55 research outputs found

    Design of microfluidic networks

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    Microfluidics is a relatively new and fast growing research area in fluid mechanics. The devices in question are thin wafers containing etched or printed interconnecting channels through which fluids are pumped, which can mix and/or react at various nodes to produce an output product. Microfluidic devices have applications in many manufacturing and chemical detection processes. For example, they can be used to manufacture monodisperse droplets with very well defined properties for pharmaceutical applications; or form the basis for miniaturised ‘lab-on-a-chip’ sensor arrays for detecting biological substances or toxins

    Human Decompression Modelling

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    At present, no decompression algorithm is able to predict safe decompression for all dive scenarios. In practice, empirical adjustments are made by experienced organisations or divers in order to improve decompression profiles for the range of depths and durations needed on any particular dive. Bubble formation and growth in the human body are the fundamental causes of decompression sickness, and it is believed that there is significant scope for incorporating better modelling of these processes into the design of decompression algorithms. VR Technology is a leading supplier of technical dive computers. The company is interested in expanding upon an existing algorithm (the Variable Gradient Model - VGM), which is used to design ascent profiles/decompression schedules and thereby mitigate the risk of decompression sickness in divers. The Study Group took the approach of trying to extend the existing Haldane model to account more explicitly for the formation of bubbles. By extending the model to include bubble dynamics it was expected that some physical understanding could be gained for the existing modifications to some of the parameters. The modelling that occurred consisted of first looking at the Haldane model and then considering a single small isolated bubble in each of the compartments and interpreting the predictions of the model in terms of decompression profiles

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