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Aaron Zecchin

Senior Lecturer
Civil, Environmental and Mining Engineering
University of Adelaide
Australia

Biography

2010 Doctor of Philosophy (Civil Engineering) University of Adelaide, Adelaide, South Australia. 2003 Bachelor of Science (Maths and Computer Science) at the University of Adelaide, South Australia, Australia. 2002 Bachelor of Engineering (Civil) with first class honours at the University of Adelaide, South Australia, Australia.

Research Interest

I have a strong interest and passion for research in the field of fluid line netowork dynamics. I am actively undertaking research in the development and analysis of partial differential equation solvers, and the analysis of two-dimensional and fluid-structure interaction effects within pipe flow. I research Laplace-domain characterisations of hydraulic networks, and the utilisation of these characterisations for simulation and model identification. I am also working on the use of sparse linear solvers for the fast steady-state simulation of pipe networks. I am extremely interested in the broad area of system identification, and I am active in its theoretical and practical application to the condition assessment of hydraulic systems. In particular, I have focused on the use of statistical frequency- and time-domain methods for both parameter estimation and fault detection within pipeline networks. In addition to the areas mentioned above, I also have an active interest in evolutionary algorithms, or more generally, population-based metaheuristics such as genetic algorithms, ant colony optimisation, particle swarm optimisation, differential evolution and the dynamically dimensioned search algorithm Within this field, my interest is in not only the application of these algorithms to engineering and environmental problems, but also the analysis and quantification of the convergence behaviour of such algorithms.

Publications

  • A. C. Zecchin, L. B. White, M. F. Lambert, A. R. Simpson. Parameter identification of fluid line networks by frequency-domain maximum likelihood estimation, Mechanical Systems and Signal Processing, (In press, accepted 15-01-2013).

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