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Results
Sloshing Load Assessments for a Midscale Single-Row FLNG
Kwon, Chang Seop (Central Research Institute, Samsung Heavy Industries Co. Ltd.) | Kim, Hyun Joe (Central Research Institute, Samsung Heavy Industries Co. Ltd.) | Park, Jong Jin (Central Research Institute, Samsung Heavy Industries Co. Ltd.) | Lee, Dong Yeon (Central Research Institute, Samsung Heavy Industries Co. Ltd.) | Kim, Booki (Central Research Institute, Samsung Heavy Industries Co. Ltd.) | Kim, Yonghwan (Seoul National University)
The application of the single-row arrangement system into a midscale floating production unit of liquefied natural gas platform is introduced based on numerical and experimental studies on sloshing load. An increased lower chamfer height is applied to reduce sloshing impact load. Wave scatter diagrams and extreme sea states at North West Australia are considered. In addition, the wave height limitation in offloading operation is taken into account. A sloshing severity index is calculated and compared with sloshing model test results. Sloshing pressure distributions are derived from proposed computational fluid dynamics (CFD) analysis, and the results are compared with those of model tests.
- Asia (0.69)
- North America > United States > California > San Francisco County > San Francisco (0.28)
- Energy > Oil & Gas > Midstream (1.00)
- Transportation > Marine (0.96)
Determination of Roll Damping Coefficients for an FPSO Through Model Tests and CFD Analysis
Kwon, Chang Seop (Samsung Heavy Industries Co. Ltd.) | Kim, Hyun Joe (Samsung Heavy Industries Co. Ltd.) | Jung, Dong Woo (Korea Research Institute of Ships and Ocean Engineering) | Lee, Sung Wook (Korea Maritime and Ocean University)
Abstract The purpose of this study is to provide a guideline to estimate the damping coefficient for a box-shaped Floating Production Storage and Offloading (FPSO) under various loading conditions and bilge keel heights through model tests and Computational Fluid Dynamics (CFD) analysis. A series of free roll decay model tests is carried out under various conditions for parameters such as the draft, metacentric height (GM), radius of gyration, and bilge keel height. 3D CFD simulations are carried out and 6DOF motion of the FPSO is realized through the employment of the overset mesh technique. The effects of the loading condition and bilge keel height on the roll damping performance of a box-shaped FPSO and a prediction method of roll damping through the use of CFD simulations are discussed in detail. Introduction As FPSOs are operated under various loading conditions, the motion responses for each loading condition should be investigated. The roll damping is essential for the accurate prediction of the motions at initial and detailed design phases. Ikeda (1976) and Himeno (1981) extensively investigated the empirical roll damping prediction method. Prediction based on a database from previous projects may be a practical solution, but the available database for box-shaped FPSOs is quite limited. Recently, Computational Fluid Dynamics (CFD) solvers have been applied to investigate the roll damping. Atluri (2009) computed hydrodynamic coefficients of oscillating bodies by CFD and validated the method on a flat plate. The roll damping for sharp and rounded bilges of a 2D rolling hull section was studied by Jaouen (2011). Veer and Fathi (2011) investigated the roll damping of a converted FPSO with riser balcony and bilge keels through CFD analysis. Additionally, Veer et al. (2012) investigated a validated methodology to calculate the oscillatory loads on bilge keels of ships operating in irregular sea states through the numerical and experimental studies. Yan (2013) studied the effect of bilge keel tip configuration on the normal force acting on the bilge keel through CFD. Thilleul (2013) investigated the turbulence model effect on the drag force acting on a circular cylinder in oscillatory flow.
- Europe (0.68)
- North America > United States (0.68)
Prediction of Course Stability of Towed Offshore Structures by Computational Fluid Dynamics
Kwon, Chang Seop (Korea Advanced Institute of Science and Technology) | Kwon, Oh Joon (Korea Advanced Institute of Science and Technology) | Lee, Sung Wook (Samsung Heavy Industries Co. Ltd.) | Kim, Hee Taek (Samsung Heavy Industries Co. Ltd.)
The purpose of this research is to find practical methods to predict the course stability of towed offshore structures at the initial design stage. The equilibrium yaw angles of a towed Floating Production Storage and Offloading (FPSO) with a single skeg and twin skegs are predicted by a drift model test and a Computational Fluid Dynamics (CFD) analysis. The results are compared with the towing model test results. Additionally, CFD towing simulations are performed and validated, and the mechanism of instability is analyzed through an investigation of physical quantities obtained from the CFD simulations. Introduction The demand for offshore structures such as Floating Production Storage and Offloadings (FPSOs) and semi-submersibles has increased in order to develop offshore oil and gas fields. Offshore structures constructed at shipyards should be transported safely to the oil fields. They are generally towed by several tugboats and towing lines. Defined as whether the towed offshore structure follows the desired course of the tugboats, the course stability is one of the indices for safe transportation. If the course stability is not secured enough, it will be difficult to keep the course, and eventually the overall transportation may fail in the worst case. If the transportation fails, the risk of collision with other vessels or geographic features increases, which may lead to damage to the towed offshore structure or even a catastrophic oil spill. Governed by the submerged hull form, the hydrodynamic characteristics can change the course stability. In other words, transportation safety starts from the design stage of the hull form. Therefore, the prediction of the course stability is one of the most important aspects of the design and engineering of offshore projects. Much research has been done on the prediction of the course stability. Strandhagen et al. (1950) investigated the course stability criteria for the towed vessels using the Routh-Hurwitz stability criterion. Bernitsas and Kekridis (1985) suggested the discriminant using characteristic equations derived from the equations of motion of the towed vessel. As of now, the prediction of the course stability of towed vessels at the design stage heavily depends on the model tests in marine industries. Latorre (1988) investigated the scale effect on the course stability of towed barges. He found that the model resistance was larger than the full-scale resistance. On the basis of his findings, he indicated that the model barge might overesti mate the course stability compared to the full-scale barge due to the scale effect. You (2000) carried out the towing model tests for a tanker ship and an FPSO. He found that the FPSO achieved better course stability than the tanker. Jung et al. (2005) performed the towing model tests to investigate the bow shape effect on the course stability of FPSOs. Two different types of bow shapes were tested: a barge bow shape and a spoon bow shape. It was found that the barge bow shape obtained better course stability than the spoon bow shape. Yang and Hong (2006) carried out extensive towing model tests for different stern hull shapes, skegs, and bilge radii for an FPSO. Kwon (2007) performed the towing model tests for the forward blocks of container ships and tankers. The towing model tests showed that the container blocks were towed with a fishtailing motion. Yang et al. (2011) investigated the interactions between a tugboat, tow lines, and a towed vessel through two different modelings of tugboats, in which the FPSO model was directly towed by a carriage and towed by a free-sailing tug model. As previously mentioned, the model test is widely used for its reliability, but there are many limitations such as time, cost, measurements, and test facilities. It is also extremely difficult to redesign the hull form after the model test by reason of the poor course stability since the basic design is nearly finished at the model test stage. More importantly, it is difficult to understand the resulting instability with limited data from the model test.
- Transportation > Marine (1.00)
- Energy > Oil & Gas > Upstream (1.00)