International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP) (12th : 2015)

Bayesian networks for model updating inspection support of marine structures subject to fatigue Groden, Mark D.; Collette, Matthew D.

Abstract

There is significant uncertainty in the structural health and resulting capabilities of a marine structure during service life. Design-stage marine structural engineering models offer limited information on the as-built structure’s health during its service life. Despite copious amounts of data provided by structural monitoring techniques, synthesizing these different data types to offer support in decision making for inspection remains challenging and underexplored. A Bayesian network data to decision framework fusing through-life inspection data with design-stage fatigue calculations is demonstrated to afford data fusion and inspection extent decision support. Using parametric encoding for a Weibull pressure distribution governing cyclic loading, and a lognormal probabilistic fatigue initiation model, the network represents a large stiffened metallic grillage with fatigue-critical details typical of a marine structure. Updating is performed with inspection observation and maximum strain values. Extension of the Bayesian network to an Influence Diagram with utility and decision nodes offers inspection extent decision support. The ability of the network approach to provide reasonable inspection guidance and forecast of future structural performance is tracked for different evidence sets. Recommendations for adapting the network approach for fatigue life support are drawn based on the systematic study conducted.

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Attribution-NonCommercial-NoDerivs 2.5 Canada

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