Probabilistic fatigue failure assessment of free spanning subsea pipeline using dynamic Bayesian network

The pipeline spanning is triggered by the unevenness of seabed. cyclic fatigue loadings from subsequent scouring make be prone to failure which can cause loss integrity and even catastrophic accident. However, probabilistic modeling a free subsea challenging task due its dynamic characteristics uncertain information. This paper proposes methodology that could capture uncertainty time dependence scenario pipelines. Dynamic Bayesian Network (DBN) adopted develop accident finding causations derived events. probabilities basic are estimated fuzzy set evidence theory considering their characteristics. established model accumulation pipelines over entire service life assess probability at different slices. Besides, most credible figured out diagnostic ability model. A real-field case study used demonstrate application steps developed methodology. It observed useful tool analyze risk