Resilient infrastructure based on cognitive buildings

气候变化是显而易见的。迫切需要确保民用基础设施能够抵御气候变化的影响。要使民用基础设施具有复原力，就需要对基础设施状况有准确的了解，同时考虑到结构和环境信息，以及越来越多的社会经济现象。现代民用基础设施既能分析其状况，又能适应环境，例如通过(半)主动阻尼器或基于传感器的执行器。然而，尽管经常被称为“智能”，但目前的基础设施无法从结构和环境因素中学习或预测，也无法利用物联网(IoT)整合社会经济现象。该项目旨在利用“认知建筑”这一新兴范式，为具有复原力的基础设施开发一种新的科学基础。认知建筑能够感知环境条件，学习外部(或用户相关)因素，并集成物联网设备以优化性能。然而，认知建筑通常专注于减少能源消耗和碳足迹，缺乏无缝集成与弹性相关的结构信息的能力。因此，拟议的项目旨在将认知建筑范例扩展到基础设施复原力。作为出发点，将考虑与弹性基础设施相关的结构健康监测和结构控制(SHM/SC)战略。几年来，SHM/SC实践主要依靠数据驱动建模来提取关于结构状态的信息。然而，数据驱动的建模缺乏物理背景，无法提供SHM/SC对未来结构行为进行可靠预测所需的信息。因此，对认知建筑范例的拟议扩展将涉及将分散的、基于物理的建模整合到无线SHM/SC中。这项研究是由DFG资助的德国-希腊联合研究项目提出的，该项目旨在启动一项国际合作。拟议研究的预期结果是一种将分散的基于物理的模型有效地嵌入到无线SHM/SC系统中以提高基础设施弹性的方法。预计该项目将有助于提高无线SHM/SC系统的性能，并将基础设施系统整合到“工业4.0”、“智慧城市”和“万物互联”的概念中。这一研究项目标志着无线SHM/SC嵌入式计算的一种全新范式的转变，这是根据气候变化促进弹性基础设施的持续发展。

Climate change is evident. There is an urgent need to ensure resilience of civil infrastructure against impacts of a changing climate. Making civil infrastructure resilient requires precise insights into the infrastructure condition, taking into account structural and environmental information and, increasingly, socio-economic phenomena. Modern civil infrastructure is able to both analyze its condition and to adapt to the environment, e.g. through (semi-)active dampers or sensor-based actuators. However, although frequently termed "smart", current infrastructure is unable to learn or to anticipate from structural and environmental factors, or to utilize the Internet of Things (IoT) for integrating socio-economic phenomena. This project aims to take advantage of the emerging paradigm of "cognitive buildings" to develop a novel scientific basis towards resilient infrastructure. Cognitive buildings are able to sense environmental conditions, to learn from external (or user-related) factors, and to integrate IoT devices to optimize performance. However, cognitive buildings, typically focusing on reducing energy consumption and carbon footprint, lack the ability of seamlessly integrating structural information relevant to resilience. The proposed project therefore aims to extend the cognitive buildings paradigm towards infrastructure resilience. As a point of departure, structural health monitoring and structural control (SHM/SC) strategies, relevant to resilient infrastructure, will be considered. For several years, SHM/SC practice has been mainly relying on data-driven modeling for extracting information on the structural condition. However informative, data-driven modeling lacks physical background and fails to provide the information necessary for SHM/SC to produce reliable predictions on future structural behavior. As a consequence, the proposed extension to the cognitive buildings paradigm will involve integrating decentralized, physics-based modeling into wireless SHM/SC. This research is proposed out of a DFG-funded German-Greek joint research project conducted to initiate an international collaboration. The expected outcome of the proposed research is a methodology for efficiently embedding decentralized physics-based models into wireless SHM/SC systems to advance infrastructure resilience. It is further expected that this project will contribute to enhancing the performance of wireless SHM/SC systems and to integrating infrastructure systems into the concepts of "Industry 4.0", "Smart City", and the "Internet of Everything". This research project marks a shift towards an entirely new paradigm in embedded computing for wireless SHM/SC in accordance with ongoing developments facilitating resilient infrastructure in the light of climate change.