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  School of Mathematical Sciences, Queen Mary, University of London
School of Mathematical Sciences, Queen Mary, University of London

The aim of this project is to analyse real-world infrastructure systems with a view to aiding day-to- day and emergency planning of critical —primarily energy— European infrastructures. Our strategy will be to apply the mathematical findings that constitute the body of, so-called, complexity theory to real-world networks. In order to do so we shall map specific networks (both physical and service) that make up the main elements of functional interconnected networks. The project partners will engage directly with infrastructure owners and governmental decision making bodies; thus enabling access to knowledge sets that will form the basis of the project case studies.
In view of these goals, the project will assemble, develop and apply complementary mathematical methods to analyse large, man-made multi-element infrastructure systems that exhibit, so-called, complex behaviour.

The linking themes between these widely differing systems will be the common needs for both qualitative and quantitative prescriptions required to gain insight into the processes that generate complex behaviour. This will assist in the development of civil emergency preparedness strategies as well as in the general long-term planning of energy infrastructure programmes. In order to address such interdisciplinary topics, researchers working in a wide variety of fields will bring insights to problems that, in complex systems terms, have a common qualitative nature; thus enabling a macroscopic overview of the complex behaviour of key infrastructures.

The themes running across the individual subject areas will be vulnerability, volatility and emergent phenomena. In addition to tackling specific real-world problems, the project will provide a generalised view of how specific classes of topology, coupling laws, and interdependencies affect their vulnerabilities (or conversely robustness) to unexpected natural, economic or man-made perturbations.

To gain insight into the key qualitative dynamical features exhibited by such networks, the consortium will identify which types of non-linear phenomena are responsible for generic network behaviour such as:

  • instabilities and collapse: both structural (catastrophic failure of network components), functional (electricity grid blackouts, supply chain),
  • volatility and memory (spot electricity pricing),
  • feedback (influence on congestion in networks)
  • inter-network coupling (e.g. vulnerability of interconnected networks to unexpected failures)

Although the project will make ample use of standard mathematical concepts of complex systems theory, new methods based on the spectral representation of the weighted connectivity matrices will be introduced and tested on real-world networks to measure the vulnerability of agglomerate networks systems to widespread propagation of failures. We shall also study the role of feedback and scaling as drivers for emergent phenomena, and correlate volatility (or conversely persistence) from differing parametric time series in coupled systems


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