ARDC Research Link Australia Research Link Australia   BETA Research
Link
Australia
  • ARDC Newsletter Subscribe
  • Contact Us
  • Home
  • About
  • Feedback
  • Explore Collaborations
  • Researcher
  • Funded Activity
  • Organisation
  • Researcher
  • Funded Activity
  • Organisation
  • Researcher
  • Funded Activity
  • Organisation

Need help searching? View our Search Guide.

Advanced Search

Current Selection
Field of Research : Mining Engineering
Australian State/Territory : SA
Clear All
Filter by Field of Research
Mining Engineering (5)
Resources Engineering and Extractive Metallurgy (3)
Geomechanics and Resources Geotechnical Engineering (2)
Artificial Intelligence and Image Processing (1)
Civil Engineering (1)
Civil Geotechnical Engineering (1)
Computer Vision (1)
Earthquake Engineering (1)
Robotics And Mechatronics (1)
Filter by Socio-Economic Objective
Coal Mining and Extraction (2)
Mining and Extraction of Copper Ores (2)
Application Software Packages (excl. Computer Games) (1)
Geothermal Energy Extraction (1)
Iron Ores (I.E. Ferrous Ores) (1)
Mineral Exploration not elsewhere classified (1)
Mining and Extraction of Iron Ores (1)
Oil Shale and Tar Sands Mining and Extraction (1)
Other (1)
Filter by Funding Provider
Australian Research Council (5)
Filter by Status
Closed (4)
Active (1)
Filter by Scheme
Linkage Projects (4)
Linkage Infrastructure, Equipment and Facilities (1)
Filter by Country
Australia (5)
Filter by Australian State/Territory
SA (5)
VIC (2)
NSW (1)
QLD (1)
WA (1)
  • Researchers (4)
  • Funded Activities (5)
  • Organisations (1)
  • Funded Activity

    Linkage Projects - Grant ID: LP150100539

    Funder
    Australian Research Council
    Funding Amount
    $184,000.00
    Summary
    A new damage model for rock burst in hard rocks during deep mining. This project seeks to develop a new model to predict incipient rock burst in deep mines. Violent sudden energy released during dynamic brittle failure of rocks can kill people and cause serious damages to mining infrastructures. The project aims to investigate formation of micro-fractures on the brittle shear zones during dynamic brittle failure of pristine rocks with a unique experimental methodology under high-pressure-tempera .... A new damage model for rock burst in hard rocks during deep mining. This project seeks to develop a new model to predict incipient rock burst in deep mines. Violent sudden energy released during dynamic brittle failure of rocks can kill people and cause serious damages to mining infrastructures. The project aims to investigate formation of micro-fractures on the brittle shear zones during dynamic brittle failure of pristine rocks with a unique experimental methodology under high-pressure-temperature condition. It is anticipated that a new micromechanics-based damage model for brittle rocks will be developed from this. Implementation of the new coupled thermo-mechanical damage model into a finite element should result in realistic simulation of deep mining operations to identify rock-burst prone areas and allow mining managers to avoid potential hazards.
    Read more Read less
    More information
    Active Funded Activity

    Linkage Projects - Grant ID: LP200100038

    Funder
    Australian Research Council
    Funding Amount
    $516,000.00
    Summary
    A Machine Learning driven flow modelling of fragmented rocks in cave mining. The project aims to develop an integrated method that uses micro scale and macro scale information to predict block scale behaviour so that a better cave mining design can be established. The role of various mineral composition on the energy storage and fracture properties of rocks will be investigated to examine rock fragmentation for block cave mining. Later Machine Learning based models will be developed to establis .... A Machine Learning driven flow modelling of fragmented rocks in cave mining. The project aims to develop an integrated method that uses micro scale and macro scale information to predict block scale behaviour so that a better cave mining design can be established. The role of various mineral composition on the energy storage and fracture properties of rocks will be investigated to examine rock fragmentation for block cave mining. Later Machine Learning based models will be developed to establish various predictive models for Block Scale rock mass behaviour and caveability of ore deposit. Finally, we will develop a new constitutive model based on a dual damage concept that will capture the rock fragmentation and simulate the cave propagation in a large scale mine layout using Smoothed-particle hydrodynamics.
    Read more Read less
    More information
    Funded Activity

