Home Journals Articles Updates About
CN
image
收藏切换
Impact of blast design parameters on rock fragmentation in sub-level caving: A multivariate regression approach
收藏切换
PDF
Ahmadreza Khodayaria, *, Chaoshui Xua, Peter Dare-Bryanb, Peter Dowda, Veljko Lapcevicc, Andrew Metcalfea
Journal of Rock Mechanics and Geotechnical Engineering | 2026, 18(5) : 3348 - 3364
Less
收藏切换
Journal of Rock Mechanics and Geotechnical Engineering | 2026, 18(5): 3348-3364
• Full Length Article •
Impact of blast design parameters on rock fragmentation in sub-level caving: A multivariate regression approach
Full
Ahmadreza Khodayaria, *, Chaoshui Xua, Peter Dare-Bryanb, Peter Dowda, Veljko Lapcevicc, Andrew Metcalfea
Affiliations
  • aSchool of Chemical Engineering, Faculty of Mining Engineering, The University of Adelaide, Adelaide, South Australia, 5000, Australia
  • bOrica, Perth, Western Australia, 6007, Australia
  • cDivision of Mining and Geotechnical Engineering, Luleå University of Technology, Luleå, 971 87, Sweden

    • Ahmadreza (Reza) Khodayari is a PhD candidate in Mining Engineering at the University of Adelaide (since April 2023), focusing on drawpoint and cave operations and fragmentation sensing. He holds a BSc in Mining Engineering from Imam Khomeini International University (2018) and an MSc from Amirkabir University of Technology (2021). His research interests include sublevel-caving blast modelling, gravity flow and fragmentation analysis, fracture mechanics, 3D numerical simulation, and data-driven methods. His recent publications cover topics such as a machine-learning approach to predicting blast-induced fragment size (FRAGBLAST, 2025), sublevel-caving blast modelling (ARMA, 2024), and the impact of explosive-charge misfires on gravity flow (MassMin, 2024).

Published: 2026-05-25 doi: 10.1016/j.jrmge.2025.07.038
Outline
收藏切换

Sub-level caving (SLC) is a mass mining method suitable for large, steeply dipping orebodies. The particle size distribution (PSD) of blasted material affects material flow through the stope. Improving blast-induced fragmentation can enhance draw point extraction, increasing ore recovery, reducing dilution, and lowering costs in loading and crushing. Numerical simulations using the Mechanistic Blasting Model (MBM) explored these improvements. MBM simulates the explosive loading, rock fracturing, and dynamic explosive gas effects. It addresses uneven explosive distribution from fan-shaped blast holes and complex broken ground conditions. The simulations used Ernest Henry Mine (EHM) data to define the baseline blast design and rock mass and compared field and modelled fragmentation sizes for varying explosive densities and burden sizes. Then, MBM simulations incorporated different rock mass fracture densities, tensile strengths and in-situ stresses, and further blast design changes in the blasthole diameter and charge spacings. A total of 34 scenarios were modelled. Multivariate regression analysis identified key parameters, and new regression models for P20, P50, and P80 passing sizes were developed and validated against the EHM and MBM simulation data. Additional simulations confirmed that while regression predictive models were slightly less accurate, they provided efficient predictions with acceptable accuracy.

Sublevel caving  /  Mechanistic blast model  /  Ernest Henry mine  /  Multivariate regression analysis  /  Particle size distribution
Ahmadreza Khodayari, Chaoshui Xu, Peter Dare-Bryan, Peter Dowd, Veljko Lapcevic, Andrew Metcalfe. Impact of blast design parameters on rock fragmentation in sub-level caving: A multivariate regression approach[J]. Journal of Rock Mechanics and Geotechnical Engineering, 2026 , 18 (5) : 3348 -3364 . DOI: 10.1016/j.jrmge.2025.07.038
Full Text
Less
Funding
Less
  • Australian Research Council Integrated Operations for Complex Resources Industrial Transformation Training Centre(IC190100017)
Appendix
Less
Year 2026 volume 18 Issue 5
PDF
2
0
Cite this Article
BibTeX
Article Info
doi: 10.1016/j.jrmge.2025.07.038
  • Receive Date：2025-01-20
  • Online Date：2026-06-17
  • Published：2026-05-25
Article Data
Affiliations
History
  • Received：2025-01-20
  • Revised：2025-07-30
  • Accepted：2025-07-30
Funding
Australian Research Council Integrated Operations for Complex Resources Industrial Transformation Training Centre(IC190100017)
Affiliations
    aSchool of Chemical Engineering, Faculty of Mining Engineering, The University of Adelaide, Adelaide, South Australia, 5000, Australia
    bOrica, Perth, Western Australia, 6007, Australia
    cDivision of Mining and Geotechnical Engineering, Luleå University of Technology, Luleå, 971 87, Sweden

Corresponding:

* Corresponding author. E-mail address: (A. Khodayari).
References
Share
https://castjournals.cast.org.cn/joweb/jrmge/EN/10.1016/j.jrmge.2025.07.038
Share to
QR

Scan QR to access full text

Cite this article
BibTeX
Citations
表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
关闭全屏
  • BibTeX
  • EndNote
  • RefWorks
  • TxT
Links
Articles
Latest Articles
Most Read
Collections
Updates
Events
News
Multimedia
About
About Us
Contact
No. 86 Xueyuan South Road, Haidian District, Beijing
100081
010-62199257
qkjq@cast.org.cn

Copyright © 2025 China Association for Science and Technology. All rights reserved. For all open access content, the relevant licensing terms apply.
Sponsored by the Office of the Leading Group for Cybersecurity and Informatization of CAST, and supported by Science and Technology Review Publishing House