Abstract
Probabilistic risk-based approaches have been used for cost-effective structural design and maintenance guidelines. The effectiveness of these provisions, however, has yet to be adequately validated. Also, current risk management approaches are hardly adaptable to changes in operational and environmental conditions as well as structural properties over the service life of structures. As the need and demand of real-time monitoring systems have increased dramatically for high-value and high-risk facilities such as offshore structures particularly, it is important to discuss directions for future research to advance the risk-based management approaches by utilizing the invaluable “big-scale” field data obtained from sensor network systems. Therefore, knowledge gaps in the current state-of-the-art structural risk management approaches are discussed in this paper. Subsequently, a novel risk management framework is presented in this paper integrating physics-based data into a data-driven decision model. The proposed decision framework will improve system adaptability to future performance requirements due to changing operational and environmental conditions and will be applicable to any structural systems instrumented by sophisticated SHM systems such as complex naval and marine systems.
