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Details of Grant 

EPSRC Reference: EP/N010019/1
Title: Engineering Complexity Resilience Network Plus
Principal Investigator: Mayfield, Professor M
Other Investigators:
Varga, Professor LE Vasile, Professor M Purvis, Professor A
Researcher Co-Investigators:
Project Partners:
Deloitte UK Department of Energy and Climate Change Fujitsu
Idaho National Laboratory Met Office National Grid
National instruments (Global) National Physical Laboratory NPL Santa Fe Institute
Sofintsys SPECIFIC Innovation and Knowledge Ctr
Department: Civil and Structural Engineering
Organisation: University of Sheffield
Scheme: Standard Research
Starts: 15 February 2016 Ends: 14 February 2019 Value (£): 502,348
EPSRC Research Topic Classifications:
Building Ops & Management Complexity Science
Sustainable Energy Networks Transport Ops & Management
Urban & Land Management
EPSRC Industrial Sector Classifications:
Aerospace, Defence and Marine Construction
Related Grants:
Panel History:
Panel DatePanel NameOutcome
09 Sep 2015 EPSRC Grand Challenge 4 - Risk and Resilience Announced
Summary on Grant Application Form
Our society is increasingly reliant upon engineered systems of unprecedented and growing complexity. As our manufacturing and service industries, and the products that they deliver, continue to complexify and interact, and we continue to extend and integrate our physical and digital infrastructure, we are becoming increasingly vulnerable to the cascading and escalating effects of failure in highly complex and evolving systems of systems. Consequently, it is becoming increasingly critical that we are able to understand and manage the risk and uncertainty in Complex Engineering Systems (CES) to provide reliant and optimal design and control solutions.

Research on natural complex systems is helping us to understand the implications of inter-dependencies within and between complex adaptive systems. However, unlike natural ecosystems, which may become more robust through diversifying, man-made complex systems tend to become more fragile as their complexity increases. If we are to deal with the challenge presented by complex engineered systems, we will need to exploit and synthesise our current understanding of natural and engineered systems, our current theories of complexity more generally.

The ENgineering COmplexity REsilience Network Plus (hereafter called ENCORE) addresses the Grand Challenge area of Risk and Resilience in CES. Our vision is to identify, develop and disseminate new methods to improve the resilience and sustainable long-term performance of complex engineered systems, initially including Cities and National Infrastructure, ICT and Energy Infrastructure, Complex Products: Aerospace (both Jet Engines and Space Launch and Recovery Systems) and later to explore the inclusion of Nuclear Submarines, Power Stations and Battlefield Systems. We have chosen these particular CES domains as they strike a balance between the challenges and opportunities that the UK faces for which complexity science can have a significant impact for our citizens and businesses whilst spanning sufficiently diverse fields to present cross-domain learning opportunities.

Our approach is to create shared learning from [1] the manner in which naturally complex systems cope with risk and uncertainty to deliver resilience (ecosystems, climate, finance, physiology, etc.) and how such strategies can be adapted for engineering systems; [2] how the tools and concepts of complexity science can contribute towards developing a greater understanding of risk, uncertainty and resilience, and [3] distilling world-class activity within individual CES domains to provide new insights for the design and management of other engineering systems.

Examples of the potential for the application of this field and which will be considered for inclusion in the feasibility studies include:

- Predicting equipment failures and their consequences in critical infrastructure systems;

- Developing a management heuristic that plays the same role as a "risk register", but addresses systemic resilience;

- Optimising the deployment of instrumentation required to manage cities and other CES effectively;

- Increasing the resilience of interdependent digital systems;

- Advancing models of cascading failure on networks such that they take account of node heterogeneity and in particular the different failure/recovery modes of different types of node.

- Improving the number of contexts in which CES can be deployed with replicable performance;

- Decreasing the likelihood of human behavioural errors in operating CES.

- Identifying the critical elements that constrain/define system performance most strongly;

- Extending system lifetimes and functionality;

- Mapping the relationship between complex system complexity and fragility;

- Characterising uncertainty and defining the inference process to transition from one phase to the other in the control of CES and in complex decision making processes.

Key Findings
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Potential use in non-academic contexts
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Organisation Website: http://www.shef.ac.uk