Critical infrastructure systems are socio-technical in nature, comprising engineered, organisational, and user subsystems that interact physically, logically and socially. However, interactions between critical infrastructure systems have traditionally been modelled on the assumption that these systems are primarily of a physical nature; whereas studies that explore social interactions of these systems are limited.
The Understanding Interdependencies research module aims to
- improve our understanding of social interdependencies
- develop a methodology to identify hidden interdependencies, on the assumption that they increase with increasing system complexity
- improve our understanding of how critical infrastructure networks adapt to urbanisation
Researchers in the group focus on three key topics:
The Organisational Interdependencies submodule will study social interdependencies in order to measure the extent of organisational interdependencies to explore how a system responds to failure and to understand how organisational arrangements affect system-level robustness and resilience. A comparative study of the electrical grid systems of Singapore and Switzerland will reveal how organisational interdependencies affect a system’s robustness and resilience and how to modify or adapt systems to increase their capacity to cope with disruptions.
The Hidden Interdependencies submodule will develop a novel approach to represent and model socio-technical critical infrastructure systems to explore the existence of latent unobserved interdependencies, which is a pioneering problem. Modelling will be based on sophisticated data mining techniques such as the Gaussian graphical models, and will be validated against real-world data sets.
Studies of the Growth and Evolution of City Infrastructure submodule is based on the premise that infrastructure systems are not static, but rather, grow in tandem with urban development. The submodule will investigate historical data of energy infrastructure in Singapore, Zurich and a third Asian city at different stages of development to uncover the relationship between growth mechanism and the city's growth parameters. The study will explore the predictive power of scaling laws that were recently developed at the Santa Fe Institute, which has been proven to be rather generic across cities, nations, and time scales.