Prof Seth Bullock is a leading UK complexity science researcher at the University of Southampton. The Resilient Futures project aims to build a prototype interactive demonstrator simulation that operationalises the otherwise nebulous concept of resilience for a wide range of decision makers and stakeholders.

1. Resilient Futures
Operationalizing Resilience for UK
Infrastructure and its Stakeholders
Seth Bullock, Andy Dainty,
Rich Dawson, Pete Fussey,
Jonathan Rigg, Brooke Rogers, Institute for Complex
Beverly Searle, Jon Timmis Systems Simulation

3. Origins
An EPSRC “Sandpit”: Next-Generation Resilience.
Aim: generate adventurous, interdisciplinary
research projects targeting infrastructure resilience.
• 20+ academics from a range of disciplines
• + “mentors”, “facilitators”, guest speakers…
• …and a BBC Radio 4 documentary team…
• One week of presentations and brainstorming
Collaborative proposals developed and pitched
R-Futures project green lit

4. Future Resilience
What will our critical national infrastructure
look like in 2030? In 2050? Beyond?
How resilient will it be?
Today’s decision makers will
partly determine the answers.
R-Futures aim: to enable resilience considerations
to inform current decision making.

5. What do we Mean by Resilience?
• the ability to cope with shock or stress
• “bounce-back-ability”
Iain Dowie:
Football manager,
rocket scientist

6. Resilience of What to What?
For every sector of our national infrastructure...
• transportation, ICT, energy, water, waste
• health, government, emergency services
...resilience is seen as increasingly important.
This is particularly significant in the context of:
• sustainability
• climate change
• terrorism

7. White-Out

8. Wash-Out

9. Knock-Out

10. The R-Futures Team
An interdisciplinary collaboration:
- Complex Systems Modellers: Southampton, York
- Civil Engineers: Loughborough, Newcastle
- Social Scientists: Durham, Essex, Kings, St Andrews

11. Key Challenges
• Capture the inter-dependencies between sectors

13. Interdependent Futures...

14. Interdependent Networks
Every node needs
at least one same
type neighbour.
Attack
Green edges
indicate additional
inter-network mutual A complex
inter-dependencies cascade of
failures...

15. Interdependent Resilience
Network A
N
Size of Largest Remaining
Connected Component
2
4 K
32
0
0% % Attacked 100%
Coupling redundancy (K) increases resilience.

16. Interdependent Resilience
Network B
N
Size of Largest Remaining
Connected Component
2
4 K
32
0
0% % Network A Attacked 100%

17. Measuring Robustness
How should network A and B be connected and
coupled in order to maximise robustness to attack?
• If “robustness of Network B” = “size of the largest
post-attack connected component of B”
Optimal between-network coupling = zero
Optimal within-network connectivity = maximal
• But real-world networks are coupled together
because they need to be.
• What if a viable B node were one in a B fragment
that remains: large enough + coupled to A enough.

18. Unconstrained Viability (Γ=0.0)
1
1 1
Surviving A
Initial Coupling
Robustness
Surviving B
0 0 0
0 1 4 24
Attack Size Initial Connectivity

19. Constraining Coupling (Γ=0.1)
1
1 1
Surviving A
Initial Coupling
Robustness
Surviving B
0 0 0
0 1 4 24
Attack Size Initial Connectivity

20. Constraining Coupling
1 1
Network A Network B
Robustness
0 0
0% 100% 0% 100%
Initial Coupling Between Network A and B

21. Influence of Topology
1 1
Network A Network B
Robustness
0 0
0% 100% 0% 100%
Initial Coupling Between Network A and B
Switching from Erdos-Reyni graphs to regular lattices
radically changes the influence of coupling.

22. Open Questions
• Spatial embedding
• Correlated/structured interdependencies
• More than two coupled networks
• Hierarchical multi-network structures
• Dynamic processes on networks: e.g., flows
• Repair and recovery dynamics
• What do post-attack networks look like?
• How functional are they?

23. Key Challenges
• Capture the inter-dependencies between sectors
• Engage with the right stakeholders

24. Stakeholders
• Cabinet Office – Civil Contingencies Secretariat
• Fire & Rescue Service • Halcrow
• Institute of Civil Engineers • Costain
• Local Authorities • Arup • TFL
• National Youth Agency • RUSI • CPNI
• Health Protection Agency • DfT • NaCTSO
• Community Organisations • BT • Red Cross

25. Key Challenges
• Capture the inter-dependencies between sectors
• Engage with the right stakeholders
• Address the right future scenarios and hazards

27. R-Futures Scenarios

28. R-Futures Scenarios
New Tech
High-Tech Hamlets i-World
Decentralised Centralised
Local Power for
Local People The Global Village
Trad Tech

29. Key Challenges
• Capture the inter-dependencies between sectors
• Engage with the right stakeholders
• Address the right future scenarios and risks
• Effectively integrate social science and modelling

30. Scenarios
Insight Models
Stakeholders

31. Key Challenges
• Capture the inter-dependencies between sectors
• Engage with the right stakeholders
• Address the right future scenarios and risks
• Effectively integrate social science and modelling
• Make a critical impact on the key stakeholders

32. Beyond “one number”
• New understanding of interdependencies
A demonstrator system that foregrounds resilience
Transformative learning in key stakeholders
What is the best new Flooded
conduit for insight? area
Trapped
agents
Congestion
Evacuation
point
Built up
areas

33. “Serious Games”
There is increasing interest and investment in
interactive models for informing policy/strategy.
Some key issues revolve around the question of scale:
• Spatial: Regional? National? Continental? Global?
• Temporal: Acute phase? Recovery? Adaptation?
• Governance: Local agencies? National? Community?
Where should the boundaries be drawn for serious
games? What needs to be in and what can be left out?

34. Key Questions for Me
• How can academic research projects align with
private sector and policy making imperatives?
–“Infrastructure” is an increasingly crowded area
–But academic and non-academic interests are
divergent.
–Will we make a difference here and now, or ever?
• What do we want from models?
–Realistic, Accurate, Predictive
–“Computational Thought Experiments”
–Serious Games, Decision Theatres?

35. Gaihua Fu
Paul Andrews
Dan Sage
Mehdi Khoury
Duncan Mortimer
Julia Pearce
Kate Cochrane
Lucy Gregson-Green

36. Thank you