A presentation conducted by Miss Sarah Dunn, Newcastle University.
Presented on Thursday the 3rd of October 2013.
Modern infrastructure systems are vital to the functioning of modern society.They promote social well-being, support economic development and are crucial in mitigating the effects of natural hazards. While there is some understanding of their mitigation role, there has been little quantifiable work on how they support our societies or how they stimulate economic development. Some recent analysis of infrastructure
systems have shown that many of these seemingly different systems display similar architectures to each other leading to the hypothesis that the evolution of these systems is a result of underlying drivers that are common to all. This paper presents a network model that captures the growth of infrastructure networks in terms of architecture, hazard tolerance and geographical characteristics. The results presented in the paper suggest that the model may be the basis for an enhanced understanding of the role that infrastructure plays in sustaining our communities
SMART International Symposium for Next Generation Infrastructure: Modelling Infrastructure Systems for Resilience and Sustainability
1. ENDORSING PARTNERS
Modelling
Infrastructure Systems
for Resilience and
Sustainability
The following are confirmed contributors to the business and policy dialogue in Sydney:
•
Rick Sawers (National Australia Bank)
•
Nick Greiner (Chairman (Infrastructure NSW)
Monday, 30th September 2013: Business & policy Dialogue
Tuesday 1 October to Thursday, 3rd October: Academic and Policy
Dialogue
Presented by: Miss Sarah Dunn, Newcastle University
www.isngi.org
www.isngi.org
4. SCALE-FREE NETWORKS
EXPONENTIAL NETWORKS
• The Internet
• Electrical Distribution Systems
• The World-Wide-Web
• Airline Networks
(Albert, et al. Nature: 1999)
(Albert, et al. Nature: 2000)
Newman (2003)
(Sole, et al. 2008)
(Wilkinson, et al. 2012)
Carvalho, et al. (2009)
5. NETWORK GENERATION ALGORITHMS
Scale-free network generation algorithm:
Barabasi, A. L. and Albert, R. (1999). "Emergence of scaling in random networks." Science 286(5439): 509-512.
6. NETWORK GENERATION ALGORITHMS
Exponential network generation algorithm:
Wilkinson, S. M., Dunn, S., and Ma, S., (2012) ‘The Vulnerability of the European Air Traffic Network to Spatial
Hazards’ Natural Hazards. 60(3): 1027-1036.
9. DEVELOPMENT OF SPATIAL NETWORK MODEL
Starts with the input of initial conditions
Seed node locations and their geographic influence
The remaining nodes are then added individually
Each cluster can attract new nodes
New nodes located randomly within cluster
Each cluster expands with added nodes
𝑃 𝑐𝑐𝑐𝑐𝑐𝑐𝑐 =
𝑛𝑛𝑛𝑛𝑛𝑛 𝑜𝑜 𝑛𝑛𝑛𝑛𝑛 𝐶𝐶𝐶𝐶𝐶𝐶𝐶
𝑟𝑟𝑟𝑟𝑟𝑟 𝐶𝐶𝐶𝐶𝐶𝐶𝐶
𝑅𝑅𝑅𝑅𝑅𝑅 = 𝐶 𝐷 ln 𝑛𝑛𝑛𝑛𝑛𝑛 𝑜𝑜 𝑛𝑛𝑛𝑛𝑛 + 1
14. SPATIAL HAZARD TOLERANCE
Assessed by using a ‘central attack’ spatial hazard
Remove nodes in order of their distance from the centre of the
network
17. CONCLUSION
To date little work has been done on spatially distributed
networks
Space has a small but important effect on the degree
distribution of a network and can have a significant effect on
the hazard tolerance
We have developed a network model which is capable of
capturing the growth of infrastructure systems in terms of
both their network architecture and geographical distribution
This can be used to form an assessment of their hazard
tolerance to spatial hazards