Cyber-physical model of civil infrastructure system subjected to extreme loads

极端载荷下民用基础设施系统的网络物理模型

• 批准号: RGPIN-2021-03430
• 负责人: Kwon, OhSung
• 金额: $ 4.52万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=742512
• 关键词: Cyber; physical; model; civil; infrastructure

The safety of the public and stable economic development of a modern society depend highly on reliable civil infrastructure such as bridges, tunnels, nuclear power plants, and highrise buildings. While these infrastructures are designed to be operational for several decades, infrastructures constructed with outdated design codes are vulnerable when subjected to extreme events such as earthquakes, fires, as well as frequent and increasingly unpredictable weather events. Accurate prediction of infrastructures' performance when subjected to extreme loads is of the utmost importance to optimally design new infrastructures and to develop maintenance and retrofit strategies for existing ones. However, the prediction of civil infrastructures' performance subjected to extreme loads has been challenging, especially when predicting infrastructures' failure. The challenges arise from various sources such as a lack of: (1) accurate models of structural components that can replicate the failure process of the components subjected to extreme loads; (2) data on the as-built condition of civil infrastructures; (3) testing facilities that can test full scale structural elements subjected to multi-axial boundary conditions; and, (4) inherent randomness in the external loads and uncertainties in the prediction models. This proposal's main objective is to expand the UT-SIM framework developed in the PI's research group toward a framework for the cyber-physical (CP) model of civil infrastructure to address aforementioned challenges. To achieve the objective, four projects will be carried out in the next five years: (1) a control scheme for substructure hybrid simulation with mega-scale multi-axial testing equipment; (2) a robust hybrid simulation methods for structures subjected to strong wind or fire; (3) a model updating of a cyber-model based on a machine-learning algorithm and IoT sensor data; and (4) a large-scale city block scale cyber-model that interacts with a physical model. The CP model is a conceptual advancement of a hybrid (numerical-experimental) model. The central premise in the hybrid model is that the numerically represented components are sufficiently accurate, which is often not the case. Also, the number of physically represented elements is limited by the capacities of experimental facilities. In the CP model, the numerical model of civil infrastructure is updated through measurements from real structures or physical specimens instrumented with various IoT-enabled sensors, while the main components that are expected to behave in the nonlinear range and are difficult to be modelled numerically are represented with physical specimens. The proposed research program and the proposed projects will lead to a simulation framework for the accurate prediction of civil infrastructure's performance in various natural hazards. Through the research program, diverse HQPs will be trained with a unique set of skills to contribute to the industry.

现代社会的公众和稳定的经济发展的安全在很大程度上取决于可靠的民用基础设施，例如桥梁，隧道，核电站和高层建筑。尽管这些基础架构被设计为几十年的运作，但在遭受地震，火灾以及频繁且越来越不可预测的天气事件等极端事件时，使用过时的设计代码构建的基础设施很容易受到伤害。准确地预测基础设施的性能，即受到极端载荷的绩效，对于最佳设计新基础架构并为现有策略制定维护和改造策略至关重要。但是，对民事基础设施的绩效的预测是挑战，尤其是在预测基础设施失败时。挑战来自各种来源，例如缺乏：（1）可以复制遭受极端载荷的组件的故障过程的结构组件的准确模型； （2）有关民用基础设施条件的数据； （3）测试设施，可以测试经过多轴边界条件的完整结构元素； （4）预测模型中外部载荷和不确定性的固有随机性。该提案的主要目标是将PI研究小组中开发的UT-SIM框架扩展到针对民用基础设施的网络物理（CP）模型的框架，以应对上述挑战。为了实现目标，将在未来五年内进行四个项目：（1）使用大型多轴测试设备进行子结构混合模拟的控制方案； （2）一种遭受强风或火的结构的强大混合模拟方法； （3）基于机器学习算法和IoT传感器数据的网络模型的模型更新； （4）与物理模型相互作用的大型城市块网络模型。 CP模型是混合动力（数值实验）模型的概念进步。混合模型中的中央前提是数值表示的组件足够准确，这通常不是这样。同样，物理代表元素的数量受到实验设施的能力的限制。在CP模型中，民用基础架构的数值模型是通过带有各种启用IoT传感器的实际结构或物理标本的测量来更新的，而预期在非线性范围内表现的主要组件则很难在数值上进行建模。拟议的研究计划和拟议的项目将导致模拟框架，以准确预测民用基础设施在各种自然危害中的表现。通过研究计划，各种各样的HQP将接受一系列独特的技能培训，可以为该行业做出贡献。