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

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 While these infrastructures are designed to be operational for several decades, infrastructures constructed with outdated design codes are vulnerable when subjected to extreme events such as earthquakes, fires, as well as frequent and increasingly unpredictable weather events.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