Reliability and integrity management of ocean structures

Corrosion is a major cause of deterioration in marine and offshore structures. It affects the life of process equipment and pipelines. Over the time corrosion can result in structural failure, leakage, product loss, environmental pollution, and the loss of life. Pitting corrosion is regarded as one of the most hazardous forms of corrosion it causes structural failure and its effects on offshore structures are reported to be catastrophic. Hence, significant attention should be given to predict the occurrence of pitting corrosion in offshore structures and the adequate measures should be taken to prevent as well as control the consequences. Pitting corrosion has been studied for several decades and considerable understanding of the pitting phenomenon has been learned. However, in depth knowledge of pitting modelling and pitting measurement is still lacking. This thesis advances these developments by proposing several novel extensions in the areas and provides a complete package. This thesis is also aimed to make a distinctive contribution within the area of safety and reliability of offshore structures susceptible to pitting corrosion. This thesis contains seven chapters. The first chapter provides the introduction and general structure of the thesis. In the second chapter, a highly systemized and thorough literature review on pitting corrosion was completed and the knowledge gaps were identified. This chapter reviews and analyses the current understanding of the pitting corrosion mechanism and investigates all possible factors that can cause pitting corrosion. Furthermore, different techniques employed by scientists and researchers to identify and model the pitting corrosion are also reviewed and analysed. The third chapter presents a development of a novel methodology for an optimum maintenance programme by integrating a dynamic RBM based reliability approach with risk assessment strategy. The developed methodology is applied to a case study involving an offshore oil and gas production facility. The application of the methodology has proven to be a high degree of prediction capability, which increase the reliability of the equipment and also optimizes the cost of maintenance. A sensitivity analysis proved that pitting corrosion is a predominant and critical factor for structural deterioration. While the fourth chapter proposes a novel probabilistic methodology to precisely predict the depth of pitting corrosion for structural steel in marine and offshore environments. The propose Bayesian network model combines an understanding of corrosion phenomenological model and empirical model calibrated using real-world data. A case study, which exemplifies the application of methodology to predict the pit depth of structural steel in long-term marine environment, is also presented in fourth chapter. The result shows that the proposed methodology succeeds in predicting the time-dependent, long-term anaerobic pitting corrosion depth of structural steel in different environmental and operational conditions. In the fifth chapter, an accelerated laboratory experiment for pitting corrosion was conducted in order to understand the practical significance of pitting mechanism, and to realistically predict the long-term service life of the steel structures. A series of pitting corrosion tests on stainless steel specimen with different thickness were conducted and data were statistically evaluated. This chapter also presents the modified ASTM G48 procedure. Similarly, the sixth chapter presents an experimental and numerical modelling of the stainless-steel specimen with varying thickness subjected to different level of pitting corrosion deterioration are considered. Numerical investigations using Finite Element Analysis (FEA) were performed using corroded and un-corroded steel specimen to predict the ultimate tensile strength, thereby for casting its prevention for the pitting corrosion degradation. The ultimate strengths for both intact and corroded specimen obtained using numerical method are validated with experimental data. The numerical analysis proved to produce excellent result with minimal difference when comparing with experimental result. Finally, chapter 7 includes the conclusions of the thesis.