Науковий вісник НГУ

Prediction of rock fragmentation in the Boukhadra’s mine conditions

• 
• 

User Rating:  / 0

PoorBest 

Details

Category: Content №5 2024

Last Updated on 29 October 2024

Published on 30 November -0001

Hits: 830

Authors:

L.Bouterfif*, orcid.org/0009-0005-8513-9291, Laboratory of Environment, Mining Institute, Echahid Cheikh Larbi Tebessi University, Tebessa, Algeria; Mining Department,Faculty of Earth Sciences, Badji Mokhtar University, Annaba, Algeria, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

A.Hafsaoui, orcid.org/0000-0002-1720-9527, Laboratory of Natural Resources and Planning, Badji Mokhtar University, Annaba, Algeria

I.Zeriri, orcid.org/0009-0006-5247-8841, Environmental Research Center (C.R.E), Annaba, Algeria

M.Attia, orcid.org/0000-0003-3700-7049, Laboratory of Environment, Mining Institute, Echahid Cheikh Larbi Tebessi University, Tebessa, Algeria

A.Idres, orcid.org/0000-0001-8029-0930, Laboratory of Valorisation of Mining Resources and Environment (LAVAMINE), Badji Mokhtar University, Annaba, Algeria

* Corresponding author e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

повний текст / full article

Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2024, (5): 025 - 029

https://doi.org/10.33271/nvngu/2024-5/025

Abstract:

Purpose. The objective of the study consists in obtaining better quality rock fragmentation by using inclined holes to ensure good energy distribution and better stability of the upper wall.The Kuz-Ram model and the Langefors method are best suited to achieve the goal.

Methodology. The study compares the blasting plan adopted by the Boukhadra mine located in the Wilaya of Tebessa, with that calculated by the Langefors method while using inclined holes. We chose the Kuz-Ram model as a simulation model and validation for the following reasons.

Findings. The application of the proposed method of Langefors gave a satisfactory result in terms of process efficiency, the Kuz-Ram model predicts a significant reduction in the rate of oversized blocks using an inclined hole drilling technique, from 13.1 to 5.3 %. This approach appears to improve the degree of fragmentation, reduce the percentage of oversized blocks and decrease energy loss during blasting.

Originality. Rock fragmentation, which corresponds to the size distribution of fragments of the blasted rock, is one of the most important indices for estimating the effectiveness of blasting works where the size of the fragments of the blasted pile plays an important role in efficient transportation, crushing and grinding.The size of the fragments depends on the characteristics of the rock mass, the type of explosive used, and the drilling and blasting pattern.

Practical value. The use of inclined holes is an important technique to optimize rock fragmentation in open pit mines. The inclination can be adjusted to improve the direction and distribution of blast energy, which contributes to more efficient and uniform fragmentation of extracted rocks.

Keywords: rock, rock jointing, blasting, inclined holes, Tebessa, Algeria

References.

1. Sanchidrián, J. A., & Ouchterlony, F. (2023). Blast-Fragmentation Prediction Derived From the Fragment Size-Energy Fan Concept. Rock Mechanics and Rock Engineering, 56(12), 8869-8889. https://doi.org/10.1007/s00603-023-03496-9.

2. Alipour, A., & Asadizadeh, M. (2023). Prédiction de la taille des fragments de roche à l’aide de la méthode RSM dans le dynamitage en banc: un focus sur les facteurs d’influence et leurs interactions. Arabian Journal of Geosciences, 16(1), 61.

3. Pan, R., Wang, P., Zhou, Z., Lan, R., Chen, L., & Yang, H. Y. (2023). Effects of Confining Stress on Blast-Induced Damage Distribution of Rock with Discontinuity. Sustainability, 15(17), 13278. https://doi.org/10.3390/su151713278.

4. 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(1),747-778. https://doi.org/10.1007/s00603-022-03068-3.

5. Yilmaz, O. (2023). Rock factor prediction in the Kuz–Ram model and burden estimation by mean fragment size. Geomechanics for Energy and the Environment, 33, 100415. https://doi.org/10.1016/j.gete.2022.100415 2352-3808.

