ALTERNATIVE METHODOLOGIES FOR SUBSEA FLEXIBLE STRENGTH ANALYSIS

摘要

This paper presents a study of the analysis methodologies used to predict the most likely response of flexibles in a subsea environment, with the aim of determining an efficient and reliable prediction methodology. The most accurate method involves simulating multiple wave realisations of a real world sea state, i.e. irregular waves, and post-processing the results to determine the most probable maximum (MPM). Due to the computationally intensive nature of this approach, however, regular wave analysis is typically used to determine flexible response. This approach considers the maximum wave within a design storm at a desired period; the choice of periods may leave room for uncertainty in the conservatism of the approach. With proper screening, regular wave analysis can be a valid yet overly conservative approach resulting in over design and additional cost. However, if screened incorrectly, there is a possibility that the choice of periods could give results that are under conservative. In addition to regular wave analysis, the paper presents two alternative methodologies to determine the most likely response, with the focus on reducing the computational resources required. The first alternative is an 'Irregular Wave Screen' approach in which the wave train is screened at areas of interest for waves within a user defined threshold of the maximum wave height, in addition to other user defined parameters. Only waves within these parameters are simulated to determine responses. The second alternative is the 'New Wave' approach, which models the most probable wave elevation around the maximum wave crest. The calculated new wave is then placed at the desired location to determine responses. The responses of the Regular, Irregular Wave Screen and New Wave methodologies are compared with the Irregular MPM approach to determine their feasibility to predict the response of flexibles in a real world irregular sea state with lower computational requirements.