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Research Topic : preserving solution
Field of Research : Stochastic Analysis and Modelling
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Numerical Solution of Differential and Integral Equations (5)
Stochastic Analysis and Modelling (5)
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  • Funded Activity

    Discovery Projects - Grant ID: DP150102758

    Funder
    Australian Research Council
    Funding Amount
    $295,900.00
    Summary
    New Approaches to Modelling and Analysing Long-Memory Random Processes. The project aims to develop new approaches using infinite-dimensional Markov processes to solving important long-standing problems from the theory of long memory random processes and their applications. It aims to: construct a class of new representations of random processes; derive inequalities for the key numerical characteristics; and, devise and investigate numerical methods for computing the characteristics and for perf .... New Approaches to Modelling and Analysing Long-Memory Random Processes. The project aims to develop new approaches using infinite-dimensional Markov processes to solving important long-standing problems from the theory of long memory random processes and their applications. It aims to: construct a class of new representations of random processes; derive inequalities for the key numerical characteristics; and, devise and investigate numerical methods for computing the characteristics and for performing statistical inference on the long memory models. The accuracy of numerical approximations will be analysed using simulations on supercomputers. Expected outcomes include models and results of practical importance with applications such as intrusion detection problems, cell motility for biological data and telecommunication.
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    Funded Activity

    Discovery Projects - Grant ID: DP120101886

    Funder
    Australian Research Council
    Funding Amount
    $320,000.00
    Summary
    The mathematics of novel magnetic memory materials. Magnetic memories are the world’s principal device for storing information. The next generation will have greatly increased access speed and data-storage capacity. This project will develop the mathematical theory of these new magnetic memory materials, a crucial first step in understanding and being able to fine-tune their properties.
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    Funded Activity

    Discovery Projects - Grant ID: DP160101755

    Funder
    Australian Research Council
    Funding Amount
    $329,377.00
    Summary
    Novel Approaches for Problems with Uncertainties. This project aims to develop novel mathematical theories and numerical methods for problems affected by uncertainty in input data. This type of uncertainty exists in most mathematical models of real life applications. For these problems, a single deterministic simulation with one set of input data is of limited use. Therefore, novel techniques to deal with randomness are essential. The problems in this project are driven by specific applications .... Novel Approaches for Problems with Uncertainties. This project aims to develop novel mathematical theories and numerical methods for problems affected by uncertainty in input data. This type of uncertainty exists in most mathematical models of real life applications. For these problems, a single deterministic simulation with one set of input data is of limited use. Therefore, novel techniques to deal with randomness are essential. The problems in this project are driven by specific applications from ferromagnetism, structural acoustics and vibration. The new theories may lay the foundation for understanding ferromagnetic materials and structural acoustics. The novel approaches to be developed in this project may form the basis for the study of stochastic liquid crystal theory and other interface problems.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP200101866

    Funder
    Australian Research Council
    Funding Amount
    $525,000.00
    Summary
    Mathematics for breaking limits of speed and density in magnetic memories. The aim of this project is to develop a mathematical theory and numerical models of stochastic partial differential equations for magnetic nano-structures. Such materials will yield next-generation magnetic memories with up to three orders of magnitude faster switching speeds and dramatically increased data storage density. New mathematical theories will help understand their sensitivity to small random fluctuations that .... Mathematics for breaking limits of speed and density in magnetic memories. The aim of this project is to develop a mathematical theory and numerical models of stochastic partial differential equations for magnetic nano-structures. Such materials will yield next-generation magnetic memories with up to three orders of magnitude faster switching speeds and dramatically increased data storage density. New mathematical theories will help understand their sensitivity to small random fluctuations that can destroy stored information. This project aims to revolutionise mathematical modelling of magnetic memories and put Australia at the forefront of international research. Technological advances to create much smaller and faster memory devices are expected to enable groundbreaking ways of managing and mining big data.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP180100506

    Funder
    Australian Research Council
    Funding Amount
    $386,828.00
    Summary
    Uncertainty on spheres and shells: mathematics and methods for applications. This project aims to develop new mathematics and mathematically rigorous approximation methods for physical problems on spherical geometries in the presence of uncertainty. Many physical phenomena are modelled on either a sphere or a spherical shell. Such models typically have large uncertainty in the input data, through uncertainty in model coefficients, forcing terms, geometry or boundary conditions. Yet their stochas .... Uncertainty on spheres and shells: mathematics and methods for applications. This project aims to develop new mathematics and mathematically rigorous approximation methods for physical problems on spherical geometries in the presence of uncertainty. Many physical phenomena are modelled on either a sphere or a spherical shell. Such models typically have large uncertainty in the input data, through uncertainty in model coefficients, forcing terms, geometry or boundary conditions. Yet their stochastic modelling and subsequent numerical analysis in the presence of uncertainty are still in their infancy. This project will conduct numerical analysis, stochastic analysis and approximation to address such problems.
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