Urban Dynamics, Complex Networks and Energy

How do people shape the cities in which they live? How do cities shape the behaviour of people? How does this influence the energy consumed in urban systems? Is it possible to influence the dynamics of a city to be more efficient at the city scale?

These are all questions that are of great interest in the emerging theories of complex systems, in our quest to scientifically understand what shapes our urban environment. This research will focus on how the complex interactions between the various components, such as buildings, technology, infrastructure, the environment, and people, result in system-scale properties such as energy consumption of the built environment.

Networks are often used to mathematically and computationally model complex interactions between individual components in a complex system such as a city, and networks appear in cities in many guises. The most obvious of these are the physical infrastructure networks such as transport and power networks. Less well defined are the more human networks that contribute to the functioning of urban dynamics. These range from supply networks for goods and services to networks representing communication between associated individuals. The latter type in particular are constantly changing in their structure and not very well known. Online social networks are often used as a proxy for these real-world peer networks, but can only be approximately representative. There is therefore scope in this research for the development of better models for the networks of influence between individuals, for example on energy technology uptake and behaviour. Other areas that may be of interest include distributed generation and storage, micro-grid stability and many other topics where networks appear in the complex systems of cities.

The PhD will be based in the Department of Architecture and Civil Engineering, but will have strong links with Mathematics, Computer Science and Electrical Engineering, collaborating through the Centre for networks and collective behaviour (CNCB), which provides a focus and forum for the discussion of research where issues of network connectivity or collective behaviour between individuals arise. Candidates are sought with a keen interest in mathematical modelling and computer simulation, and a strong experimental attitude to exploring new ideas. Previous experience of programming (for example in Python or C) would be a strong advantage, and the ability to learn new methods of digital analysis essential.