Buckman, AH (2016) An Exploration of the Applications of Increased Information Availability in Smart Buildings. PhD thesis, University of Sheffield.
Abstract
Modern buildings have the capability to capture vast quantities of information about the building itself, its purpose, the people that use it and its wider environment. With the development of fields such as the Internet of Things and Big Data, the future of buildings will involve more data around all aspects of their operation and the people using them. Within the context of these changes, this research hypothesises that the availability of increasing information within buildings can enable new ways of operation to step change their performance.
Initially the thesis combines an extensive literature review of modern building developments and the current landscape that buildings operate within to develop clarity around the term “Smart Building”. Two case studies are then presented to demonstrate the potential of Smart Building concepts: The first case study involves a pilot study within an existing university library building using occupancy, energy, occupant satisfaction and building functionality data to investigate the potential of the buildings ability to vary physical space with occupancy. The second study uses computational fluid dynamics to model the thermal comfort variations throughout a large underfloor heated naturally ventilated atrium. The results are then used to investigate potential energy savings and comfort improvements through correlating individual comfort preferences with environmental variations.
The work forms a clear definition of a Smart Building to create a framework for researchers and designers to focus future Smart Building developments. The first case study then demonstrates that by varying physically occupied space with occupancy, energy consumption of the building can be reduced by approximately 33%. The second study demonstrates that a step change in both comfort and energy efficiency can be achieved in flexible working spaces by aligning individual preferences with environmental conditions. These findings are discussed in detail, addressing limitations and future expansions of the novel approaches developed.
Metadata
Supervisors: | Beck, Stephen and Mayfield, Martin |
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Awarding institution: | University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Mechanical Engineering (Sheffield) |
Identification Number/EthosID: | uk.bl.ethos.694143 |
Depositing User: | Mr AH Buckman |
Date Deposited: | 13 Sep 2016 15:02 |
Last Modified: | 03 Oct 2016 13:19 |
Open Archives Initiative ID (OAI ID): | oai:etheses.whiterose.ac.uk:13858 |
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Thesis for the Degree of Doctor of Philosophy
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Description: Thesis for the Degree of Doctor of Philosophy
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