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Paul Linden

Professor Paul Linden

Professor Paul Linden

Research Fellow

Interests and expertise (Subject groups)

Grants awarded

Environmental fluid mechanics and the application to sustainability

Scheme: Wolfson Research Merit Awards

Organisation: University of Cambridge

Dates: Jul 2010-Jun 2015

Value: £150,000

Summary: My research on environmental fluid mechanics is concerned with flows that affect our daily lives. These flows, that are responsible e.g. for the transfer of heat from a building through ventilation or the mixing of pollutants, are typically turbulent and involve the effects of variations of density within the fluid. In my research on the ventilation of low-energy buildings I use scaled laboratory models that show how to design the openings to a space so that it can be cooled by natural ventilation. The experiments show that the most efficient arrangement is to have openings at both low and high levels, and that ventilation control can be achieved by different arrangements of openings. We have constructed mathematical models for a range of natural ventilation systems which have been implemented into whole-building energy simulation codes that enable the energy consumption and other performance measures of a building to be predicted over a wide range of time scales. These codes are now being used to assess the potential for reducing energy consumption and the associated greenhouse gas emissions by retrofitting buildings with natural ventilation. We are currently investigating the use of phase change materials to reduce the amount of concrete in construction, while retaining the desired thermal capacity of the structure. We have also been studying air curtains commonly used in shop doorways and examining ways to optimize their performance Most natural and industrial flows have variations in density that inhibit vertical motion and mixing – hot air rises and it requires work to mix the heat downwards. At present we are unable to predict the rates of mixing that occur in these flows, which make for significant uncertainties in e.g. climate models. We have begun a new project that combines state-of-the-art experiments with high-performance computing and new mathematical modelling that examines these mixing flows directly.

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