Structural health monitoring (SHM) systems have been developed to evaluate structural responses to extreme events such as natural and man-made hazards. Additionally, the increasing volume of users and vehicle sizes can lead to the sudden damage and collapse of bridge structures. Hence, structural monitoring and dynamic characteristic analyses of bridge structures are critical and fundamental requirements for bridge safety. SHM can overcome the weaknesses of visual inspection practices, such as lack of resolution. However, because of computational limitations and the lack of data analysis methods, substantial quantities of SHM data have been poorly interpreted. In this paper, the SHM of bridges based on dynamic characteristics is used to assess the "health state" of bridge structures. A comprehensive SHM system using vibration-based techniques and modal identification for bridge structures are well defined. Some advanced concepts and applications regarding bridge safety evaluation methods, including damage detection and load-carrying capacity, are reviewed. For the first time, the pros and cons of each vibration technique are comprehensively evaluated, providing an advantage to the authority or structural owner when developing a bridge management database. This information can then be used for continuous structural monitoring to access and predict the bridge structure condition.

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Total knee replacement has become a viable option for treating severe knee arthritis. The demand for more kinematically functional implants that better replicate natural knee kinematics led to the development of total knee arthroplasty (TKA), including bi-cruciate-retaining (BCR) TKA. However, optimised design parameters of BCR TKA knee implants that can help achieve a long-term prosthetic survival rate remain unknown. Therefore, this study aimed to investigate the effect of the design parameters of BCR TKA knee implants on the mechanics of knee joints and optimise and individualise the knee implant design parameters using the Taguchi method incorporating finite element analysis. Herein, experimental factors and levels were selected and nine finite element models of BCR TKA knee implants were developed to optimise the design of the following parameters: the curvature ratio on the sagittal plane, curvature ratio on the coronal plane, and tibial slope. In addition, finite element analysis was used to determine the effect of the design parameters on the peak contact stress on ultra-high-molecular-weight polyethylene (UHMWPE) and its deformation. Consequently, among the three parameters that affect the peak contact stress and its deformation, the curvature ratio on the sagittal plane had the greatest effect (range = 10.96), followed by the curvature ratio on the coronal plane (range = 3.54), and the tibial slope (range = 2.56). The optimal design parameters for the BCR TKA knee implant were a curvature ratio of 1.5 on both the sagittal and coronal planes and a tibial slope of 5°. Under these conditions, the peak contact stress and deformation were 25.80 MPa and 0.0835 mm, respectively. The optimisation method based on finite element analysis and the Taguchi method can produce one of the highest-performing BCR TKA knee implant designs, thereby reducing the peak contact stress and deformation. This method sheds fresh light on the development of the BCR TKA knee implant as well as biomechanical decision-making to implant the TKA prosthesis correctly.

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