Discovery Early Career Researcher Award - Grant ID: DE210100256
Funder
Australian Research Council
Funding Amount
$415,283.00
Summary
Extracting the hidden structure of glass from particle vibrations. Predicting the rigid behaviour of glass from its disordered, amorphous atomic structure remains a challenge in materials science. This project aims to define an innovative measure of structure based on how constrained each particle is, which can be quantified by measuring the particles’ vibrations. Using this new measure of structure, this project expects to link the microscopic structure of glass to its macroscopic properties v ....Extracting the hidden structure of glass from particle vibrations. Predicting the rigid behaviour of glass from its disordered, amorphous atomic structure remains a challenge in materials science. This project aims to define an innovative measure of structure based on how constrained each particle is, which can be quantified by measuring the particles’ vibrations. Using this new measure of structure, this project expects to link the microscopic structure of glass to its macroscopic properties via computer simulations. Expected outcomes of this project include a new methodology for characterising amorphous materials and an improved understanding of the nature of glass. This should provide significant benefits, such as an increased ability to rationally design amorphous materials with desired properties.Read moreRead less
Learning to predict polymorphism through simulation of nucleation and nanoparticle evolution. Many substances are capable of exhibiting a myriad of different structures despite having the same composition. This behaviour can have a significant impact on the production of new pharmaceuticals, since the sudden appearance of a new form can lead to instant withdrawal of the drug. By understanding how different forms grow, rather than focusing on just the stability of the product, this research will ....Learning to predict polymorphism through simulation of nucleation and nanoparticle evolution. Many substances are capable of exhibiting a myriad of different structures despite having the same composition. This behaviour can have a significant impact on the production of new pharmaceuticals, since the sudden appearance of a new form can lead to instant withdrawal of the drug. By understanding how different forms grow, rather than focusing on just the stability of the product, this research will lead to more reliable prediction of how pharmaceutical molecules might assemble. The same technology will potentially have impacts in many areas of nanoscience through improvements in efficiency, including the production of minerals, desalination and undersea gas recovery.Read moreRead less
Wake dynamics of oscillating cylinder in steady currents. This project aims at advancing knowledge in flow/structure interactions and developing improved methodology for predicting wave and current loading on marine structures, which are vital in many practical applications such as extraction of oil and gas resources and renewable energy from the ocean. The improved methodology and much-needed database of hydrodynamic force coefficients developed through this project for estimating hydrodynamic ....Wake dynamics of oscillating cylinder in steady currents. This project aims at advancing knowledge in flow/structure interactions and developing improved methodology for predicting wave and current loading on marine structures, which are vital in many practical applications such as extraction of oil and gas resources and renewable energy from the ocean. The improved methodology and much-needed database of hydrodynamic force coefficients developed through this project for estimating hydrodynamic loading on marine structures will significantly reduce the high, costly uncertainly levels that are being experienced in the design, construction and maintenance of marine structures (and facilities) and increase the competiveness of Australian relevant industries. Read moreRead less
Mathematical and computational models for agrichemical retention on plants. Mathematical and computational models for agrichemical retention on plants. This project aims to build interactive software that simulates agrichemical spraying for multiple virtual plants reconstructed from scanned data. Mathematical modelling and computer simulation could offer an alternative to expensive experimental programs for agrichemical spraying of plants. This project will use contemporary fluid mechanics to bu ....Mathematical and computational models for agrichemical retention on plants. Mathematical and computational models for agrichemical retention on plants. This project aims to build interactive software that simulates agrichemical spraying for multiple virtual plants reconstructed from scanned data. Mathematical modelling and computer simulation could offer an alternative to expensive experimental programs for agrichemical spraying of plants. This project will use contemporary fluid mechanics to build practical mathematical models for droplet impaction, spreading and evaporation on leaf surfaces, and experimentally calibrate and validate the models. The software is expected to drive the development of agrichemical products that increase retention, minimise environmental impacts, and reduce costs for end-users.Read moreRead less
Modelling stock market liquidity in Australia and the Asia Pacific Region. This project will develop new methods of assessing stock market liquidity in Australia and the Asia-Pacific region. These methods will use high frequency transactions-based data provided by the industry partner, SIRCA. The data will be the basis of smart information real time algorithms for measuring market liquidity. They will incorporate generalizations and extensions of recent developments in time series econometrics, ....Modelling stock market liquidity in Australia and the Asia Pacific Region. This project will develop new methods of assessing stock market liquidity in Australia and the Asia-Pacific region. These methods will use high frequency transactions-based data provided by the industry partner, SIRCA. The data will be the basis of smart information real time algorithms for measuring market liquidity. They will incorporate generalizations and extensions of recent developments in time series econometrics, and will be calibrated and evaluated statistically. The novel methods will be crucial to market participants and to regulators, who will be able to apply them to assess market depth and liquidity, and reduce trading costs substantially.Read moreRead less
