Integrated research program for safety and sustainability of new and ageing infrastructure subjected to multiple hazards

拟议研究计划的长期目标是开发知识、技术和高素质人才，以促进新的和老化的民用基础设施的最佳安全性和可持续性。公共安全——包括经济安全——在很大程度上依赖于桥梁和建筑物等民用基础设施。在本研究中，由于劣化和剧烈加载事件而导致的损坏概率进入到用于决策的总损失曲线中。虽然传统的研究主要集中在单个结构成员，但本建议建立在全球结构性能模拟的最新进展之上。在协同努力下，建筑行业新兴的bim技术被用于生成复杂的结构模型，包括对非结构部件的损坏。沟通是通过扩展工业基础课程来进行的；建筑行业互操作性的ISO标准。通过一种新的统一的可靠性方法，这些模型考虑了多种危险，包括地震和老化造成的恶化。在一种可靠性分析中，获得了区域损失概率，并将关键基础设施识别为有价值的副产品。提出了一种“自适应保真度”策略，通过平衡计算成本和认知模型的不确定性，逐步完善结构模型。在协调的努力下，结构性能的概率模型使用贝叶斯方法进行校准，以明确识别认知不确定性。这项工作利用了近年来在世界范围内进行的广泛的结构测试程序。以平衡成本、安全和可持续发展的方式分配资源的最终目标；现有的可持续性效用指标在结构工程的背景下得到了扩展。预计这将影响传统的最佳设计、材料选择和建筑组件的可重用性。值得注意的是，该方法的区域性质有助于研究与城市地区密集化有关的风险，最近有人认为城市地区密集化比城市蔓延更具可持续性。

The long-term objective of the proposed research program is to develop knowledge, technologies, and highly qualified personnel to foster optimal safety and sustainability of new and ageing civil infrastructure. Public safety - including economic security - depends strongly on civil infrastructure, such as bridges and buildings. In the proposed research, the probability of damage due to deterioration and dramatic loading events enter into total loss curves that are used in decision making. While traditional research has focused on individual structural members, this proposal builds upon recent progress in simulation of global structural performance. In a synergistic endeavor, the emerging BIM-technology in the building industry is utilized to generate sophisticated structural models, including damage to non-structural components. The communication is carried out by extending the Industry Foundation Classes; an ISO standard for interoperability in the building industry. By means of a novel unified reliability approach, these models are considered in conjunction with multiple hazards, including earthquakes and deterioration due to ageing. In one reliability analysis, a regional loss probability is obtained, with identification of critical infrastructure as a valuable by-product. An "adaptive fidelity" strategy is put forward to gradually refine the structural models by balancing computational cost and epistemic model uncertainty. In a coordinated effort, probabilistic models for structural performance are calibrated with a Bayesian methodology to explicitly identify the epistemic uncertainty. This work utilizes the extensive structural testing programs that have been undertaken worldwide in recent years. Towards the ultimate objective of allocating resources in a manner that balances cost, safety, and sustainability; existing utility metrics for sustainability are extended in the context of structural engineering. This is expected to affect traditional optimal designs, material selection, and re-usability of building components. Notably, the regional nature of the methodology facilitates the study of risk associated with densification of urban areas, which has recently been argued to be more sustainable than urban sprawl.