Engineering Complexity Resilience Network Plus

我们的社会越来越依赖于前所未有且日益复杂的工程系统。随着我们的制造业和服务业及其提供的产品不断复杂化和相互作用，我们继续扩展和整合我们的物理和数字基础设施，我们越来越容易受到高度复杂和不断发展的系统中故障的级联和升级影响。因此，理解和管理复杂工程系统（CES）中的风险和不确定性，以提供可靠的、最优的设计和控制解决方案变得越来越重要。对自然复杂系统的研究有助于我们理解复杂适应系统内部和之间的相互依赖关系。然而，与自然生态系统不同的是，自然生态系统可能通过多样化变得更加强大，而人为的复杂系统往往随着其复杂性的增加而变得更加脆弱。如果我们要应对复杂工程系统所带来的挑战，我们将需要利用和综合我们目前对自然和工程系统的理解，以及我们目前对复杂性的更普遍的理论。ENCORE复杂性弹性网络Plus（以下简称ENCORE）解决了CES中风险和弹性的大挑战领域。我们的愿景是识别，开发和传播新方法，以提高复杂工程系统的弹性和可持续长期性能，最初包括城市和国家基础设施，ICT和能源基础设施，复杂产品：航空航天（喷气发动机和空间发射和回收系统），后来探索包括核潜艇，发电站和战场系统。我们之所以选择这些特定的CES领域，是因为它们在英国面临的挑战和机遇之间取得了平衡，复杂性科学可以对我们的公民和企业产生重大影响，同时跨越足够多的领域，提供跨领域的学习机会。我们的方法是从[1]自然复杂系统科普风险和不确定性以提供弹性的方式（生态系统，气候，金融，生理学等）以及这些策略如何适用于工程系统;[2]复杂性科学的工具和概念如何有助于加深对风险、不确定性和复原力的理解，[3]世界上最伟大的奇迹。课程活动在个别CES领域提供新的见解，为其他工程系统的设计和管理。这一领域的应用潜力的例子，这将是考虑纳入可行性研究的内容包括：-预测关键基础设施系统中的设备故障及其后果;-开发一种管理启发式方法，发挥与“风险登记册”相同的作用，但解决系统弹性问题;-优化有效管理城市和其他CES所需的仪器部署;-提高相互依赖的数字系统的弹性;- 改进网络上级联故障的模型，使其考虑到节点的异质性，特别是不同类型节点的不同故障/恢复模式。- 增加CES可以部署的环境数量，并具有可复制的性能;-减少操作CES时人类行为错误的可能性。识别最强烈地约束/定义系统性能的关键要素;-延长系统寿命和功能;-映射复杂系统复杂性和脆弱性之间的关系;-表征不确定性并定义推理过程，以在CES控制和复杂决策过程中从一个阶段过渡到另一个阶段。

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.