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Multilayer networks and Games of incomplete information for infrastructure resilience

  • Full or part time
  • Application Deadline
    Friday, September 25, 2020
  • Funded PhD Project (European/UK Students Only)
    Funded PhD Project (European/UK Students Only)

Project Description

Infrastructure are socio-technical systems: they are comprised of (1) the technical, engineered side and (2) the social layer, that exchange stresses and strains leading at times to system failures. Resilience of such systems is demand-dependent. For example, the route and mode of transport to work determines the possibility of traffic congestions or station overcrowding. The peaks in the demand for electricity determine the likelihood of blackouts. These systems are often found to be driven towards a “tragedy of the commons” scenario, in which individually rational (but selfish) behaviours put at risk the infrastructure system integrity.

This PhD project investigates fundamental questions about how users take decisions based on the amount and type of information, to produce the onset of behaviours that boost performance and enhance resilience of spatially embedded infrastructure.

A new understanding of the decision dynamics will be achieved using a multilayer network framework where (imperfect) information layers and a non spatially embedded social network can be superimposed to the physical infrastructure network.

The working hypothesis is that decisions are influenced by the amount of information available, the perception individuals have of their importance and of their reliability.

The project is proposed as a theoretical investigation but will use data for validation and benchmarking including Transport for London (TFL) passenger counts and Sheffield City Council (SCC) traffic data.

Understanding what information triggers virtuous decisions will not only preserve the health of the infrastructure but can be leveraged to meet targets such as reducing energy consumption and carbon emissions.

The PhD student will be based at the Department of Automatic Control and Systems Engineering, supervised by Dr Giuliano Punzo and be part of the Urban Flow Observatory to which objective they will be expected to contribute (https://urbanflows.ac.uk).

The successful candidate must start by October 2020.

Next steps 
Informal enquiries are welcome, please contact the lead supervisor Dr Giuliano Punzo, at  

Applications should be made through the University of Sheffield and include a CV and a succinct one-page research proposal within this proposed topic area. Applications will be evaluated on a rolling basis.

Funding Notes

This PhD project is funded through an EPSRC Doctoral Training Partnership Grant for which eligibility rules apply (View Website).

The Scholarship provides funding for 3 and a half years. The Scholarship covers UK/EU tuition fees and pays a maintenance stipend at the UK rate (£15,009 per annum). An RTSG of £4500 is also included.

References

Candidate Requirements and Eligibility

Candidates are expected to have a degree in Engineering, Physics or Mathematics with strong mathematical skills, especially in the area of calculus and linear algebra. More information about entry requirements can be found here: https://www.sheffield.ac.uk/acse/research-degrees/applyphd

Applicants with other qualifications or experience should contact the Department’s PGR Support Team via [email protected] so that we can check on your eligibility.

How good is research at University of Sheffield in General Engineering?

FTE Category A staff submitted: 21.80

Research output data provided by the Research Excellence Framework (REF)

Click here to see the results for all UK universities

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