Numerical and Experimental Analysis of Extreme Slamming Loads on FPSO Bows

A practical method for prediction of slamming loads and structural responses in the bow of an FPSO is presented. Incoming waves are simulated by a second-order random wave model, which describes the water elevation and kinematics. Vessel motions are calculated by linear analysis. The diffracted wave field is calculated taking into account linear 3D diffraction. Relative motions are then estimated by combining the linear vessel motions, second-order incoming waves and linear diffraction. The relative motions and velocities at the bow are used as input to numerical slamming calculations. The bow is divided into 2D sections and a boundary value problem is solved for each section applying the generalized Wagner-method of Zhao & Faltinsen (1993) and Zhao et al (1996). The 2D slamming calculations account for the local pile-up of water on each side of the section during impact. Structural responses are calculated from a finite-element model of the bow using the exact pressure distribution from the slamming calculations. This is achieved by automatic mapping of pressures onto the outer surface of the FE-model and performing a quasi-static structural analysis for each time-step. The methods are implemented into a package of computer tools, allowing the user to perform the various steps in the process with little manual editing of data. The system runs easily on a standard PC. Measurements on a 1:55 scaled model of an FPSO are used for validation of the bow slamming calculations. The model was equipped with five 3.85m × 1.65m (full-scale) panels in the upper part of the bow for slamming force measurements. The tests were run in storm conditions with steep waves. The calculated slamming force on a panel located at the foremost tip of the bulwark, 12.8 meters above the mean waterline, is compared with measured results for selected extreme slamming events. Considering the complexity of this problem and the relative simplicity of the approach, the agreement is very good.