海底管道
降级(电信)
可靠性工程
概率逻辑
计算机科学
法律工程学
环境科学
工程类
岩土工程
人工智能
电信
作者
Mark Manzocchi,Bryan Horton,Nicolas Rooms,Jeremy Evans,Oluwole Fajuyitan,Alexander William Macdonald
标识
DOI:10.1115/omae2024-128159
摘要
Abstract The integrity of offshore structures subjected to degradation depends on the structures’ system capacity and the applied loading through time. Inspections are used to establish the current condition of degrading components. Inspection plans can be developed through application of risk-based inspection methodologies using, for example, the guidance given in ISO 19901-9 [1]. Inspections give information on the condition of the members inspected. The detail of the information about weld condition depends on the inspection method: Flooded member detection gives information on the presence of through-thickness cracks; detailed non-destructive inspection such as ultrasonic inspection identifies defects based on their size; and structural monitoring detects brace severance. As ageing structures are life-extended, semi-quantitative Risk Based Inspection (RBI) methods can result in onerous and sometimes impractical levels of weld fatigue Non-destructive Testing (NDT) inspections. There is a need to refine the inspection plan using a quantitative method which can directly calculate the impact of inspection plans in terms of their influence on the probability of platform collapse. The present study outlines a Monte Carlo Simulation (MCS) based probabilistic assessment methodology for inspection planning of offshore jacket structures. The method calculates the probability of collapse of a jacket structure when subjected to the combined effects of the time-dependent fatigue degradation of structural elements, characterized by member severance, leading to reduced jacket strength, and collapse when the degraded jacket is subjected to extreme metocean loading. The outcomes of in-service weld inspections and online structural monitoring are incorporated into the probabilistic assessment by applying Bayesian updating based on no-find inspection results and probability of detection relationships. The dates and scope of future inspections may be planned by calculating the probability of collapse at future time conditional on no-find inspection and monitoring outcomes. The inspections and monitoring plans are developed to ensure the probability of structural collapse or unacceptable levels of widespread fatigue damage is maintained below acceptable quantified risk-based targets. The method generates sequences of fatigue failures using Monte-Carlo simulation and weld fatigue life probability distributions. Allowance is made for the redistribution of fatigue loading throughout the structure during the member fatigue failure sequences. The method takes advantage of the redundancy afforded by the structural system and the method is currently applicable to offshore jacket-type structures. However, it could be extended to ship-shaped and other floating type structures. Given the limited redundancy of offshore wind turbine structures this methodology is not applicable. A case study example is presented describing the motivation for the use of this method as well as the updates to the inspection plans justified by the results. The approach outlined is a useful method for quantitatively planning inspections of late-life offshore jacket structures that can be applied by practicing engineers responsible for structural integrity management and/or life extension.
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