Euan Barlow

Multiobjective Memetic Algorithm Applied to the Optimisation of Water Distribution Systems

Finding low-cost designs of water distribution systems (WDSs) which satisfy appropriate levels of network performance within a manageable time is a complex problem of increasing importance. A novel multi-objective memetic algorithm (MA) is introduced as a solution method to this type of problem. The MA hybridises a robust genetic algorithm (GA) with a local improvement operator consisting of the classic Hooke and Jeeves direct search method and a cultural learning component. The performance of the MA and the GA on which it is based are compared in the solution of two benchmark WDS problems of increasing size and difficulty. Solutions that are superior to those reported previously in the literature were achieved. The MA is shown to outperform the GA in each case, indicating that this may be a useful tool in the solution of real-world WDS problems. The potential benefits from search space reduction are also demonstrated.

A theoretical investigation of chirp insonification of ultrasound contrast agents

A theoretical investigation of second harmonic imaging of an Ultrasound Contrast Agent (UCA) under chirp insonification is considered. By solving the UCAs dynamical equation analytically, the effect that the chirp signal parameters and the UCA shell parameters have on the amplitude of the second harmonic frequency are examined. This allows optimal parameter values to be identified which maximise the UCAs second harmonic response. A relationship is found for the chirp parameters which ensures that a signal can be designed to resonate a UCA for a given set of shell parameters. It is also shown that the shell thickness, shell viscosity and shell elasticity parameter should be as small as realistically possible in order to maximise the second harmonic amplitude. Keller-Herring, Second Harmonic, Chirp, Ultrasound Contrast Agent.

Investigating the performance of a fractal ultrasonic transducer under varying system conditions

As applications become more widespread there is an ever-increasing need to improve the accuracy of ultrasound transducers, in order to detect at much finer resolutions. In comparison with naturally occurring ultrasound systems the man-made systems have much poorer accuracy, and the scope for improvement has somewhat plateaued as existing transducer designs have been iteratively improved over many years. The desire to bridge the gap between the man-made and naturally occurring systems has led to recent investigation of transducers with a more complex geometry, in order to replicate the complex structure of the natural systems. These transducers have structures representing fractal geometries, and these have been shown to be capable of delivering improved performance in comparison with standard transducer designs. This paper undertakes a detailed investigation of the comparative performance of a standard transducer design, and a transducer based on a fractal geometry. By considering how these performances vary with respect to the key system parameters, a robust assessment of the fractal transducer performance is provided.

A mixed-method optimisation and simulation framework for supporting logistical decisions during offshore wind farm installations

With a typical investment in excess of £100 million for each project, the installation phase of offshore wind farms (OWFs) is an area where substantial cost-reductions can be achieved; however, to-date there have been relatively few studies exploring this. In this paper, we develop a mixed-method framework which exploits the complementary strengths of two decision-support methods: discrete-event simulation and robust optimisation. The simulation component allows developers to estimate the impact of user-defined asset selections on the likely cost and duration of the full or partial completion of the installation process. The optimisation component provides developers with an installation schedule that is robust to changes in operation durations due to weather uncertainties. The combined framework provides a decision-support tool which enhances the individual capability of both models by feedback channels between the two, and provides a mechanism to address current OWF installation projects. The combined framework, verified and validated by external experts, was applied to an installation case study to illustrate the application of the combined approach. An installation schedule was identified which accounted for seasonal uncertainties and optimised the ordering of activities.

A fractional Fourier transform analysis of a bubble excited by an ultrasonic chirp

The fractional Fourier transform is proposed here as a model based, signal processing technique for determining the size of a bubble in a fluid. The bubble is insonified with an ultrasonic chirp and the radiated pressure field is recorded. This experimental bubble response is then compared with a series of theoretical model responses to identify the most accurate match between experiment and theory which allows the correct bubble size to be identified. The fractional Fourier transform is used to produce a more detailed description of each response, and two-dimensional cross correlation is then employed to identify the similarities between the experimental response and each theoretical response. In this paper the experimental bubble response is simulated by adding various levels of noise to the theoretical model output. The method is compared to the standard technique of using time-domain cross correlation. The proposed method is shown to be far more robust at correctly sizing the bubble and can cope with much lower signal to noise ratios.