Journal
CHINA OCEAN ENGINEERING
Volume 34, Issue 5, Pages 597-607Publisher
CHINA OCEAN PRESS
DOI: 10.1007/s13344-020-0054-0
Keywords
structure resilience; structure system; remaining useful life; dynamic Bayesian networks
Funding
- National Natural Science Foundation of China [51779267]
- Taishan Scholars Project [tsqn201909063]
- Science and Technology Support Plan for Youth Innovation of Universities in Shandong Province [2019KJB016]
- National Key Research and Development Program of China [2019YFE0105100]
- Fundamental Research Funds for the Central Universities
- Opening Fund of National Engineering Laboratory of Offshore Geophysical and Exploration Equipment [20CX02301A]
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Under unanticipated natural disasters, any failure of structure components may cause the crash of an entire structure system. Resilience is an important metric for the structure system. Although many resilience metrics and assessment approaches are proposed for engineering system, they are not suitable for complex structure systems, since the failure mechanisms of them are different under the influences of natural disasters. This paper proposes a novel resilience assessment metric for structure system from a macroscopic perspective, named structure resilience, and develops a corresponding assessment approach based on remaining useful life of key components. Dynamic Bayesian networks (DBNs) and Markov are applied to establish the resilience assessment model. In the degradation process, natural degradation and accelerated degradation are modelled by using Bayesian networks, and then coupled by using DBNs. In the recovery process, the model is established by combining Markov and DBNs. Subsea oil and gas pipelines are adopted to demonstrate the application of the proposed structure metric and assessment approach.
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