    Linkage Infrastructure, Equipment And Facilities - Grant ID: LE150100058

    Funder
    Australian Research Council
    Funding Amount
    $560,000.00
    Summary
    Three dimensionally compressed and monitored Hopkinson bar . 3D compressed and monitored Hopkinson bar: The 3D compressed and monitored Hopkinson bar allows determination of the dynamic mechanical properties and fracturing behaviour of materials under such confinement. Understanding material behaviour under dynamic loading is essential in dealing with many engineering problems as excavation, fragmentation, earthquake, blasting, and structure design. In geotechnical and structure projects, materi .... Three dimensionally compressed and monitored Hopkinson bar . 3D compressed and monitored Hopkinson bar: The 3D compressed and monitored Hopkinson bar allows determination of the dynamic mechanical properties and fracturing behaviour of materials under such confinement. Understanding material behaviour under dynamic loading is essential in dealing with many engineering problems as excavation, fragmentation, earthquake, blasting, and structure design. In geotechnical and structure projects, materials are often subjected to existing confining stresses. The full-field optical techniques, with an ultra-high speed and resolution camera in the system, aims to assist the quantitative measurement of deformation fields including small strain induced in brittle material's failure and identification of constitutive parameters.
    Read more Read less
    More information
    Funded Activity

    Linkage Projects - Grant ID: LP0989780

    Funder
    Australian Research Council
    Funding Amount
    $78,420.00
    Summary
    The study and development of a 3D real-time stockpile management system. By successfully completing this project, the efficiency of existing infrastructure investments in industries involved in bulk material handling (inclusive of minerals, grain, sugar and woodchips) will be largely improved. This will allow such industries to contain costs and thus increase international competitiveness. Efficiencies gains (in these industries) to date have been in recover and processing with little attention .... The study and development of a 3D real-time stockpile management system. By successfully completing this project, the efficiency of existing infrastructure investments in industries involved in bulk material handling (inclusive of minerals, grain, sugar and woodchips) will be largely improved. This will allow such industries to contain costs and thus increase international competitiveness. Efficiencies gains (in these industries) to date have been in recover and processing with little attention to stockyard and movement within the stockyards. The industries sectors in which will receive the greatest benefits are in rural and remote Australia. There is also the ability of the system to be exported to overseas clients, particularly in the mining sector.
    Read more Read less
    More information
    Funded Activity

    Linkage Projects - Grant ID: LP140100946

    Funder
    Australian Research Council
    Funding Amount
    $240,000.00
    Summary
    Visual sensing for localisation and mapping in mining. The creation of high quality survey data is integral to productivity and safety in mining and mining exploration. The current state-of-the-art mine surveying involves scanning from a number of fixed points using laser range-finding equipment (LIDAR). The aim of this project is to develop camera systems and computer vision algorithms to improve the speed and accuracy of this digital mapping of mines, to allow accurate mapping in locations den .... Visual sensing for localisation and mapping in mining. The creation of high quality survey data is integral to productivity and safety in mining and mining exploration. The current state-of-the-art mine surveying involves scanning from a number of fixed points using laser range-finding equipment (LIDAR). The aim of this project is to develop camera systems and computer vision algorithms to improve the speed and accuracy of this digital mapping of mines, to allow accurate mapping in locations denied GPS, and in locations where LIDAR cannot be deployed. The project aims to develop methods to assess these data to detect long-term trends such as shifts in mine drives which may be indicative of stress build-up. The new technology intends to impact both productivity and safety within mining.
    Read more Read less
    More information

    Showing 1-5 of 5 Funded Activites

    Advanced Search

    Advanced search on the Researcher index.

    Advanced search on the Funded Activity index.

    Advanced search on the Organisation index.

    National Collaborative Research Infrastructure Strategy

    The Australian Research Data Commons is enabled by NCRIS.

    ARDC CONNECT NEWSLETTER

    Subscribe to the ARDC Connect Newsletter to keep up-to-date with the latest digital research news, events, resources, career opportunities and more.

    Subscribe

    Quick Links

    • Home
    • About Research Link Australia
    • Product Roadmap
    • Documentation
    • Disclaimer
    • Contact ARDC

    We acknowledge and celebrate the First Australians on whose traditional lands we live and work, and we pay our respects to Elders past, present and emerging.

    Copyright © ARDC. ACN 633 798 857 Terms and Conditions Privacy Policy Accessibility Statement
    Top
    Quick Feedback