Науковий вісник НГУ

Optimal parameters of blasting destruction in the Ben Azouz quarry based on study of strength limestone rock

• 
• 

User Rating:  / 0

PoorBest 

Details

Category: Content №3 2024

Last Updated on 28 June 2024

Published on 30 November -0001

Hits: 74

Authors:

H.Mahtali*, orcid.org/0009-0006-6787-496X, Department of Mining, Metallurgy and Materials Engineering of National Higher School of Technology and Engineering, Annaba, Algeria; Mining, Metallurgy and Materials Laboratory “L3M” National Higher School of Technology and Engineering, Annaba, Algeria; Mining Department, 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, Mining Department, Badji Mokhtar University, Annaba, Algeria

Z.Mezdoud, orcid.org/0009-0004-8569-7333, Mathematic Department, Badji Mokhtar University, Annaba, Algeria; Laboratory of Probabilities and Statistics “LAPS”, Badji Mokhtar University, Annaba, Algeria

A.Bouslama, orcid.org/0009-0004-5218-7708, Architecture Department, Badji Mokhtar University, Annaba, Algeria

A.Idres, orcid.org/0000-0001-8029-0930, Mining Department, 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, (3): 012 - 018

https://doi.org/10.33271/nvngu/2024-3/012

Abstract:

Purpose. This paper highlights the importance of taking into account the evaluation of the strength properties of limestone rock in the Ben Azzouz quarry. The purpose is to achieve optimum blasting quality based on the information on petro-physical and mechanical characteristics of the rock.

Methodology. Models have been developed to estimate physico-mechanical properties of limestone rock. The models are based on the results of many laboratory tests by petro-physical and mechanical methods. Statistical analysis was performed on simple and multiple regression equations.

Findings. Linear regression models have a higher estimated success rate, as expected. The best model for estimating the compressive strength of the rock (UCS, Uniaxial Compression Strength) based on simple regression is the model containing P-Velocity as an independent variable with a coefficient of determination R² of 0.81 and P-value = 0.000000003.

Originality. To benefit from the enormous reserves in the quarry of Ben Azouz, knowing that there is no evaluation of the physico-mechanical characteristics of the rock, a set of the tests in the rock mechanics laboratory of polytechnic faculty of Mons in Belgium was carried out and limestone rock strength was estimated.

Practical value. to Solid understanding of the physical and mechanical characteristics of the rock mass and the mechanism of blasting the rock is an essential step that must be taken gradually according to the development of mining works with the aim of minimizing the disadvantages in blasting and obtaining an optimal effectiveness.

Keywords: Ben Azouz quarry, Algeria, Uniaxial Compressive Strength, multiple regression, blasting destruction, punching resistance

References.

1. Hu, H., Lu, W., Yan, P., Chen, M., Gao, Q., & Yang, Z. (2020). A new horizontal rock dam foundation blasting technique with a shock-reflection device arranged at the bottom of vertical borehole. European Journal of Environmental and Civil Engineering, 24(4), 481-499. https://doi.org/10.1080/19648189.2017.1399168.

2. Wang, J., Yin, Y., & Esmaieli, K. (2018). Numerical simulations of rock blasting damage based on laboratory-scale experiments. Journal of Geophysics and Engineering, 15(6), 2399-2417. https://doi.org/10.1088/1742-2140/aacf17.

3. Chouaf, I., Lamouri, B., Bouabsa, L., Chouabbi, A., & Fagel, N. (2018). Caractérisation minéralogique et physico-chimique des formations argileuses sous numidienne de la région d’Azzaba (NE Algérie). Courrier du savoir, 621-632.

4. Rezaei, M., Davoodi, P. K., & Najmoddini, I. (2019). Studying the correlation of rock properties with P-wave velocity index in dry and saturated conditions. Journal of Applied Geophysics, 169, 49-57. https://doi.org/10.1016/j.jappgeo.2019.04.017.

5. Anastasio, S., Fortes, A. P. P., Kuznetsova, E., & Danielsen, S. W. (2016). Relevant petrological properties and their repercussions on the final use of aggregates. Energy Procedia, 97, 546-553. https://doi.org/10.1016/j.egypro.2016.10.073.

6. Stan-Kłeczek, I., & Idziak, A. F. (2017). The changes of P-wave velocity of rock samples over time. Procedia engineering, 191, 483-487. https://doi.org/10.1016/j.proeng.2017.05.207.

7. Aladejare, A. E. (2021). Characterization of the petrographic and physicomechanical properties of rocks from Otanmäki, Finland. Geotechnical and Geological Engineering, 39(3), 2609-2621. https://doi.org/10.1007/s10706-020-01648-0.

8. El-Aal, A. A., Zakhera, M., Al Saiari, M., & Tolba, A. (2021). Determination of the geomechanical and chemical properties of carbonate rocks along Najran, Sharourah District, Saudi Arabia: implications for construction and industrial purposes. Arabian Journal of Geosciences, 14(17), 1694. https://doi.org/10.1007/s12517-021-08135-7.

9. Aydin, A. (2014). Upgraded ISRM Suggested Method for Determining Sound Velocity by Ultrasonic Pulse Transmission Technique. Rock Mechanics and Rock Engineering, 47(1), 255-259. https://doi.org/10.1007/s00603-013-0454-z.

10. De Micheaux, P. L., Drouilhet, R., & Liquet, B. (2014). Présentation du logiciel R. In Le logiciel R. collection statistique et probabilités appliquées, (pp. 1-29). Springer, Paris. https://doi.org/10.1007/978-2-8178-0535-1_1.

11. Castro-Filgueira, U., Alejano, L. R., Arzúa, J., & Ivars, D. M. (2017). Sensitivity Analysis of the Micro-Parameters Used in a PFC Analysis Towards the Mechanical Properties of Rocks. Procedia Engineering, 191, 488-495. Elsevier. https://doi.org/10.1016/j.proeng.2017.05.208.

12. Briševac, Z., Hrženjak, P., & Buljan, R. (2016). Models for estimating uniaxial compressive strength and elastic modulus. Građevinar, 68(01), 19-28. https://doi.org/10.14256/JCE.1431.2015.

13. Aladejare, A. E., Akeju, V. O., & Wang, Y. (2022). Data-driven characterization of the correlation between uniaxial compressive strength and Youngs’ modulus of rock without regression models. Transportation Geotechnics, 32, 100680. https://doi.org/10.1016/j.trgeo.2021.100680.

• < Prev
• Next >