Computational modelling of nanofluids for industrial applications. The use of nanoparticles in heat transfer fluids, then known as nanofluids, increases their specific heat and thermal conductivity. Recent experimental works highlight that anomalous transport phenomena are evident in nanofluids that cannot be adequately described by classical conservation laws. We will extend these conservation laws to incorporate fractional operators to capture the fluid memory effects and the impact of particl ....Computational modelling of nanofluids for industrial applications. The use of nanoparticles in heat transfer fluids, then known as nanofluids, increases their specific heat and thermal conductivity. Recent experimental works highlight that anomalous transport phenomena are evident in nanofluids that cannot be adequately described by classical conservation laws. We will extend these conservation laws to incorporate fractional operators to capture the fluid memory effects and the impact of particle clustering. Computational modelling and experimental investigations will be undertaken to identify the heat transfer mechanisms of various nanofluids. The outcomes of the work will increase knowledge on nanofluids and offer a significant opportunity to improve the efficiency of many thermal engineering systems.Read moreRead less
Predicting strength of porous materials. This project aims to develop a predictive theory of strength for unflawed, low-ductile porous materials – an unsolved problem in computational solid mechanics. Three-dimensional printing of lightweight, porous materials is used in industry, medicine and science. The project will develop the theory and conduct experiments on porous metallic and polymeric samples made using additive manufacturing, which require understanding and optimisation of the building ....Predicting strength of porous materials. This project aims to develop a predictive theory of strength for unflawed, low-ductile porous materials – an unsolved problem in computational solid mechanics. Three-dimensional printing of lightweight, porous materials is used in industry, medicine and science. The project will develop the theory and conduct experiments on porous metallic and polymeric samples made using additive manufacturing, which require understanding and optimisation of the building of fine scale features. Understanding strength should improve design of stronger materials, by using and extending the capabilities of three-dimensional printing. These advances will further provide a much-needed basis for a fundamental understanding of fracture in other porous materials important to society such as concrete, rocks, porous ceramics and bone implants.Read moreRead less
Transforming Australian bio-based industries through multiscale modelling. Agricultural and forestry biomass can be converted into feedstocks for production of biofuels and biomaterials via synthetic biology. A key challenge is the complex biomass microstructure renders it highly resistant to conversion, and pretreatment is crucial for enhancing process efficiency. Micro-CT imaging will enable particle characterisation and identification of changes in the fibre composition during pretreatment. T ....Transforming Australian bio-based industries through multiscale modelling. Agricultural and forestry biomass can be converted into feedstocks for production of biofuels and biomaterials via synthetic biology. A key challenge is the complex biomass microstructure renders it highly resistant to conversion, and pretreatment is crucial for enhancing process efficiency. Micro-CT imaging will enable particle characterisation and identification of changes in the fibre composition during pretreatment. This information will be used to create a virtual biomass particle model for an in silico investigation to inform optimal process design. The framework will transform the way biomass is processed, contributing to the growth of the Australian bio-manufacturing industry by making it more productive, profitable and sustainable.Read moreRead less
Fractional dynamic models for MRI to probe tissue microstructure. This project aims to develop new mathematical tools for mapping tissue microstructural properties via the use of space-time fractional calculus methods. In magnetic resonance imaging, mathematical models and their parameters play a key role in associating information between images and biology, with the overall aim of producing spatially resolved maps of tissue property variations. However, models which can inform on changes in mi ....Fractional dynamic models for MRI to probe tissue microstructure. This project aims to develop new mathematical tools for mapping tissue microstructural properties via the use of space-time fractional calculus methods. In magnetic resonance imaging, mathematical models and their parameters play a key role in associating information between images and biology, with the overall aim of producing spatially resolved maps of tissue property variations. However, models which can inform on changes in microscale tissue properties are lacking. The tools developed by this project will be used to generate new magnetic resonance image based maps to convey information on tissue microstructure changes in the human brain. Additionally, the mathematical tools developed will be transferable to other applications where diffusion and transport in heterogeneous porous media play a role.Read moreRead less
A Novel Multilevel Modelling Framework to Design Diamond Nanothread Bundles. This project aims to develop a novel, computationally-based framework to optimally and efficiently design new fibre materials based on the diamond nanothreads synthesized by the PI in 2014. The CIs (and others) have demonstrated the tremendous promise these materials hold to replace common carbon fibres. The proposed framework will combine advanced computer modelling, statistical learning, genetic algorithm-based optima ....A Novel Multilevel Modelling Framework to Design Diamond Nanothread Bundles. This project aims to develop a novel, computationally-based framework to optimally and efficiently design new fibre materials based on the diamond nanothreads synthesized by the PI in 2014. The CIs (and others) have demonstrated the tremendous promise these materials hold to replace common carbon fibres. The proposed framework will combine advanced computer modelling, statistical learning, genetic algorithm-based optimal design and experimental validations. It will accelerate the design of these new carbon-based fibres as game-changing materials in a wide range of areas. Ultimately this project has the potential to deliver significant economic benefits and will place Australia at the forefront of the industrial revolution of the future.Read moreRead less
