A model for the computation of failure probabilities for partly reshaping mass-armored berm breakwaters in the Arctic is presented. The model consists of a reliable tool for the design of port structures in the rapidly changing Arctic environment and considers the simultaneous effects of wave and ice forces.
The applied probabilistic approach was based on Bayesian inference. Hydrodynamic and ice historical data from Prudhoe Bay, Alaska were collected and analyzed to supply the Bayesian network with a large pool of information for the analysis. The model performed real-time predictions based on historical data and the user’s prior knowledge and assigned relevant values to load and resistance parameters. The predictive skill of the Bayesian network was validated with log-likelihood tests. Furthermore, the main outputs were applied for a Level III (fully probabilistic) reliability assessment of the structure.
The study shows that a well-formulated Bayesian network can be a powerful tool in the design process and for the purpose of reliability analysis of coastal structures in highly unpredictable environments, such as the Arctic. The model can represent the dependencies between wave and ice loads in relation to the characteristics of the breakwater, as well as, its response. The average deviation of computed probabilities of failure relative to the prior estimates was 58.7%.