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Abstract
The work proposes a probabilistic-driven framework for enhanced corrosion estimation of ship structural components using Bayesian inference and limited measurement data. The new approach for modelling measurement uncertainty is proposed based on the results of previous corrosion tests that incorporate the non-uniform character of the corroded surface of structural components. The proposed framework's basic features are outlined, and the detailed algorithm is presented. Further, the proposed framework is validated by comparison with the classical statistical approach and mass measurements, considering previous experimental work results. Notably, the impact of the number of measuring points is investigated, and the accuracy index is proposed to identify the optimum number of measurements. The developed framework has a significant advantage over the classical approach since measuring uncertainty is incorporated. Additionally, the confidence intervals of both mean value corrosion depth and standard deviation could be gathered due to the probabilistic character of the framework. Thus, the presented approach can potentially be used in the structural health monitoring of ship structural components and reliability analysis.
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Full text
- Publication version
- Accepted or Published Version
- DOI:
- Digital Object Identifier (open in new tab) 10.1016/j.ress.2023.109721
- License
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Details
- Category:
- Articles
- Type:
- artykuły w czasopismach
- Published in:
-
RELIABILITY ENGINEERING & SYSTEM SAFETY
no. 242,
ISSN: 0951-8320 - Language:
- English
- Publication year:
- 2024
- Bibliographic description:
- Wołoszyk K., Garbatov Y.: A probabilistic-driven framework for enhanced corrosion estimation of ship structural components// RELIABILITY ENGINEERING & SYSTEM SAFETY -,iss. 242 (2024), s.109721-
- DOI:
- Digital Object Identifier (open in new tab) 10.1016/j.ress.2023.109721
- Sources of funding:
-
- Free publication
- Verified by:
- Gdańsk University of Technology
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