QUT offers a diverse range of student topics for Honours, Masters and PhD study. Search to find a topic that interests you or propose your own research topic to a prospective QUT supervisor. You may also ask a prospective supervisor to help you identify or refine a research topic.
Found 8 matching student topics
Displaying 1–8 of 8 results
Optimisation of piezoelectric materials for robotics applications
Piezoelectricity, which translates to “pressure electricity”, is the phenomenon in which certain materials convert mechanical energy to electrical energy, and vice versa. Such materials are common-place and are used in a variety of applications including sensor, actuator, and energy harvesting technologies. The capabilities of such piezoelectric materials have not yet been fully realised. We plan to use computational structural optimisation to design new piezoelectric materials and components that may contribute to novel sensing technologies for robotics applications. Essentially, robots need …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
Branching processes, stochastic simulations and travelling waves
Branching processes are stochastic mathematical models used to study a range of biological processes, including tissue growth and disease transmission.This project will implement a simple stochastic branching process to generate simulations of biological growth, and then consider differential equation-based description of the stochastic model.Using computation we will compare the two models, and use phase plane and perturbation analysis to analyze the resulting traveling wave solutions.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Design, derivation, and implementation of mesh-free finite volume solvers based on 3D unit cell morphology to estimate biomass particle effective parameters
The aim of this PhD project is to use lignocellulosic morphological features extracted from high resolution micro-CT images of biomass particles undergoing a dilute acid pretreatment process to perform computational homogenisation over representative unit cell configurations. Mesh-free finite volume solvers will be developed based on 3D point cloud data sets to estimate virtual biomass particle effective parameters, such as diffusivity, thermal conductivity, and permeability. The simulation results will be analysed to provide a fundamental understanding of the impact that changes …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
Mathematical and computational techniques for advection diffusion reaction models
Mathematical models of advection diffusion reaction processes are fundamental to many applied disciplines including physics, biology, ecology and medicine. This project will focus on developing mathematical and computational techniques for continuum (PDE) and/or stochastic (random walk) models of advection diffusion reaction.Potential project topics include:building new simplified models that are easier to implement, interpret and analyseextracting new mathematical insights into advection diffusion reaction processesproposing new methods for parameterising models from datadeveloping new numerical and/or analytical methods for solving PDE models.All project …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
Computational methods for multi-scale structural optimisation
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.With recent developments in 3D printing technologies it is now becoming possible to …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
Exact and approximate solutions of diffusion on evolving domains
Classical applications of mathematical analysis involve solving partial differential equation models on fixed domains, e.g. 0 < x < L. Applications in biology, however, involve studying diffusive transport on rapidly evolving domains, e.g. 0 < x < L(t), where L(t) represents the length of the evolving tissue. While many problems have been addressed for the case where L(t) increases, less attention has been paid to cases where we consider diffusion on an oscillating domain.In this project we will construct exact …
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
Mathematical tools for stochastic and continuum transport models
Mathematical models of particle transport are fundamental to many applied disciplines including physics, biology, ecology and medicine. Particle transport is typically modelled using either a stochastic model, where probability rules govern the motion of individual particles, or a continuum model, where partial differential equations govern the concentration of particles in space and time. This project aims to use analytical and numerical techniques from applied and computational mathematics to address one or both of the following questions:what is the average time …
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
Mathematical and computational models for diffusion magnetic resonance imaging (dMRI)
In 1985, the first image of water diffusion in the living human brain came to life. Since then significant developments have been made and diffusion magnetic resonance imaging (dMRI) has become a pillar of modern neuroimaging.Over the last decade, combining computational modelling and diffusion MRI has enabled researchers to link millimetre scale diffusion MRI measures with microscale tissue properties, to infer microstructure information, such as diffusion anisotropy in white matter, axon diameters, axon density, intra/extra-cellular volume fractions, and fibre orientation …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Centre for Biomedical Technologies
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