There is a large risk of damage, triggered by harsh ocean environments, associated with offshore structures, so structural health monitoring plays an important role in preventing the occurrence of critical and global structural failure from such damage. However, obstacles, such as applicability in the field and increasing calculation costs with increasing structural complexity, remain for real-time structure monitoring offshore. Therefore, this study proposes the comparison of cosine similarity with sensor data to overcome such challenges. As the comparison target, this method uses the rate of changes of natural frequencies before and after the occurrence of various damage scenarios, including not only single but multiple damages, which are organized by the experiment technique design. The comparison method alerts to the occurrence of damage using a normalized warning index, which enables workers to manage the risk of damage. By comparison, moreover, the case most similar with the current status is directly figured out without any additional analysis between monitoring and damage identification, which renders the damage identification process simpler. Plus, the averaged rate of errors in detection is suggested to evaluate the damage level more precisely, if needed. Therefore, this method contributes to the application of real-time structural health monitoring for offshore structures by providing an approach to improve the usability of the proposed technique.

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A realtime simulator using an explicit integration method is introduced to improve the solving performance for the dynamic analysis of a wheeled vehicle. Because a full vehicle system has many parts, the development of a numerical technique for multiple d.o.f. and ground contacts has been required to achieve a realtime dynamics analysis. This study proposes an efficient realtime solving technique that considers the wheeled vehicle dynamics behavior with full degrees of freedom and wheel contact with soft ground such as sand or undersea ground. A combat vehicle was developed to verify this method, and its dynamics results are compared with commercial programs using implicit integration methods. The combat vehicle consists of a chassis, double wishbone type front and rear suspension, and drive train. Some cases of vehicle dynamics analysis