Practical Approach for Reliability-Based Inspection Planning of Jacket Platforms Using Bayesian Networks
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 6, Issue 3
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.
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Data Availability Statement
Some or all data, models, or code generated or used during the study are available from the corresponding author by request. These items include:
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All code for the generation of wave force and BN Learning
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Data for Corrosion loss
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Finite-element model of jacket
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Information & Authors
Information
Published In
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 6 • Issue 3 • September 2020
Copyright
©2020 American Society of Civil Engineers.
History
Received: Aug 2, 2019
Accepted: Mar 9, 2020
Published online: Jun 11, 2020
Published in print: Sep 1, 2020
Discussion open until: Nov 11, 2020
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