Macro-Scale Digital Twin of High-Rise Building with Interlayer Flexible-Shear Coupling Model

In the context of the development of smart city construction, and in response to the technical needs of digital disaster prevention and scientific management of civil engineering structures, the application of digital twins in high-rise buildings provides an efficient solution for the safe construction and the tracking and evaluation of service status. The simulation accuracy and efficiency of virtual model to physical entity and model updating method based on monitoring data are the key issues to realize digital twin of high-rise buildings. In this paper, a macro-scale digital twin method for high-rise structures is proposed based on modal monitoring data and flexural shear coupling model considering the action of transverse members. Firstly, the deformation of the floor boundary node of a typical high-rise frame structure is analyzed, and the influence of the bending moment resistance of the transverse members on the overall bending dynamic characteristics of the floor is explored. A new three-dimensional macro-scale floor model of high-rise structure considering the action of transverse members is established by using spring components. Artificial neural network combined with simulated modal monitoring data is used to identify parameters of the macro-scale model, so as to realize the macro-scale digital twin of high-rise structures. Compared with the full-order model, the macro-scale model only uses a small number of coefficients to characterize the dynamic characteristics of the whole high-rise structure, and the calculation amount and storage capacity are significantly reduced, which provides an efficient technical path for the data mapping and digital twin model updating of the structural health monitoring system.