Multilayer Graphene Based Anti-Corrosion Polymer Coated Structures. This project aims to develop a novel multilayer graphene/polymer coating for structures exposed to corrosive environment with graphene concentration varying layer-wise to eliminate galvanic corrosion yet maintain all unique advantages owing to graphene inclusion, thus offering a cost-effective design solution with significantly improved anti-corrosion performance and remarkably enhanced safety and durability for structures. Expe ....Multilayer Graphene Based Anti-Corrosion Polymer Coated Structures. This project aims to develop a novel multilayer graphene/polymer coating for structures exposed to corrosive environment with graphene concentration varying layer-wise to eliminate galvanic corrosion yet maintain all unique advantages owing to graphene inclusion, thus offering a cost-effective design solution with significantly improved anti-corrosion performance and remarkably enhanced safety and durability for structures. Expected outcomes of this project include an innovative design, experimental data on corrosion prevention, development of reliable simulation techniques and design procedures for the proposed coating. This should provide huge benefits to Australian civil, offshore and marine engineering industry and national economy.Read moreRead less
Characterisation of mechanical behaviour of lithiated silicon. This project aims to develop novel characterisation and numerical techniques, thus aiming to solve the problem of mechanical failure in silicon based high energy density lithium-ion batteries. This will be achieved through development of novel techniques for in situ microscopy observation, nano-mechanics testing and atomistic modeling. The expected outcomes are effective solutions for development of reliable and efficient battery sys ....Characterisation of mechanical behaviour of lithiated silicon. This project aims to develop novel characterisation and numerical techniques, thus aiming to solve the problem of mechanical failure in silicon based high energy density lithium-ion batteries. This will be achieved through development of novel techniques for in situ microscopy observation, nano-mechanics testing and atomistic modeling. The expected outcomes are effective solutions for development of reliable and efficient battery systems. This project will provide significant benefits in the development of new power sources and energy storage devices for mobile electronics, electric vehicle and sustainable energy industries.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE210100273
Funder
Australian Research Council
Funding Amount
$407,679.00
Summary
Supercomputing to understand track buckling and related train derailments. This project aims to understand the contributions of railway train forces to a dangerous and high-cost track dynamic behaviour called buckling; by developing a supercomputing method that unlocks the capability for large-scale 3D train-track interaction research for railway trains of up to 250 vehicles. This project expects to generate new knowledge regarding track buckling, train derailments and train-track dynamics. Expe ....Supercomputing to understand track buckling and related train derailments. This project aims to understand the contributions of railway train forces to a dangerous and high-cost track dynamic behaviour called buckling; by developing a supercomputing method that unlocks the capability for large-scale 3D train-track interaction research for railway trains of up to 250 vehicles. This project expects to generate new knowledge regarding track buckling, train derailments and train-track dynamics. Expected outcomes include a new supercomputing method for train-track dynamics and derailment research and a science-based technique to assess track buckling safety. This project should provide significant benefits to the rail industry including enhanced rail safety, lower maintenance costs and improved transport efficiency.Read moreRead less
A Novel Surrogate Framework for evaluating THM Properties of Bentonite. Compacted bentonite as favoured engineered barrier material is widely used in environmental geotechnics and its failure can incur huge societal, economic and environmental loss. The project aims to develop a novel surrogate model to identify the optimal controllable factors' value to increase barrier's integrity and reliability. It expects to advance the fundamental knowledge of bentonite thermo-hydro-mechanical properties t ....A Novel Surrogate Framework for evaluating THM Properties of Bentonite. Compacted bentonite as favoured engineered barrier material is widely used in environmental geotechnics and its failure can incur huge societal, economic and environmental loss. The project aims to develop a novel surrogate model to identify the optimal controllable factors' value to increase barrier's integrity and reliability. It expects to advance the fundamental knowledge of bentonite thermo-hydro-mechanical properties through advanced molecular dynamics modelling, statistic learning and machine learning. It will deliver revolution design approach for bentonite used in engineered barriers in Australia and internationally. In the long-time it will bring huge economic, societal and environmental benefits to our community.Read moreRead less
Understanding bone structure evolution using machine learning. Bone remodeling is the ancient process of bone resorption and formation that optimises material properties and has led to evolution of terrestrial vertebrates. To date it is not understood how remodeling achieves tuning of bone material. This proposal aims to develop a machine learning based approach, linking computational modeling and imaging to address this problem. Intended outcomes are development of a multiscale model of remodel ....Understanding bone structure evolution using machine learning. Bone remodeling is the ancient process of bone resorption and formation that optimises material properties and has led to evolution of terrestrial vertebrates. To date it is not understood how remodeling achieves tuning of bone material. This proposal aims to develop a machine learning based approach, linking computational modeling and imaging to address this problem. Intended outcomes are development of a multiscale model of remodeling and machine learning algorithms for image analysis. This approach will help establish a structural-functional link between remodeling and bone material optimisation which ultimately provides significant benefits for bone tissue engineering, fracture healing and improved therapies for osteoporosis. Read moreRead less