Summer and Winter Research Programs for Undergraduates

Project title:

Data capture and mapping from mine and comminution energy data into emissions profiles and climate change impacts.

Project Duration & Delivery:

5 weeks duration and the applicant will be required on-site at UQ’s Indooroopilly Mine site.

Description:

The research project will support an existing MPhil project that is developing mine energy curves into emissions curves. The project will involve analysis of mine energy supply and demand profiles, and map this information into visual formats (based on the existing comminution energy curves) to benchmark and evaluate mine operations’ performance in emissions, climate impacts and improvement opportunities.

The project may also analyse the potential impacts of introducing renewable energy solutions on mine performance in emissions, climate impacts.

Expected outcomes and deliverables:

The successful applicant will be required to gain an understanding of the existing mine energy curves outcomes and processes. This will be supported by the Emissions Curves MPhil scholar and JKMRC researchers.

The aim of the project is to prepare benchmarking tools to:

• Assess potential impacts of introducing renewable energy solutions to mines
• Impacts of different mine energy sources on
  • Climate change
  • Emissions profiles
• Compare emissions performance of
  • Different mine types
  • Commodities
  • Energy supply profile
  • Operating regimes

The applicant will be integrated into the Energy to Emissions Curves research project at the JKMRC and receive bespoke instruction energy & emissions curves techniques.

At conclusion of the project the applicant will be expected to produce a written report and provide an oral presentation summarising their investigations and the results obtained.

Suitable for:

The project is well suited for 3^rd or 4^th year Engineering, Science or Information Technology students wishing to obtain experience in integrated engineering and climate change/emissions impacts across the minerals industry.

The project does not require minerals industry expertise, but familiarity with natural resources and energy/emissions is beneficial.

Self-motivation and willingness to learn new skills are essential.

Primary Supervisor:

Associate Professor Marcin Ziemski

Further information:

Interested applicants may contact Associate Professor Marcin Ziemski or Dr Gordon Forbes to discuss this project in more detail, prior to submission of their online application.

Project title:

Discovery of an optimal set of topology metrics from causal networks formed from hazard identification data for enhancing risk management decision making.

Project Duration & Delivery:

6-8 weeks duration. This project can be done remotely, with regular communication with supervisor via Zoom.

Description:

Across all of the engineering industry, much data is generated to support risk management decision making. Often in the interests of enhancing safety, but also for integrating the management of various types of risks (eg financial, environmental, social, safety, etc) in a systematic way. A big problem that all industries, and the mining industry in Australia in particular, faces at the moment is how to integrate all this data and view it in one place to be able to make well-informed decisions about risk management?

One new approach for integrating the various risk data together is done by converting the results of hazard identification (HAZID) methods (e.g. Fault Tree Analysis, Failure Mode and Effects Analysis, Hazard and Operability study (HAZOP), etc) into causal networks and analysing the topology of that network. Hazard identification results describe a potential accident scenario that could occur, and these are used to help engineers decide what controls can be put in place to avert or prevent it. See Figure 1 for an example of HAZOP results converted into a causal network.

Figure 1 - HAZOP Causal network, measuring the degree of each node

Various metrics, that are meaningful from a causal point of view, can be calculated from the topology of the network, as used as systems level data for supporting risk management decision making. For example, which event in the above HAZOP scenario, in Figure 1 has the most causes and consequences attached to it? It will be nodes with the highest network degree, which the colour map in Figure 1 shows you, such as node 26 and 28 in the middle of the diagram. These are nodes to address first in attempting to avert or prevent the above accident scenario from occurring.

Recently, various metrics have been applied to causal networks made from HAZID results to explore their usefulness and meaningfulness, such as the degree and betweenness. However, there are many, many metrics that haven’t yet been tested. Nor has the question been answered what is the best set of metrics to use together that give the most useful information for supporting risk management decision making?

This project is about exploring the best set of causal network topology metrics to use together in an integrated way to support decision prioritisation in the context of managing risk. This project is a graph theory/network theory-based project, with very practical applications in the field of risk management. Case studies on real chemical process and mining examples will be the subject of study.

An abstract for a conference paper has already been submitted on this topic. This paper will be presented at CHEMECA 2021 (next year). CHEMECA is the prime chemical engineering conference in Australia and New Zealand. Students who participate in this project will have an opportunity to contribute to this paper and be included as an author.

Expected outcomes and deliverables:

The applicant will gain skills in practical applications of network theory to risk management situations. This will involve learning how to using Excel and Matlab to perform network topology calculations.

The student will have access to opportunities to share their findings with industrial personnel throughout the course and at the end of the project.

They will also learn how to:

• Engage with literature about network metric calculation methods
• Communicate their findings via oral presentation
• Communicate their findings in a report.

Suitable for:

This project is suitable for 1-2 students, since multiple scenarios can be tested with 2 students.

This project is open to students with an engineering, applied maths, computer science or software engineering background, who have completed their 3^rd year of their degree (for 4 year degrees) or 2^nd year (if it is a 3 year degree).

Primary Supervisor:

Dr Ben Seligmann

Further information:

Interested applicants may contact Dr Ben Seligmann to discuss this project in more detail, prior to submission of their online application.

Project title:

Evaluation of new instrumentation for the JK Drop Weight Tester Ore Characterisation Device.

Project Duration & Delivery:

5 weeks duration and the applicant will be required on-site at UQ’s Indooroopilly Mine site.

Description:

The University of Queensland’s Julius Kruttschnitt Minerals Research Centre (JKMRC) is world-renowned for development of a novel ore breakage characterisation device known as the JK Drop Weight Tester. The device is designed to assess the energy required to crush and grind rock within minerals processing plants and has become a minerals industry standard via JKMRC’s commercialisation company, JKTech. The purpose of this project is to evaluate recently procurred  instrumentation for the JK Drop Weight Tester: an impact load cell. The impact load cell promises to provide quantitative measurements of the fracture energy absorbed by rocks during breakage events with differing input energies. The research wil involve conducting a series of experiments aiming to assess the efficacy of the new instrumentation, as well as provide background knowledge for development of a new standard for ore breakage characterisation within the minerals industry. The experimental program wil involve preparation of rock samples for breakage experiments, conducting the breakage tests and analysis of the results.

Expected outcomes and deliverables:

The successful applicant will receive training in the safe use of industrial Pilot Plant equipment to conduct experimental investigations, as well as gain skills in data collection, analysis and reporting.

The applicant will be integrated into the research program of the JKMRC and receive bespoke instruction on minerals processing knowledge and techniques.

At conclusion of the project the applicant will be expected to produce a written report and provide an oral presentation summarising their experimental investigations and the results obtained.

Suitable for:

The project is well suited to 3^rd or 4^th year Engineering students wishing to obtain experience in industrial R&D procedures and practice.

Self-motivation and willingness to learn new skills are essential.

Primary Supervisor:

Dr Dion Weatherley

Further information:

Interested applicants may contact Dr Dion Weatherley to discuss this project in more detail, prior to submission of their online application.