Engineering Complexity Resilience Network Plus

我们的社会越来越依赖于前所未有的、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，我们不断扩展和集成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系统故障的级联和升级效应的影响。因此，我们能够理解和管理复杂工程系统（CES）中的风险和不确定性，以提供可靠和最佳的设计和控制解决方案，这一点变得越来越重要。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相互依赖的含义。然而，与自然生态系统不同，自然生态系统可能会通过多样化而变得更加强大，而人造复杂系统往往会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带来的挑战，我们需要利用和综合我们目前对自然和工程系统的理解，以及我们目前关于复杂性的更普遍的理论。工程复杂性弹性网络Plus（以下简称ENCORE）解决了CES中风险和弹性的重大挑战领域。我们的愿景是确定、开发和传播新方法，以提高复杂工程系统的弹性和可持续的长期性能，最初包括城市和国家基础设施、信息通信技术和能源基础设施、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。我们选择了这些特殊的CES领域，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，同时跨越足够多的不同领域，提供跨领域的学习机会。我们的方法是从[1]中共享学习自然复杂系统应对风险和不确定性的方式，以提供弹性（生态系统，气候，金融，生理学等），以及如何将这些策略适用于工程系统；[3]复杂性科学的工具和概念如何有助于更好地理解风险、不确定性和弹性，[3]在单个CES领域中提炼世界级的活动，为其他工程系统的设计和管理提供新的见解。这一领域应用的潜力，将被考虑纳入可行性研究的例子包括：-预测关键基础设施系统中的设备故障及其后果；-开发管理启发式，发挥与“风险登记册”相同的作用，但解决系统弹性；-优化有效管理城市和其他CES所需仪器的部署；-提高相互依赖的数字系统的弹性；-改进网络级联故障模型，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。-增加能够部署具有可复制性能的消费电子系统的环境数量；-减少在操作电子消费系统时出现人为行为错误的可能性。-识别约束/定义系统性能的关键因素；-延长系统寿命和功能；-绘制复杂系统复杂性和脆弱性之间的关系；-描述不确定性特征，并定义在CES控制和复杂决策过程中从一个阶段过渡到另一个阶段的推理过程。

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.