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Status : Active
Research Topic : Mining Soils
Field of Research : Mechanical Engineering
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  • Researchers (45)
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  • Active Funded Activity

    Linkage Projects - Grant ID: LP210301054

    Funder
    Australian Research Council
    Funding Amount
    $240,000.00
    Summary
    Innovative metamaterial magnetorheological technology for mining machines. Hard-rock mining machines have been identified as the next generation mining technology, which will finally replace the traditional drill and blast method to increase productivity and mitigate dangerous working conditions. This project aims to develop innovative metamaterial magnetorheological elastomer joints for a typical hard-rock mining machine to improve the mining efficiency by reducing the vibration. The findings a .... Innovative metamaterial magnetorheological technology for mining machines. Hard-rock mining machines have been identified as the next generation mining technology, which will finally replace the traditional drill and blast method to increase productivity and mitigate dangerous working conditions. This project aims to develop innovative metamaterial magnetorheological elastomer joints for a typical hard-rock mining machine to improve the mining efficiency by reducing the vibration. The findings and outcomes of this research will advance the knowledge and practice of hard-rock mining machines in Australia. The success of this project will significantly increase mining productivity and reduce human injury
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    Active Funded Activity

    Discovery Projects - Grant ID: DP190103231

    Funder
    Australian Research Council
    Funding Amount
    $309,934.00
    Summary
    Cepstral methods of operational modal analysis to separate multiple sources. This project aims to develop new methods of operational modal analysis in situations with multiple complex sources, such as rotating machines. The project will obtain scaled mode shapes as well as separated scaled sources. One of the main applications will be to improve the prognostics of machines by having separated scaled estimates of the forcing functions to make it easier to find fault parameters which trend monoton .... Cepstral methods of operational modal analysis to separate multiple sources. This project aims to develop new methods of operational modal analysis in situations with multiple complex sources, such as rotating machines. The project will obtain scaled mode shapes as well as separated scaled sources. One of the main applications will be to improve the prognostics of machines by having separated scaled estimates of the forcing functions to make it easier to find fault parameters which trend monotonically towards failure, and thus greatly improve the estimates of remaining useful equipment life. An additional benefit of the application will be the ability to predict overall noise radiation from a machine or object if both the sources and modal models are scaled.
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    Active Funded Activity

    Linkage Projects - Grant ID: LP190100378

    Funder
    Australian Research Council
    Funding Amount
    $545,000.00
    Summary
    Deep Learning Augmented Intelligent Grinding Mill Simulation and Design. Comminution is a key operation in mineral processing that utilises grinding mills to reduce the size of ore for further mineral enrichment processing. The aim of this project is to provide a step change improvement in the operational efficiency and service life of grinding mills through the development of advanced numerical models to simulate the grinding mill process. The outcome will be a hierarchical deep learning progra .... Deep Learning Augmented Intelligent Grinding Mill Simulation and Design. Comminution is a key operation in mineral processing that utilises grinding mills to reduce the size of ore for further mineral enrichment processing. The aim of this project is to provide a step change improvement in the operational efficiency and service life of grinding mills through the development of advanced numerical models to simulate the grinding mill process. The outcome will be a hierarchical deep learning program to select optimal model parameters from which computational algorithms will optimise grinding mill geometries. This research project will deliver substantial improvements to equipment used to process our most valuable exports and result in immediate industry impact.
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