Computational methods for multi-physics and multi-phase topology optimisation

Overview

Topology optimisation facilitates the computational design of material layouts to maximise design performance subject to physics constraints expressed as partial differential equations. Owing in part to the considerable growth in additive manufacturing, these methodologies have become key design tools in structural design, aerospace, and robotics. The figure below shows an an example of topology optimisation for fluid-structure interaction.

With recent developments in multi-phase additive manufacturing, it is now becoming possible to manufacture components that are made of several distinct materials. Multi-physics and multi-phase topology optimisation methods are being developed that can design such multi-phase components to take advantage of these new manufacturing technologies for applications that involve multiple physical phenomena (e.g., fluid-structure interaction).

We are looking for students with an interest in computational mathematics, modelling, and high-performance computing. You will undertake novel research in the area of multi-physics and multi-phase topology optimisation using our Julia package GridapTopOpt.

Potential projects could include:

• Investigating the effect of the initial design parameterisation on the resulting optimised structures
• Benchmarking and optimisation of computational algorithms
• Developing new computational approaches
• Implementing new topology optimisation problems
• Deriving analytic shape derivatives

Research activities

• Read recent publications to gain an understanding of the current research in the field.
• Develop your understanding of numerical methods for partial differential equations and optimisation.
• Undertake pen and paper derivations.
• Develop and run research code including on high-performance computing infrastructure.
• Create visualisations and analyse optimised structures.
• Communicate your work in written form.
• Meet regularly with your supervisor(s) to discuss ideas and research direction, as well as receive feedback.

Outcomes

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

Outcomes will include new code, optimisation results, and a report summarising your progress over the course of the VRES project.

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 computational mathematics and high performance computing.

Start date

2 November, 2026

End date

19 February, 2027

Location

QUT Gardens Point Campus

Keywords

• Topology optimisation
• Shape optimisation
• Computational mathematics
• High-performance computing
• Finite element methods

Contact

Dr Zachary J Wegert

wegert@qut.edu.au