Reliability Analysis of a Steel Catenary Riser With Environmental, Geometry, and Operational Uncertainties
Steel Catenary Riser (SCR) offers an attractive solution to deepwater floating structure due to its economical effectiveness, large diameters, high resistance to internal and external pressure, simple and robust installation methods. SCR forms a prolongation of a subsea flowline attached to a fixed platform or a floating unit in a catenary shape. Due to the relatively large motion under waves and currents, SCR lines are sensitive to dynamic effects and vulnerable to damage in deep water. They are commonly subjected to high top tension and large bending moment due to platform or FPSO movements which may lead to fatigue damage. There are many uncertainties that can affect the safety and cost-effectiveness of the SCR. Offshore design codes typically adopt empirical safety factors to account for these uncertainties but this approach does not permit the prediction of failure probability of the riser system. To address the above issue, this paper presents the coupling of the stochastic analysis concept to the deterministic computational model for the dynamic analysis of SCR. The finite element solution is developed for hydrodynamic and structural analysis accounting for nonlinear and dynamic coupling effects. Methods for reduction of dimensionality of uncertainties are investigated to help to make the analysis computationally feasible. Uncertainty and numerical realization of specific uncertainty parameters are modeled through riser dynamics software and uncertainty analysis software. Distributions of effective tension, bending moment, and API RP 2RD stress are illustrated for a specified SCR model. The correlation effects between structural responses and random variables are investigated. In addition, the failure probability of SCR API RP 2RD stress is investigated through Monte Carlo simulations. This will help to evaluate the behavior and reliability of SCR realistically, incorporating the environmental, geometry and operational uncertainties in engineering practice.