doi.org/10.24425/ams.2021.139597
Choudhary, B. S., Sonu, K., Kishore, K., & Anwar, S. (2016). Effect of rock mass properties on blast induced rock fragmentation. International Journal of Mining and Mineral Engineering, 7(2), 89–101. https://doi.org/10.1504/IJMME.2016.076489
Dumakor-Dupey, N. K., Aryafar, A., & Yakubu, I. (2021). Machine learning techniques for predicting rock fragmentation in blasting operations. Engineering with Computers, 37(3), 1943–1956. https://doi.org/10.1007/s00366-019-00903-6
Dumakor-Dupey, N. K., Arya, S., & Jha, A. (2021). Advances in blast induced impact prediction. Minerals, 11(6), 601. https://doi.org/10.3390/min11060601
Fissha, Y., Khatti, J., Ikeda, H., Grover, K. S., Owada, N., Toriya, H., & Adachi, T. (2024). Predicting ground vibration during rock blasting using relevance vector machine improved with dual kernels and metaheuristic algorithms. Scientific Reports, 14, 20026. https://doi.org/10.1038/s41598-024-70939-w
Gebretsadik, A., Kumar, R., Fissha, Y., Kide, Y., Okada, N., Ikeda, H., Mishra, A. K., Armaghani, D. J., Ohtomo, Y., & Kawamura, Y. (2024). Enhancing rock fragmentation assessment in mine blasting through machine learning algorithms. Discover Applied Sciences, 6, 223. https://doi.org/10.1007/s42452-024-05888-0
Ghasemi, E., Ataei, M., & Hashemolhosseini, H. (2012). Prediction of rock fragmentation due to blasting in open pit mines. International Journal of Rock Mechanics and Mining Sciences, 60, 231–236. https://doi.org/10.1016/j.ijrmms.2012.01.013
Gholami, R., Rasouli, V., & Alavi, M. (2015). Blastability evaluation for rock mass fragmentation in central iron ore mines. International Journal of Mining Science and Technology, 25(1), 59–66. https://doi.org/10.1016/j.ijmst.2014.11.008
Guo, J., Zhao, P., & Li, P. (2023). Prediction and optimization of blasting induced ground vibration in open pit mines using intelligent algorithms. Applied Sciences, 13(12), 7166. https://doi.org/10.3390/app13127166
Haghnejad, A., Ahangari, K., Moarefvand, P., & Goshtasbi, K. (2019). Numerical investigation of the impact of rock mass properties on propagation of ground vibration. Natural Hazards, 96(2), 587–606. https://doi.org/10.1007/s11069-018-3541-6
Haghnejad, M., Goshtasbi, K., & Khandelwal, M. (2019). Influence of rock mass properties on blast induced ground vibration. International Journal of Mining Science and Technology, 29(1), 85–92. https://doi.org/10.1016/j.ijmst.2018.11.002
Hasanipanah, M., Armaghani, D. J., Amnieh, H. B., Majid, M. Z. A., & Tahir, M. M. (2018). Application of artificial neural networks for predicting blast induced ground vibration and air overpressure. Engineering with Computers, 34(4), 829–839. https://doi.org/10.1007/s00366-017-0563-7
Himanshu, V. K., Mishra, A. K., Roy, M. P., Shankar, R., Priyadarshi, V., & Vishwakarma, A. K. (2023). Influence of joint orientation and spacing on induced rock mass damage due to blasting in limestone mines. Mining, Metallurgy & Exploration, 40(6), 2349–2359. https://doi.org/10.1007/s42461-023-00763-7
Himanshu, S., Singh, P. K., & Roy, M. P. (2023). Influence of geological discontinuities on blast induced damage in limestone quarry blasting. Mining Technology. https://doi.org/10.1080/25726668.2023.2177253
Hoek, E., & Brown, E. T. (2019). The Hoek–Brown failure criterion and Geological Strength Index. Journal of Rock Mechanics and Geotechnical Engineering, 11(3), 445–463. https://doi.org/10.1016/j.jrmge.2018.08.001
Isheyskiy, V., & Sanchidrián, J. A. (2020). Prospects of measurement while drilling technology for drilling and blasting optimization. International Journal of Rock Mechanics and Mining Sciences, 129, 104284. https://doi.org/10.1016/j.ijrmms.2020.104284
