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 While these infrastructures are designed to be operational for several decades, infrastructures constructed with outdated design codes are vulnerable when subjected to extreme events such as earthquakes, fires, as well as frequent and increasingly unpredictable weather events.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.

现代社会的公共安全和经济稳定发展高度依赖于可靠的民用基础设施，如桥梁，隧道，核电站和高层建筑。虽然这些基础设施的设计可以运行几十年，但使用过时设计规范建造的基础设施在遭受地震、火灾以及频繁和日益不可预测的天气事件等极端事件时很脆弱。准确预测基础设施在极端负荷下的性能对于优化设计新的基础设施以及为现有基础设施制定维护和改造策略至关重要。然而，土木基础设施在极端荷载作用下的性能预测一直是一个挑战，特别是在预测基础设施的故障。这些挑战来自各种来源，例如缺乏：（1）能够复制承受极端载荷的构件的破坏过程的准确的结构构件模型;（2）关于民用基础设施竣工状况的数据;（3）能够测试承受多轴边界条件的全尺寸结构构件的测试设施;以及（4）外部载荷的固有随机性和预测模型的不确定性。该提案的主要目标是将PI研究小组开发的UT-SIM框架扩展为民用基础设施的网络物理（CP）模型框架，以应对上述挑战。为了实现这一目标，未来五年将开展四个项目：（1）大型多轴试验设备的子结构混合仿真控制方案;（2）强风或火灾下结构的鲁棒混合仿真方法;（3）基于机器学习算法和物联网传感器数据的网络模型模型更新;（4）基于机器学习算法和物联网传感器数据的网络模型更新。以及（4）与物理模型交互的大规模城市街区尺度网络模型。CP模型是混合（数值-实验）模型的概念性进展。混合模型的核心前提是数值表示的组件足够准确，但情况往往并非如此。此外，物理表示的元件的数量受到实验设施的能力的限制。在CP模型中，民用基础设施的数值模型通过使用各种物联网传感器的真实的结构或物理样本的测量进行更新，而预期在非线性范围内表现且难以进行数值建模的主要组件则用物理样本表示。拟议的研究计划和拟议的项目将导致一个模拟框架，用于准确预测民用基础设施在各种自然灾害中的表现。通过研究计划，不同的HQP将接受培训，掌握一套独特的技能，为行业做出贡献。