Our research aims to develop capabilities to decarbonise of the energy sector and transition to renewables resources. This is achieved by developing clean synthetic fuels and novel design of combustors which will power future engines, propulsion systems and industrial processes.
Our goal is to power conversion technologies and contribute to the development of future energy systems including near-zero emission devices, micro-reactors and fuel cells.
Other important focus areas of our research include combustion safety, fire suppression, and reduction of fire and explosion risks.
Our research into the development of novel, clean and sustainable energy solutions that ensure transition to a low emissions economy includes:
Our research is conducted within the advanced facilities within our Clean Combustion Laboratory, which we also use for consulting work on a range of industrial problems including air conditioning, heat transfer and fire safety.
Our research is providing a novel understanding of a turbulent combustion environment that spans the entire regime from non-premixed to stratified and then premixed. This is highly relevant to lean combustion gas turbines and direct-injection engines where mixed-mode combustion prevails.
The burner provides a challenging platform for combustion modellers where the requirement is for a single-model to be able to compute all modes of combustion.
The project is highly relevant to combustion in direct-injection engines and gas turbines where compositional inhomogeneity and high rates of shear dominate the flow within the combustion chamber. Developing a database for model validation in well-controlled burners is important.
This is made possible with the piloted inhomogeneous burner designed and built at the University of Sydney. In the burner, the reacting mixture is introduced through two annular tubes such that the inner tubes can slide upstream of the jet exit plane. Both shear and compositional inhomogeneity can be introduced independently by varying the composition, the velocity ratio and the recess distances of the inner tube with respect to the annulus.
A parallel experimental and numerical program is continuing to explore various research aspects of mixed-mode flames and to enable their computations.
We aim to resolve the complexities of the primary and secondary atomisation of sprays to enable control over the subsequent formation of droplets. Standard backlight shadowgraph imaging is performed to dual angle and double-pulse to enable the direct visualisation of the shape, volume and velocity of liquid fragments of irregular shapes.
Atomisation is induced by air-blast, flow-blurring, and/or electrically charging the sprays. Dual-angle particle tracking velocimetry (PTV) approach are employed to provide extremely useful information on spray morphology including quantification of volume flux in atomising sprays.
Turbulent combustion of sprays are studied using advanced imaging diagnostics to resolved the structure of reaction zones. Such information is valuable for the development of modelling capabilities for spray jets and flames.
Auto-ignition is the key mechanism that initiates combustion in compression ignition engines. We aim to resolve the complexities of the process with respect to a range of fuels and coflow conditions. A jet-in-hot-coflow burner has been developed for this purpose and been used to study a range of gaseous and liquid fuels over a range of coflow conditions.
Resolving the complexities associated with the initiation, growth, and emission of ultra-fine particles that pollute our atmosphere is one of the critical unanswered questions at the frontier of combustion and aerosol science. That’s why we’re applying complex experimental and numerical methods to bring about a more detailed understanding of the mechanisms of soot inception.
In particular, we’re focused on the transition from molecules such as polycyclic aromatic hydrocarbons (PAH) to nanoparticles, which forms more mature soot. Our studies span a range of fuels as well as a range of flames from laminar to turbulent.
A useful aspect of particle formation in flames is the scalable synthesis of nanomaterials into a range of products from catalysts to smart sensors, biomaterials and biomedical devices. Flame spray pyrolysis (FSP) has emerged as a preferred manufacturing route, yet difficulties remain in the ability to control the product quality and formation rates.
We will monitor the evolution of solid particles and liquid fragments in ‘early’ regions of spray flows and build capability for advanced diagnostics of particle dynamics and synthesis in particle-laden flows.
Reacting, turbulent flows are extremely challenging to model. Any computational fluid dynamics (CFD) tool must be able to resolve or model the full range of turbulence length scales, while accurately transporting multiple species and accounting for the interaction of turbulence on the reaction zone in a physically correct way.
We have pioneered the modelling of turbulence-chemistry interactions through the conditional moment closure method, instrumental in developing the multiple-mapping conditioning approach which aims to provide a unified representation of premixed and non-premixed combustion under a single modelling approach.
This has led to the development of sparse-Lagrangian models for turbulent reacting flows which offer high accuracy and very low computational cost. We lead an international collaboration from Australia, Germany, India and China developing the open-source combustion code known as mmcFoam that is being applied to combustion of gaseous, liquid and solid fuels and to the formation of solid nanoparticles.
In addition to model development, we’re also advancing the underlying numerical algorithms for mixing and reacting flows, developing new governing equations and solution methods which improve the accuracy of representation of both turbulence and the mixing zone.
The methods we’ve developed have been implemented in the open-source CFD algorithm OpenFOAM, and in-house codes, both of which are parallelised and thus can be used to explore the fundamentals of turbulence and reactions through large-scale computations on national high performance computing facilities.
Hydrogen fuel cell technology is considered the most promising path to increase the flight time of small drones while retaining the benefits of electric propulsion. Recent progress in fuel cell technology and small-scale hydrogen storage has resulted in several demonstrator platforms with formidable endurance. However, the power density of fuel cell technology is low compared to other power sources, and fuel cells are therefor often hybridised with batteries or ultra-capacitors.
We’re investigating ways to effectively balance the load between the multiple power sources to extend the durability and operational robustness while keeping the implications on the complexity of the balance-of-plant to a minimum. Our research also focuses on water management for non-humidified operation and the use of machine learning techniques for health monitoring and prognostics of hybrid fuel cell-based systems.
The key difficulty with fires lies in the complex interactions between the intricate multi-phase chemistry and the wildly varying flow, heat and mass transfer processes occurring over multiple length and time scales. Ignition, fire spread, radiation and soot/smoke formation are key factors which must be known for effective control and the project will provide a better understanding of these issues.
Another objective is to develop a chemically suppressing agent that can be used with water to enhance its fire-fighting capability. The research will study the dynamics of delivering water sprays into a fire and then the water will be mixed with various agents (such a metal salts) to check the possible improvement of fire suppression.
Computational fluid dynamics
Experimental combustion (gaseous and liquid fuels)
Fuel cells and micro-reactors