In this paper, A high-order response surface method is proposed for finite element model updating of continuous beam bridges. Firstly, based on visual inspection and environmental vibration testing, the peak picking (PP) method and random subspace identification (SSI) method are used to identify the dynamic characteristic parameters of the structure. Then, the finite element model of the continuous beam bridge is updated based on the third-order response surface method. It can be concluded that the results of the updated finite element model are in good agreement with the test results, and the maximum error between the calculated and measured frequency is less than 3%, with MAC values greater than 85%. Moreover, the updated finite element model can reflect the current situation of real bridges and serve as the basis for bridge health monitoring, damage detection, and safety assessment.

As an essential reference to bridge dynamic characteristics, the identification of bridge frequencies has far-reaching consequences for the health monitoring and damage evaluation of bridges. This study proposes a uniform scheme to identify bridge frequencies with two different subspace-based methodologies, i.e., an improved Short-Time Stochastic Subspace Identification (ST-SSI) method and an improved Multivariable Output Error State Space (MOESP) method, by simply adjusting the signal inputs. One of the key features of the proposed scheme is the dimensionless description of the vehicle–bridge interaction system and the employment of the dimensionless response of a two-axle vehicle as the state input, which enhances the robustness of the vehicle properties and speed. Additionally, it establishes the equation of the vehicle biaxial response difference considering the time shift between the front and the rear wheels, theoretically eliminating the road roughness information in the state equation and output signal effectively. The numerical examples discuss the effects of vehicle speeds, road roughness conditions, and ongoing traffic on the bridge identification. According to the dimensionless speed parameter S_v1 of the vehicle, the ST-SSI (S_v1 < 0.1) or MOESP (S_v1 ≥ 0.1) algorithm is applied to extract the frequencies of a simply supported bridge from the dimensionless response of a two-axle vehicle on a single passage. In addition, the proposed methodology is applied to two types of long-span complex bridges. The results show that the proposed approaches exhibit good performance in identifying multi-order frequencies of the bridges, even considering high vehicle speeds, high levels of road surface roughness, and random traffic flows.

Adjacent buildings with anticollision system would have the possibility of pounding under earthquake if there is insufficient separate distance between the two buildings. The effect of pounding and earthquake characters on the optimum parameters for anticollision system is studied through time‐history analysis method in this paper. Interstory displacement ratio, energy consumption ratio, and the total strain energy of the two buildings are considered as control variables. The results show that the pounding between adjacent buildings will reduce the range of optimum parameters, and earthquake characters also have effect on the selection of optimum parameters. Therefore, it is strongly recommended to input more than three ground motion records for a time‐history analysis to get the optimum parameters considering the effect of pounding and earthquake characters.

Smart buildings represent a significant trend in the future of the construction industry. The performance of human-computer interaction plays a vital role in achieving this from a human perspective. H...