Coupled analysis of floating production systems

Fully coupled global analysis of Floating Production Systems, including the vessel, the mooring system and the riser system is described. Design of the system can be a daunting task, involving more than 1000 load cases for global analysis. The primary driver for the mooring system and for the riser system is motion of the vessel. Vessel motions are driven by environmental forces, but are restrained by forces from the mooring and riser systems. Numerical models and procedures that provide accurate and efficient global modeling of the Floating Production System are presented. Both Time Domain and Frequency Domain procedures are included. The accuracy and efficiency of the procedures are illustrated in an example: a large semi with 16 mooring lines and 20 risers. The procedures provide the accuracy and efficiency for use of fully coupled analysis in design of Floating Production Systems from concept selection to final design, installation and operation.     

Neural networks in the dynamic response analysis of slender marine structures

Risers and anchor lines play important roles in offshore oil exploitation activities nowadays. For this reason the proper analysis and design of such slender structures has been of a paramount interest. The principal characteristics to be accounted for in riser and mooring line analysis are the severe nonlinearities involved and the random dynamic effects associated. The Finite Element Method (FEM) is an essential step to cope with this kind of analysis. But the use of the FEM can be computationally very expensive for the solution of the resultant nonlinear differential equations of motion, because the time-domain integration should produce sufficiently long response time-histories using small time-steps in order to obtain reliable time-series statistics of any structural response parameter, e.g., top tension in an anchor line or stresses occurring at a critical section in a steel catenary riser (SCR). This paper presents a very efficient hybrid Artificial Neural Network (ANN)–Finite Element Method (FEM) procedure to perform a nonlinear mapping of the current and past system excitations (inputs) to produce subsequent system response (output) for the random dynamic analysis of mooring lines and risers. Firstly, a quite short FEM-based time-domain response simulation is generated. Then, an ANN is used to predict the remaining structural response time-history simulation. The hybrid ANN–FEM approach can be very efficient for predicting long response time-histories. It has been observed that a 3 h response time-history can accurately be obtained with approximately the computational cost of a 500 s one, i.e., 20 times faster than a complete simulation using finite element-based solution. Roughly, this can represent a reduction of about a dozen of hours of computer time for a single mooring line analysis and about two dozens of hours (or more) for a single SCR analysis, both belonging to a deep-water floating unit.     

Extending a time/frequency domain hybrid method for riser fatigue analysis

Fully coupled time domain analysis of a floating system is rigorous but time-consuming, thus an efficient hybrid method was developed in a prior work. The method simulates the coupled slow-drift responses in the time domain and analyzes the wave-frequency dynamics in the frequency domain. The hybrid method was shown to compare well with time domain analysis in predicting the mean-square vessel motions and line tensions. In this paper, the hybrid method is extended for the fatigue analysis of moorings and risers. The fatigue damage thus calculated is found to closely agree with the result from time domain analysis in conjunction with rainflow counting. Several spectral fatigue techniques are also compared, and these methods are significantly less accurate, thus attesting to the complexity of the problem.