ORCID Profile
0000-0003-3544-5897
Current Organisation
CSIRO
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Civil Engineering | Civil Geotechnical Engineering | Geomechanics and Resources Geotechnical Engineering |
Primary Mining and Extraction of Mineral Resources not elsewhere classified | Mining and Extraction of Energy Resources not elsewhere classified | Civil Construction Design
Publisher: Springer Science and Business Media LLC
Date: 22-12-2017
Publisher: Elsevier BV
Date: 12-2015
Publisher: Elsevier BV
Date: 08-2017
Publisher: Copernicus GmbH
Date: 28-05-2018
DOI: 10.5194/ISPRS-ANNALS-IV-2-17-2018
Abstract: Abstract. Estimation of rock breakage characteristics plays an important role in optimising various industrial and mining processes used for rock comminution. Although little research has been undertaken into 3D photogrammetric measurement of the progeny kinematics, there is promising potential to improve the efficacy of rock breakage characterisation. In this study, the observation of progeny kinematics was conducted using a high speed, stereo videometric system based on laboratory experiments with a drop weight impact testing system. By manually tracking in idual progeny through the captured video sequences, observed progeny coordinates can be used to determine 3D trajectories and velocities, supporting the idea that high speed video can be used for rock breakage characterisation purposes. An analysis of the results showed that the high speed videometric system successfully observed progeny trajectories and showed clear projection of the progeny away from the impact location. Velocities of the progeny could also be determined based on the trajectories and the video frame rate. These results were obtained despite the limitations of the photogrammetric system and experiment processes observed in this study. Accordingly there is sufficient evidence to conclude that high speed videometric systems are capable of observing progeny kinematics from drop weight impact tests. With further optimisation of the systems and processes used, there is potential for improving the efficacy of rock breakage characterisation from measurements with high speed videometric systems.
Publisher: Informa UK Limited
Date: 03-07-2015
Publisher: Elsevier BV
Date: 05-2012
Publisher: American Physical Society (APS)
Date: 05-08-2020
Publisher: Springer Science and Business Media LLC
Date: 30-09-2018
Publisher: Elsevier BV
Date: 09-2013
Publisher: Elsevier BV
Date: 02-2017
Publisher: Springer Science and Business Media LLC
Date: 23-08-2012
Publisher: Springer Science and Business Media LLC
Date: 10-04-2014
Publisher: Springer Science and Business Media LLC
Date: 09-04-2014
Publisher: MDPI AG
Date: 15-04-2020
Abstract: Slope stability monitoring in open cut mining is increasingly based on the use of a variety of different sensors and associated analytics, each capable of providing part of the understanding required to manage complex geotechnical environments. Designing an integrated monitoring system that is both attainable and fit for purpose can therefore be particularly challenging. In this paper, a systems engineering approach based on a novel methodology is presented to design the slope monitoring system. The methodology uses the rock engineering systems (RES) approach to system decomposition for geotechnical engineering problems, to determine the critical rock mass behaviours requiring monitoring. It follows this with the application of the system theoretic process analysis (STPA) approach, to design the control system for the monitoring system and identify and mitigate sub-optimal configurations. We demonstrate that the approach is practical to implement and supports transparent and defensible decision making for designing and implementing slope monitor systems. We apply the method to the design of a monitoring system for an Australian coal mine and demonstrate how the approach can facilitate the identification and design of new sensing modalities.
Publisher: MDPI AG
Date: 09-11-2021
Abstract: Geotechnical complexity in mining often leads to geotechnical uncertainty which impacts both safety and productivity. However, as mining progresses, particularly for strip mining operations, a body of knowledge is acquired which reduces this uncertainty and can potentially be used by mining engineers to improve the prediction of future mining conditions. In this paper, we describe a new method to support this approach based on modelling and neural networks. A high-level causal model of the mining operations based on historical data for a number of parameters was constructed which accounted for parameter interactions, including hydrogeological conditions, weather, and prior operations. An artificial neural network was then trained on this historical data, including production data. The network can then be used to predict future production based on presently observed mining conditions as mining proceeds and compared with the model predictions. Agreement with the predictions indicates confidence that the neural network predictions are properly supported by the newly available data. The efficacy of this approach is demonstrated using semi-synthetic data based on an actual mine.
Publisher: Australian Centre for Geomechanics, Perth
Date: 2021
Publisher: Elsevier BV
Date: 12-2015
Publisher: Elsevier BV
Date: 06-2016
Publisher: Springer Science and Business Media LLC
Date: 06-02-2015
Publisher: Elsevier BV
Date: 2017
Publisher: MDPI AG
Date: 04-03-2020
Abstract: Digital mining is a broad term describing the enhancement of the physical mining method through the use of digital models, simulations, analytics, controls and associated feedbacks. Mining optimisation will be improved through increased digitisation and real-time interactions via a “digital twin”, however digitisation of the rock mass component of this system remains problematic. While engineered systems can be digitally twinned, natural systems containing inherent uncertainties present challenges, especially where human-intensive procedures are required. This is further complicated, since the mining system is designed not only to interact with, but to substantially and continually alter its surrounding environment. Considering digital twin requirements and geological modelling capabilities, we assess the potential for a mine’s synchronised digital twin to encompass the complex, uncertain, geological domain within which it interacts. We find that current geological (and indeed hydro-geological) models and simulations would support digitisation that could be considered to provide, at best, a digitised ‘cousin’. Based on this assessment, the digital twin’s value for medium term forecasting of mining operations may be limited and we discuss technological advancements that can mitigate this.
Location: Australia
Start Date: 05-2022
End Date: 05-2025
Amount: $453,000.00
Funder: Australian Research Council
View Funded Activity