JOURNAL OF ROCK MECHANICS

JOURNAL OF ROCK MECHANICS

Optimizing Blast-Induced Ground Vibration Reduction Using an Integrated ANN-EOA Model: A Case Study of Sarcheshmeh Copper Mine

Document Type : ٍAn English Original Article

Author
Exploitation Division, Faculty of Mining and Materials, Tarbiat Modares University
Abstract
Blast-induced ground vibrations pose significant environmental and safety challenges in open-pit mining operations, particularly in geologically complex areas. This study develops an integrated Artificial Neural Network-Equilibrium Optimizer Algorithm (ANN-EOA) model to predict and optimize blast-induced ground vibrations specifically for the Sarcheshmeh copper mine's sensitive western wall. The ANN model demonstrated exceptional predictive accuracy (R² = 0.96) in forecasting Peak Particle Velocity (PPV) based on seven key blasting parameters. The EOA then successfully identified an optimal blasting configuration that predicts a 34% reduction in PPV to 6.72 mm/s, achieved through optimized burden (6m), spacing (7m), delay time (50ms), and charge parameters. This research bridges a critical gap between generalized AI models and site-specific applications, providing both a practical solution for vibration mitigation at Sarcheshmeh and a transferable methodology that advances the integration of computational intelligence with mining engineering challenges. The findings underscore the importance of accounting for specific geological conditions in blast optimization while highlighting the need for field validation as the essential next step.
Keywords
Subjects

