Real-Time Hybrid Testing (RTHT) requires the numerical substructure calculations to be completed within the defined integration time interval due to its real-time loading demands. For solving the problem, A Real-Time Hybrid Testing based on Restart-Loading Technology (RTHT-RLT) is proposed in this paper. In the proposed method, in case of the numerical substructure calculations cannot be completed within the defined integration time interval, the experimental substructure was returned back to the initial state statically. When the newest loading commands were calculated by the numerical substructure, the experimental substructure was restarted loading from the initial state to the newest loading commands so as to precisely disclosing the dynamic performance of the experimental substructure. Firstly, the methodology of the RTHT-RLT is proposed. Furthermore, the numerical simulations and experimental tests on one frame structure with a viscous damper are conducted for evaluating the feasibility and effectiveness of the proposed RTHT-RLT. It is shown that the proposed RTHT-RLT innovatively renders the nonreal-time refined calculation of the numerical substructure feasible for the RTHT. The numerical and experimental results show that the proposed RTHT-RLT exhibits excellent performance in terms of stability and accuracy. The proposed RTHT-RLT may have broad application prospects for precisely investigating the dynamic behavior of large and complex engineering structures with specific experimental substructure where a restarting procedure does not affect the relevant hysteretic response.

Servo-motor driven uniaxial shake tables have been widely used for education and research purposes in earthquake engineering. These shake tables are mostly displacement-controlled by a digital proportional-integral-derivative (PID) controller; however, accurate reproduction of acceleration time histories is not guaranteed. In this study, a control strategy is proposed and verified for uniaxial shake tables driven by a servo-motor. This strategy incorporates a deep-learning algorithm named Long Short-Term Memory (LSTM) network into a displacement PID feedback controller. The LSTM controller is trained by using a large number of experimental data of a self-made servo-motor driven uniaxial shake table. After the training is completed, the LSTM controller is implemented for directly generating the command voltage for the servo motor to drive the shake table. Meanwhile, a displacement PID controller is tuned and implemented close to the LSTM controller to prevent the shake table from permanent drift. The control strategy is named the LSTM-PID control scheme. Experimental results demonstrate that the proposed LSTM-PID improves the acceleration tracking performance of the uniaxial shake table for both bare condition and loaded condition with a slender specimen.

Box girder bridges are now widely used in bridge construction, and it is necessary to perform load rating regularly to evaluate the load capacity of box girder bridges. Load testing is a common measure for load rating. However, the bridge must be loaded by many trucks under different loading conditions, which is time-consuming and laborious. To solve this problem, this paper proposes a load rating method for box girder bridges based on rapid moving loads testing. The method includes three steps. First, the quasi-influence factors of the bridge are obtained by crossing the bridge with rapidly moving loads, and the structural modal parameters are simultaneously obtained from the dynamic data to supplement. Second, an objective function is constructed, consisting of the quasi-influence factors at several measurement points and structural modal parameters. The finite element model for load rating is then updated based on the Rosenbrock method. Third, on this basis, a load rating method is proposed using the updated model. The load rating method proposed in this paper can considerably reduce the time duration of traditional static load testing and effectively utilize the dynamic and static properties of box girder bridges to obtain an accurate finite element model. The load capacity obtained based on the updated model can avoid the inconsistency of the evaluation results for the different structural members using the adjustment factors specified in codes.

Energy harvesting in trams may become a prevalent source of passive energy generation due to the high density of vibrational energy, and this may help power structural health monitoring systems for the trams. This paper presents a broadband vibrational energy harvesting device design that utilizes a varied frequency from a tram vehicle using a 2 DOF vibrational system combined with electromagnetic energy conversion. This paper will demonstrate stepwise optimization processes to determine mechanical parameters for frequency tuning to adjust to the trams' operational conditions, and electromagnetic parameters for the whole system design to maximize power output. The initial optimization will determine 5 important design parameters in a 2 DOF vibrational system, namely the masses (m₁, m₂ (and spring constants (k₁, k₂, k₃). The second step will use these parameters as initial guesses for the second optimization which will maintain the ratios of these parameters and present electrical parameters to maximize the power output from this system. The obtained values indicated a successful demonstration of design optimization as the average power generated increased from 1.475 mW to 17.44 mW (around 12 times).

Recently, hybrid and electric vehicles have been actively developed to replace internal combustion engine (ICE) vehicles. However, their vibrations and noise with complex spectra cause discomfort to drivers. To reduce the vibrations transmitted through primary excitation sources such as powertrains, structural changes have been introduced. However, the interference among different parts is a limitation. Thus, active mounting systems based on smart materials have been actively investigated to overcome these limitations. This study focuses on diminishing the source movement when a structure with two active mounting systems is excited to a single sinusoidal and a multi-frequency signal, which were investigated for source movement reduction. The overall structure was modeled based on the lumped parameter method. Active vibration control was implemented based on the modeled structure, and a multi-normalization least mean square (NLMS) algorithm was used to obtain the control input for the active mounting system. Furthermore, the performance of the NLMS algorithm was compared with that of the quantification method to demonstrate the performance of active vibration control. The results demonstrate that the vibration attenuation performance of the source component was improved.