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Development of a predictive tool for material wear using experiment and coupled SPH and DEM simulation

  • Full or part time
  • Application Deadline
    Thursday, March 07, 2019
  • Funded PhD Project (Students Worldwide)
    Funded PhD Project (Students Worldwide)

Project Description

The project is in line with areas of national strategic growth, particularly in the resources sector, namely mining equipment, technology and services (METS), and oil, gas and energy resources (OG&E). In these severe operating environments, the service life of equipment and components is very limited, particularly because of wear. A thorough understanding of the wear mechanisms and the development of modelling capability to predict service performance would help to improve the design, reduce the operating costs and increase the reliability of the equipment.

The proposal is linked to the mineAlloy Industrial Transformation Training Centre, which aims to train scientists and engineers in transforming Australia into a producer of world-class equipment and wear resistant components. The new damage model implemented in the SPH solver, accompanied by the DEM capability, is expected to help scientists and engineers better predict the wear performance of equipment and components in service. The knowledge and capabilities developed would add considerable value to the reputation of the Parties and their world-class research positions. The commercial potential of resulting improved predictive models of wear could be explored with the industry partners of the mineAlloy ITTC as well as across the METS and OG&E sectors. This research is partially funded by the Australian Government through the Australian Research Council. This PhD position is dependent on the award of a DUCA scholarship from Data61, CSIRO. As part of this project the successful applicant will have to conduct research at CSIRO in Clayton.

Funding Notes

3 Year Scholarship
$27,082/year tax exempt (2019 rate)
International students: Tuition fee and overseas health coverage for 4 years
• Numerical Modelling and Analysis of Partial Differential Equations and/or Ordinary Differential Equations
• Some experience in F90 and/or C++ programming languages
• Ability to plan and conduct laboratory experiments and analyse data
• Good oral, written, presentation skills

• Good operating knowledge of Linux
• Background knowledge of SPH/FEM and DEM
• Background knowledge of material plasticity and damage models
• Experience combining experimental outputs for validating simulation predictions and understanding physical process mechanisms

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