[1]
M. Rezakhah and E. Moreno, "Open pit mine scheduling model considering blending and stockpiling," in Proceedings of the 28th International Symposium on Mine Planning and Equipment Selection - MPES 2019, Perth, 2019.
[2]
M. Rezakhah, "Short-Term Production Planning Optimization in Open-Pit Copper Mines A MILP Model Integrating Comminution Modeling and Feed Quality Control," Journal of Mining and Environment, 2025.
[3]
M. Monjezi, S. Moezinia, J. K. Hamidi, M. Rezakhah, V. Amini and A. Batarbiat, "Determining the Appropriate Rehabilitation Method in Open-Pit Mines using Decision-Making Methods," Journal of Mining and Environment, 2025.
[4]
S. Khajevand, Rezakhah, M. M. M. and F. A. Manríquez León, "Enhancing Transportation Fleet Efficiency in Open-Pit Mining via Simulation: a Case Study," Journal of Mining and Environment, vol. 16, no. 3, pp. 997-1007, 2025.
[5]
M. Mirzehi Kalateh Kazemi, Z. Nabavi, M. Rezakhah and A. Masoudi, "Application of XGB-based metaheuristic techniques for prediction time-to-failure of mining machinery," Systems and Soft Computing, vol. 5, p. 200061, 1 12 2023.
[6]
M. Mirzehi, M. Rezakhah, A. Mousavi and Z. Nabavi, "New MIP model for short-term planning in open-pit mines considering loading machine performance: a case study in Iran," International Journal of Mining and Mineral Engineering, pp. 341-364, 2023.
[7]
E. Moreno, F. Ferreira, M. Goycoolea, D. Espinoza, A. Newman and M. Rezakhah, "Linear programming approximations for modeling instant-mixing stockpiles," Application of computers and operations research in the mineral industry-proceedings of the 37th international symposium, APCOM, vol. 2009, pp. 582-587, 2015.
[8]
S. Tajik, M. Monjezi, M. Rezakhah and M. Amiri Hosseini, "Development of a Mathematical Model for Predicting Blast-Induced Fragmentation Considering Elastic Wave Velocities," JOURNAL OF ROCK MECHANICS, vol. 7, no. 2, pp. 71-82, 2023.
[9]
Y. Yan, X. Hou and H. Fei, "Review of predicting the blast-induced ground vibrations to reduce impacts on ambient urban communities," Journal of cleaner production, vol. 260, p. 121135, 2020.
[10]
A. Al-Bakri and M. Sazid, "Application of Artificial Neural Network (ANN) for Prediction and Optimization of Blast-Induced Impacts," Mining , vol. 1, pp. 315-334, 2021.
[11]
K. Behzadafshar, F. Mohebbi, M. Soltani Tehrani, M. Hasanipanah and O. Tabrizi, "Predicting the ground vibration induced by mine blasting using imperialist competitive algorithm," Engineering Computations, vol. 35, no. 4, pp. 1774-1787, 2018.
[12]
D. Mohammadi, R. Mikaeil and J. Abdollahi‐Sharif, "Implementation of an optimized binary classification by GMDH-type neural network algorithm for predicting the blast produced ground vibration," Expert Systems, vol. 37, no. 5, p. e12563, 2020.
[13]
H. Nguyen, X. N. Bui and E. Topal, "Enhancing predictions of blast-induced ground vibration in open-pit mines: Comparing swarm-based optimization algorithms to optimize self-organizing neural networks," International Journal of Coal Geology, vol. 275, p. 104294, 2023.
[14]
D. J. Armaghani, E. Momeni, S. V. A. N. K. Abad and M. Khandelwal, "Feasibility of ANFIS model for prediction of ground vibrations resulting from quarry blasting," Environmental earth sciences, vol. 74, no. 4, pp. 2845-2860, 2015.
[15]
R. Shirani Faradonbeh, D. Jahed Armaghani, M. Z. Abd Majid, M. Md Tahir, B. Ramesh Murlidhar, M. Monjezi and H. M. Wong, "Prediction of ground vibration due to quarry blasting based on gene expression programming: a new model for peak particle velocity prediction," International journal of environmental science and technology, vol. 13, no. 6, pp. 1453-1464, 2016.
[16]
S. Hosseini, J. Khatti, B. Taiwo, Y. Fissha, K. Grover, H. Ikeda, M. Pushkarna, M. Berhanu and M. Ali, "Assessment of the ground vibration during blasting in mining projects using different computational approaches," Scientific Reports, vol. 13, no. 1, p. 18582, 2023.
[17]
Y. Fissha, H. Ikeda, H. Toriya, N. Owada, T. Adachi and Y. Kawamura, "Evaluation and Prediction of Blast-Induced Ground Vibrations: A Gaussian Process Regression (GPR) Approach," Mining, vol. 3, pp. 659-682, 2023.
[18]
X. N. Bui, P. Jaroonpattanapong, H. Nguyen, Q. H. Tran and N. Q. Long, "A novel hybrid model for predicting blast-induced ground vibration based on k-nearest neighbors and particle swarm optimization," Scientific reports, vol. 9, no. 1, p. 13971, 2019.
[19]
D. Mohammadi, R. Mikaeil and J. Abdollahei Sharif, "Investigating and ranking blasting patterns to reduce ground vibration using soft computing approaches and MCDM technique," Journal of Mining and Environment, vol. 11, no. 3, pp. 881-897, 2020.
[20]
P. Bayat, M. Monjezi, A. Mehrdanesh and M. Khandelwal, "Blasting pattern optimization using gene expression programming and grasshopper optimization algorithm to minimise blast-induced ground vibrations," Engineering with Computers, vol. 38, no. 4, pp. 3341-3350, 2022.
[21]
A. Rezaeineshat, M. Monjezi, A. Mehrdanesh and M. Khandelwal, "Optimization of blasting design in open pit limestone mines with the aim of reducing ground vibration using robust techniques," Geomechanics and Geophysics for Geo-Energy and Geo-Resources, vol. 6, no. 2, p. 40, 2020.
[22]
E. Bakhtavar, J. Abdollahisharif and M. Ahmadi, "Reduction of the undesirable bench-blasting consequences with emphasis on ground vibration using a developed multi-objective stochastic programming," International Journal of Mining, Reclamation and Environment, vol. 31, no. 5, pp. 333-345, 2017.
[23]
R. Bhatawdekar, R. Kumar, M. Sabri Sabri, B. Roy, E. Mohamad, D. Kumar and S. Kwon, "Estimating Flyrock Distance Induced Due to Mine Blasting by Extreme Learning Machine Coupled with an Equilibrium Optimizer," Sustainability, vol. 15, p. 3265, 2023.
[24]
B. Elevli and E. Arpaz, "Evaluation of parameters affected on the blast induced ground vibration (BIGV) by using relation diagram method (RDM)," Acta Montanistica Slovaca, vol. 15, no. 4, p. 261, 2010.
[25]
C. K. Arthur, V. A. Temeng and Y. Y. Ziggah, "A Self-adaptive differential evolutionary extreme learning machine (SaDE-ELM): a novel approach to blast-induced ground vibration prediction," SN Applied Sciences, vol. 2, no. 11, p. 1845, 2020.
[26]
Y. Zhang, H. He, M. Khandelwal, K. Du and J. Zhou, "Knowledge mapping of research progress in blast-induced ground vibration from 1990 to 2022 using CiteSpace-based scientometric analysis," Environmental Science and Pollution Research, vol. 40, no. 47, pp. 103534-103555, 2023.
[27]
J. Zhou, Y. Zhang and Y. Qiu, "State-of-the-art review of machine learning and optimization algorithms applications in environmental effects of blasting," Artificial Intelligence Review, vol. 57, no. 1, p. 5, 2024.
[28]
K. Iwano, K. Hashiba, J. Nagae and K. Fukui, "Reduction of tunnel blasting induced ground vibrations using advanced electronic detonators," Tunnelling and Underground Space Technology, vol. 105, p. 103556, 2020.
[29]
A. Faramarzi, M. Heidarinejad, B. Stephens and S. Mirjalili, "Equilibrium optimizer: A novel optimization algorithm," Knowledge-based systems, vol. 191, p. 105190, 2020.
[30]
M. Monjezi, K. Goshtasbi, M. Rezakhah and T. N. Singh, "Design of stable slopes for Songun copper mine," Mining Technology, vol. 116, no. 3, pp. 146-152, 2007.