6. Jug, J., Strelec, S., Gazdek, M., & Kavur, B. (2017, December). Fragment size distribution of blasted rock mass. IOP Conference series: earth and environmental science,  95(4), 042013. IOP Publishing. https://doi.org/10.1088/1755-1315/95/4/042013.

7. Alipour, A., & Asadizadeh, M. (2023). Prédiction de la taille des fragments de roche à l’aide de RSM en grenaillage au banc: un focus sur les facteurs d’influence et leurs interactions. Arabian Journal of Geosciences, 16, 61. https://doi.org/10.1007/s12517-022-11072-8.

8. Li, E., Yang, F., Ren, M., Zhang, X., Jian Zhou, J., & Khandelwal, M. (2021). Prediction of blasting mean fragment size using support vector regression combined with five optimization algorithms. Journal of Rock Mechanics and Geotechnical Engineering, 13(6). https://doi.org/10.1016/j.jrmge.2021.07.013.

9. Huang, Y., Zhao, Z., Zhang, Z., Zhou, J., Li, H., & Li, Y. (2022). Calculation Method of the Blasting Throwing Energy and Its Variation Affected by the Burden. Applied Sciences, 12(13), 6524. https://doi.org/10.3390/app12136524.

10. Djoudi, M., Bensehamdi, S., & Fredj, M. (2021, August). Study of blasting effect on bench stability. IOP Conference Series: Earth and Environmental Science, 833(1), 012196. IOP Publishing. https://doi.org/10.1088/1755-1315/833/1/012196.

11. Kansake, B. A., Temeng, V. A., & Afum, B. O. (2016). Comparative analysis of rock fragmentation models – a case study. 4 ^th UMaT biennial international mining and mineral conference, (pp. 1-11). https://doi.org/10.13140/RG.2.2.10655.82081.

12. Agyei, G., & Owusu-Tweneboah, M. (2019), A Comparative Analysis of Rock Fragmentation using Blast Prediction Results. Ghana Mining Journal, 19(1), 49-58. https://doi.org/10.4314/gm.v19i1.6.

13. Mutinda, E. K., Alunda, B. O., Maina, D. K., & Kasomo, R. M. (2021). Prediction of rock fragmentation using the Kuznetsov-Cunningham-Ouchterlony model. Journal of the Southern African Institute of Mining and Metallurgy, 121(3), 107-112. https://doi.org/10.17159/2411-9717/1401/2021.

14. Jethro, M. A., Ogbodo, D., & Ajayi, P. (2016). Rock fragmentation prediction using Kuz-Ram model. Journal of Earth & Environment Science, 6(5), 110-115. P.O.Box 110, Ido Ekiti, Ekiti State, Nigeria.

15. Amoako, R., Jha, A., & Zhong, S. (2022). Rock Fragmentation Prediction Using an Artificial Neural Network and Support Vector Regression Hybrid Approach. Mining, 2, 233-2477. https://doi.org/10.3390/mining2020013.

16. Ousmanou, S., Blaise, N. N., & Martial, F. E. (2020). Comparison of the existing and calculated blast design parameters for the rock mass conditions at Bamesso-Latet rock quarry. Journal of Nepal Geological Society, 60, 131-137. https://doi.org/10.3126/jngs.v60i0.31273.

17. Larbi, G., Abderrahmen, B., Ismail, N., & Mohammed-Laid, B. (2012). The Classification Systems as a Tool to Estimate the Stability of Discontinuous Rock Mass ‒ A Numerical Approach: The iron mine of Boukhadra (Algeria) as a case study. EJGE, 17, 419-433.

18. Djellali, A., Laouar, M. S., Saghafi, B., & Houam, A. (2019). Evaluation of cement-stabilized mine tailings as pavement foundation materials. Geotechnical and Geological Engineering, 37, 2811-2822. https://doi.org/10.1007/s10706-018-00796-8.

• < Prev
• Next >