Khandelwal, M., & Singh, T. N. (2009). Prediction of blast induced ground vibration using artificial neural network. International Journal of Rock Mechanics and Mining Sciences, 46(7), 1214–1222. https://doi.org/10.1016/j.ijrmms.2009.03.004
Li, T., Chen, M., Guo, B., Song, L., Fan, B., & Cui, S. (2024). Study on fragmentation characteristics of rock mass in bench blasting with different coupling media. Frontiers in Earth Science, 12. https://doi.org/10.3389/feart.2024.1445990
Li, X., Zhang, Q., Chen, J., & Liu, H. (2025). Influence of jointed rock mass on tunnel blasting damage and excavation profile. Tunnelling and Underground Space Technology. https://doi.org/10.1016/j.tust.2025.105373
Mohamad, E. T., Yi, C. S., Murlidhar, B. R., & Saad, R. (2018). Effect of geological structure on flyrock prediction in construction blasting. Geotechnical and Geological Engineering, 36(4), 2217–2235. https://doi.org/10.1007/s10706-018-0461-1
Mohamad, E. T., Armaghani, D. J., Hasanipanah, M., & Murlidhar, B. R. (2018). Flyrock prediction and risk assessment in blasting operations. Engineering Geology, 242, 111–121. https://doi.org/10.1016/j.enggeo.2018.05.013
Monjezi, M., Bahrami, A., Varjani, A. Y., & Sayadi, A. R. (2012). Prediction and control of flyrock in blasting operations. Safety Science, 50(2), 221–226. https://doi.org/10.1016/j.ssci.2011.08.032
Moher, D., Liberati, A., Tetzlaff, J., & Altman, D. G. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Medicine, 6(7), e1000097. https://doi.org/10.1371/journal.pmed.1000097
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., & Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71
Sanchidrián, J. A., Segarra, P., & López, L. M. (2007). Energy components in rock blasting. Rock Mechanics and Rock Engineering, 40(6), 549–569. https://doi.org/10.1007/s00603-006-0109-7
Saubi, O., Jamisola, R. S., Suglo, R. S., & Matsebe, O. (2026). Simultaneous prediction and optimisation of rock fragmentation and ground vibration using an ANN–RF ensemble in open pit blasting. Scientific Reports. https://doi.org/10.1038/s41598-025-33871-1
Singh, P. K., & Narendrula, R. (2007). The effect of joint orientation on blast fragmentation in limestone quarries. International Journal of Rock Mechanics and Mining Sciences, 44(3), 387–395. https://doi.org/10.1016/j.ijrmms.2006.09.005
Singh, P. K., Roy, M. P., Paswan, R. K., Sarim, M. D., Kumar, S., & Jha, R. R. (2016). Rock fragmentation control in opencast blasting. Engineering Geology, 210, 1–10. https://doi.org/10.1016/j.enggeo.2016.05.015
Strelec, S., Gazdek, M., & Kavur, B. (2025). Influence of rock mass properties and powder factor on the fractal dimension of rock fragmentation during blasting. Discover Geoscience. https://doi.org/10.1007/s44288-025-00146-1
Zhang, X., Li, Q., Chen, M., & Wang, Y. (2023). Integration of geological characteristics in mine-to-mill blasting optimization. Minerals Engineering, 198, 108056. https://doi.org/10.1016/j.mineng.2023.108056
Zhang, Z. X., Sanchidrián, J. A., Ouchterlony, F., & Luukkanen, S. (2023). Reduction of fragment size from mining to mineral processing: A review. Rock Mechanics and Rock Engineering, 56, 747–778. https://doi.org/10.1007/s00603-022-03030-5
Zhou, Y., Zhang, Q., & Li, X. (2020). Numerical investigation of blast induced rock fragmentation. Computers and Geotechnics, 128, 103846. https://doi.org/10.1016/j.compgeo.2020.103846
Zhou, Y., Li, X., & Zhang, Q. (2024). A review of blastability evaluation methods in rock blasting engineering. Rock Mechanics and Rock Engineering. https://doi.org/10.1007/s00603-024-03862-7
Zhou, Z., Chen, C., Cai, X., & Wang, P. (2024). Blastability evaluation for rock mass: Review and new tendency. Bulletin of Engineering Geology and the Environment, 83, 517. https://doi.org/10.1007/s10064-024-04021-0
