Practical Approach for Reliability-Based Inspection Planning of Jacket Platforms Using Bayesian Networks

Abstract

This study aims to present a probabilistic framework for inspection, maintenance, and repair planning of jacket platforms based on the Bayesian probabilistic networks. To this end, considering damage and deterioration mechanisms in such a platform, some practical models are proposed to predict the extent of the damage in each element. Next, models are presented for prediction of the loads on the platform. Consequently, the condition of the structure is evaluated under the effect of damages as well as the applied loads, and the failure probabilities of structural elements are computed given their internal forces and the residual capacity of the members at the time of planning. By applying this framework, which is formulated by using Bayesian networks, it would be possible to update failure probability based on the latest information received from the inspection results or structural monitoring. Finally, the application of the proposed probabilistic Bayesian network is presented to provide an inspection plan for a sample platform and demonstrates how to incorporate the information obtained from the inspections or monitoring.