Modelling health: Reporting behaviour and misclassification using survey data. Empirical models based on large scale survey data sets are used by health economists to inform policymakers. However, in the case of sensitive topics, a potential for survey misreporting may lead to inaccurate estimates of aberrant behaviours. To date, little work has been done analysing the extent and consequences of inaccurate reporting, especially within health economics. By addressing areas where potential for mis ....Modelling health: Reporting behaviour and misclassification using survey data. Empirical models based on large scale survey data sets are used by health economists to inform policymakers. However, in the case of sensitive topics, a potential for survey misreporting may lead to inaccurate estimates of aberrant behaviours. To date, little work has been done analysing the extent and consequences of inaccurate reporting, especially within health economics. By addressing areas where potential for misinformation is high, the overall quality of results will be enhanced. This research will be submitted to highly ranked health economics and econometrics journals to be made available to relevant policymakers intent on ensuring a healthy society.Read moreRead less
Threshold models in micro-econometrics with applications to empirical models of health. The aim of this project is to develop and apply new statistical approaches to endogenously identify non-linear relationships between explanatory variable(s) and the response variable in non-linear econometric models and to illustrate these with applications important to empirical health economics. Literature proliferates in linear models with non-linear effects, but in health economics non-linear models domin ....Threshold models in micro-econometrics with applications to empirical models of health. The aim of this project is to develop and apply new statistical approaches to endogenously identify non-linear relationships between explanatory variable(s) and the response variable in non-linear econometric models and to illustrate these with applications important to empirical health economics. Literature proliferates in linear models with non-linear effects, but in health economics non-linear models dominate. This project will generalise these techniques to allow for various forms of the threshold variable(s), including categorical and continuous, endogenous and exogenous, and those measured with error.Read moreRead less
Entropic Analysis of Financial Risk and Uncertainty. The recent financial crisis has shown that the financial markets are not as stable as expected, and are at risk from a lack of knowledge about new financial products and their risks. This research provides a framework to better measure and forecast financial risks by applying a set of techniques known collectively as entropic analysis as a novel way to measure the amount of information that can be extracted from historical data. The research w ....Entropic Analysis of Financial Risk and Uncertainty. The recent financial crisis has shown that the financial markets are not as stable as expected, and are at risk from a lack of knowledge about new financial products and their risks. This research provides a framework to better measure and forecast financial risks by applying a set of techniques known collectively as entropic analysis as a novel way to measure the amount of information that can be extracted from historical data. The research will facilitate the design of policies and regulations by regulatory authorities that need to evaluate new financial products, their associated risks and their impacts on the financial markets.Read moreRead less
Modelling a portfolio of financial assets: structure, estimation, testing and forecasting. Information regarding financial returns and risk is essential for optimal portfolio selection and asset management. Returns and risk have typically been analysed for individual assets. The project provides a theoretical solution to the important practical problem of modelling a portfolio of financial assets in realistic situations. The significance of the research is the development of a new approach to an ....Modelling a portfolio of financial assets: structure, estimation, testing and forecasting. Information regarding financial returns and risk is essential for optimal portfolio selection and asset management. Returns and risk have typically been analysed for individual assets. The project provides a theoretical solution to the important practical problem of modelling a portfolio of financial assets in realistic situations. The significance of the research is the development of a new approach to analyse a portfolio of returns and risk, and the determination of its applicability using numerical simulation techniques. The expected outcomes are an optimal practical method for analysing a portfolio of assets, a scientific monograph, and publications in leading international journals.Read moreRead less
Seasonal adjustment using disaggregated short time span data. Seasonally adjusted economic and social times series are vital information used by governments and businesses in decision making. This project will develop statistical methods to estimate and remove seasonal factors from economic and social time series using finely disaggregated data for a relatively small number of time periods. This will enable better and quicker estimation of seasonal factors when new series are introduced or there ....Seasonal adjustment using disaggregated short time span data. Seasonally adjusted economic and social times series are vital information used by governments and businesses in decision making. This project will develop statistical methods to estimate and remove seasonal factors from economic and social time series using finely disaggregated data for a relatively small number of time periods. This will enable better and quicker estimation of seasonal factors when new series are introduced or there a major changes to existing series, improving the analysis of such series and the decisions based on them.Read moreRead less