A review of development of better prediction equations for blast fragmentation

Ouchterlony, Finn; Sanchidrián, José A.

doi:10.1016/j.jrmge.2019.03.001

Cited by 59 publications

(39 citation statements)

References 23 publications

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“…In cases where there are too many boulders, the mine operator will be faced with the need for secondary blasting, which will have unnecessary negative consequences for the company's cash flow. It also poses safety issues due to the increased risk of flyrock and air blast hazard because of the light stemming employed in secondary blasting (Abuhasel, 2019;Ouchterlony and Sanchidrián, 2019).…”

Section: Introductionmentioning

confidence: 99%

“…The two most recent empirical fragmentation models were introduced in 2005 and both have undergone subsequent modification to better predict the size of rock fragments and minimize the occurrence of boulders. These are the KCO (Cunningham, 2005) and Modified Kuz-Ram models (Ouchterlony and Sanchidrián, 2019), and were developed to overcome the shortcomings of the Kuz-Ram model (Ouchterlony and Sanchidrián, 2019). One of the reasons for the KCO model's superiority to the other empirical models is the fact that the required input parameters are comparatively simple to obtain and apply in fragment size prediction.…”

Section: Introductionmentioning

confidence: 99%

“…However, building these techniques to a level such that they can accommodate the blast design variables as well as quantify the influence of inherent rock properties on the blast outcome is tiresome, time-consuming, and also expensive. On the other hand, secondary blasting due to the production of large boulders increases the cost and time required before any further size reduction can take place (Ouchterlony and Sanchidrián, 2019). Therefore, this research is focused on determining the possibility of applying the KCO model for predicting blast fragment size distribution in two limestone quarries in Kenya.…”

Section: Introductionmentioning

confidence: 99%

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Prediction of rock fragmentation using the Kuznetsov-Cunningham-Ouchterlony model

Mutinda

Alunda

Maina

et al. 2021

J. S. Afr. Inst. Min. Metall.

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SYNOPSIS Assessment of blast fragment size distribution is critical in mining operations because it is the initial step towards mineral extraction. Different empirical models and techniques are available for predicting and investigating the consequences of blasting, one of which is the Kuznetsov-Cunningham-Ouchterlony (KCO) model. In this paper we summarize the advances in the empirical models from inception until now, and explore the improvements that have been made so far with particular emphasis is on the most recent KCO model. Utilization of the model and the errors that arise between expected and the actual outcomes are analysed. The results indicate that the KCO model remains useful for predicting the blast fragmentation at limestone mine sites, despite the availability of other advanced prediction models. It is also a valuable instrument for pre-surveying the impact of varying certain parameters of a blast plan. Keywords: blasting, rock fragmentation, modelling, prediction.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Prediction of rock fragmentation using the Kuznetsov-Cunningham-Ouchterlony model

Mutinda

Alunda

Maina

et al. 2021

J. S. Afr. Inst. Min. Metall.

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“…The mineral concentration, hardness, strength and toughness of the ore body is partially known in advance, from exploratory drilling, and stored in a block model [6]. These are input parameters to many models for blasting [7], crushing [8] or grinding [9], such as the Kuz-Ram blasting and JKMRC grinding models. Measurement-while-drilling (MWD) of blast holes produces data that contain information about the geo-mechanical properties at higher spatial resolution than the exploration data.…”

Section: Introductionmentioning

confidence: 99%

Digital Twins with Distributed Particle Simulation for Mine-to-Mill Material Tracking

2021

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Systems for transport and processing of granular media are challenging to analyse, operate and optimise. In the mining and mineral processing industries, these systems are chains of processes with a complex interplay among the equipment, control and processed material. The material properties have natural variations that are usually only known at certain locations. Therefore, we explored a material-oriented approach to digital twins with a particle representation of the granular media. In digital form, the material is treated as pseudo-particles, each representing a large collection of real particles of various sizes, shapes and mineral properties. Movements and changes in the state of the material are determined by the combined data from control systems, sensors, vehicle telematics and simulation models at locations where no real sensors could see. The particle-based representation enables material tracking along the chain of processes. Each digital particle can act as a carrier of observational data generated by the equipment as it interacts with the real material. This make it possible to better learn the material properties from process observations and to predict the effect on downstream processes. We tested the technique on a mining simulator and demonstrated the analysis that can be performed using data from cross-system material tracking.

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“…Finer fragmentation due to additional blast energy leads to increased throughput and creates extra value from additional revenue by relieving constraints in the plant (Kanchibotla et al 1998). Detailed comparisons of fragmentation modelling cannot be provided here and further information including comparisons with new approaches such as the distribution-free model for the prediction of fragmentation for mine-to-mill optimisation can be seen in the relevant literature (Ouchterlony & Sanchidrián 2019;Sanchidrián et al 2012Sanchidrián et al , 2014.…”

Section: Introductionmentioning

confidence: 99%

Breaking new ground: challenges and opportunities for maximising value from underground blasting

Sellers¹,

Salmi²

2020

Proceedings of the Second International Conference on Underground Mining Technology

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The challenges of underground mining operations have discouraged mine-to-mill value optimisation to maximise metal production by tailoring fragmentation for plant throughput. Improved and automated blasting techniques are required for modern remote, deeper, and highly stressed operations. The definition of value is changing with investors seeking environmental, social, and governance measures, as well as the traditional revenue and net present value approaches. In this paper, analyses of blasting from a range of underground operations are used to highlight the current challenges. Demonstration of how the lack of sufficient and appropriate continuous, 3D measurement of important properties such as blastability, in situ structures, hole deviation, and fragmentation aligned with the limited insights into the effect of mining-induced stresses show how current approaches can often lead to overbreak, dilution, production delays, the lack of excavation stability, and poor plant performance. The real-time fusion of data to recalibrate and monitor the continuously changing environment is required. On the horizon, there is a suite of new technologies such as wireless detonators, nitrate-free explosives, robotic operations, and cognitive spatial management that will enable a new generation of mining methods. These include in-place operations and in-mine recovery where the material movement and the environmental footprint of mining operations is reduced whilst extraction is optimised, and productivity and excavation stability increased.

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A review of development of better prediction equations for blast fragmentation

Cited by 59 publications

References 23 publications

Prediction of rock fragmentation using the Kuznetsov-Cunningham-Ouchterlony model

Prediction of rock fragmentation using the Kuznetsov-Cunningham-Ouchterlony model

Digital Twins with Distributed Particle Simulation for Mine-to-Mill Material Tracking

Breaking new ground: challenges and opportunities for maximising value from underground blasting

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