Existence and Stability of a Model for Three-Dimensional Toroidal Plasma Equilibria. There is great physical interest in modelling strongly non-axisymmetric toroidal plasmas, but fundamental existence problems have made rigorous numerical analysis so far impossible. We seek to overcome this by investigating a class of idealized, but physically motivated, magnetohydrodynamic equilibria with stepped pressure profiles for which existence in the neighbourhood of axisymmetry has been proven. We will ....Existence and Stability of a Model for Three-Dimensional Toroidal Plasma Equilibria. There is great physical interest in modelling strongly non-axisymmetric toroidal plasmas, but fundamental existence problems have made rigorous numerical analysis so far impossible. We seek to overcome this by investigating a class of idealized, but physically motivated, magnetohydrodynamic equilibria with stepped pressure profiles for which existence in the neighbourhood of axisymmetry has been proven. We will (i) develop numerical techniques to extend these piece-wise Beltrami states far away from axisymmetry (ii) develop practical tests to determine when existence breaks down (iii) analyze the frequency spectrum of small oscillations about such equilibria (iv) extend the model to two-fluid MHD.Read moreRead less
Robust numerical solution of partial differential equations on petascale computer systems with applications to tsunami modelling and plasma physics. The project will apply new mathematical ideas to exploit the unprecedented computational resources provided by the next generation of high performance computers. The resulting techniques and software will form a key component for the science needed to understand the workings of complex dynamical systems, such as tsunamis and fusion reactors.
Numerical Algorithms for Solving Convex Optimization Problems Arising in Systems and Control Theory. The need to optimize occurs frequently in engineering applications. Typically one has a set of constraints specifying what solutions are allowable or meet design specifications and one would like to choose from these allowable solutions one which is optimal with respect to some meaningful metric. Such optimization problems tend to be rather complicated and must be solved numerically. This project ....Numerical Algorithms for Solving Convex Optimization Problems Arising in Systems and Control Theory. The need to optimize occurs frequently in engineering applications. Typically one has a set of constraints specifying what solutions are allowable or meet design specifications and one would like to choose from these allowable solutions one which is optimal with respect to some meaningful metric. Such optimization problems tend to be rather complicated and must be solved numerically. This project is concerned with creating improved numerical algorithms for solving particular important classes of optimization problems that arise in systems and control theory.Read moreRead less
Sparse grid approximations and fitting using generalised combination techniques. Sparse grid techniques provide an effective tool to deal with the
computational curse of dimensionality which is a constant challenge in
modelling complex data. The proposed research is aimed at the
development and analysis of algorithms for data fitting with sparse
grids using variants of the combination technique. The outcome of the
research is a theory which will provide insights in the applicability,
limit ....Sparse grid approximations and fitting using generalised combination techniques. Sparse grid techniques provide an effective tool to deal with the
computational curse of dimensionality which is a constant challenge in
modelling complex data. The proposed research is aimed at the
development and analysis of algorithms for data fitting with sparse
grids using variants of the combination technique. The outcome of the
research is a theory which will provide insights in the applicability,
limitations and the convergence properties of the proposed
algorithms. The outcomes will be widely applicable in modelling of
large scale and complex data as is encountered in areas of
bioinformatics, physics and experimental studies of complex systems.
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Discovery Early Career Researcher Award - Grant ID: DE120101707
Funder
Australian Research Council
Funding Amount
$375,000.00
Summary
Regularisation methods for solving nonlinear ill-posed inverse problems. Nonlinear inverse problems arise in numerous applications and their stable resolutions require regularisation methods. This project will develop various efficient solvers by using optimisation tools and Newton type procedures and consider their convergence properties. The methods will be applied to practical problems including the tomography techniques.