Faculty/School

Faculty of Science

School of Mathematical Sciences

Topic status

We're looking for students to study this topic.

Research centre

Supervisors

Associate Professor Vivien Challis
Position
Associate Professor in Applied and Computational Mathematics
Division / Faculty
Faculty of Science

Overview

Structural optimisation is a powerful computational methodology for finding high-performing designs for structural components or material architectures. For example, what periodic scaffold would provide the highest possible stiffness for its weight?

Solving such a problem computationally requires an understanding of the relevant equations required to model the physical properties of interest, as well as efficient implementation of a range of numerical methods including finite elements, finite differences and optimisation algorithms.

With recent developments in 3D printing technologies it is now becoming possible to manufacture components with varying, fine-scaled features. Structural optimisation methods can help us take advantage of these new manufacturing technologies to generate components or materials with enhanced properties.

We are looking for students with an interest in computational modelling and high performance computing to undertake research in the area of structural optimisation, with a focus on benchmarking our algorithms on new structural optimisation problems.

Research engagement

You will do some reading of the literature, spend time understanding and making changes to research code, visualising and collating results, and writing a report. You will learn how to run research software written in the programming language Julia on high-performance computing infrastructure and make changes to the code to solve new structural optimisation problems.

Research activities

You will meet regularly with your supervisor and other group members who will guide you in your research project. You will read the literature, re-derive existing theoretical results, write and run research software, and write-up results.

Outcomes

The specific project aims can be tailored to your study level. The topic can also be personalised to suit your individual interests and skills, ranging from numerical methods and high performance computing to more of a focus on interesting applications of structural optimisation.

We expect to generate new results in structural optimisation and you will write these results up in a report.

Skills and experience

Ideally, you'll have some prior experience with MATLAB or other programming languages (Julia, Python, C or C++) and will be keen to learn more about coding in Julia, material modelling, computational methods and high performance computing.

Start date

18 November, 2024

End date

21 February, 2025

Location

QUT Gardens Point campus

Additional information

You are likely to be provided with a space on campus to work in during your project, and we will also organise access to QUT's high-performance computing facilities.

Keywords

Contact

Vivien Challis, vivien.challis@qut.edu.au