Open AccessA tabular optimisation technique for steel lazy wave riser
Author(s) -
Achoyamen Michael Ogbeifun,
Selda Oterkus,
Julia Race,
Harit Naik,
Dakshina Moorthy,
Subrata Bhowmik,
Julie Ingram
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1052/1/012022
Subject(s) - catenary , buoyancy , sorting , reduction (mathematics) , engineering design process , computer science , variable (mathematics) , set (abstract data type) , process (computing) , structural engineering , engineering , algorithm , mechanical engineering , mathematics , mechanics , geometry , mathematical analysis , physics , programming language , operating system
Steel lazy wave riser (SLWR) is derived from the simple catenary riser (SCR) by the installation of buoyancy modules on its section. Infinite SLWR configurations are possible, and this poses difficulties in determining the best configuration. However, it is possible to capture some suitable configurations which satisfy some given design criteria specific to a project. We referred to these as the optimum configurations for the problem. Several advanced optimization tools and techniques for engineering optimization are available. In this paper, we present a 2D tabular optimization method for SLWR, which is an index-based optimization technique. The approach reduces a multidimensional problem to a 2D type providing a significant reduction in the required computational resources. It combines the design variables in pairs and assigns indices to the resulting design points (configurations) for each combination. The optimum design points are then tracked through index matching using techniques such as data sorting and intersection operations. In the application of the technique to SLWR design, we set the number of design variable for the problem to three. This results in three pair of combinations of the design variables. The design variables are the apparent mass ratio, the sag bend elevation, and the arc height. The output variables of interest to be optimized include the SLWR hanging length, the smeared buoyancy section length, the smeared buoyancy thickness, the riser hang-off tension, the stress utilization and fatigue damage around the bends. Selected optimum SLWR configurations from the optimization process are subjected to an irregular wave simulation to demonstrate the suitability of the approach for such optimisation problems.