Stochastic dynamic analysis of marine risers considering fluid-structure interaction and system uncertainties

Abstract

Stochastic dynamic analysis of offshore structures considering both fluid-structure interaction and system uncertainties is a challenging research task. This paper proposes a novel method to evaluate the statistical characteristics of offshore structural responses with consideration of uncertainties in the fluid and structure. The fluid behavior is simulated by a finite number of particles with particle finite element method (PFEM), and the dynamic behavior of the offshore structure is modelled with finite element method (FEM). A PFEM-FEM scheme is used to model the fluid-structure interaction. To evaluate the statistical characteristics, spectral representations method is used for uncertainty propagation. The output of fluid particles position/pressure, structural vibration, etc. are represented by using polynomial chaos (PC) expansion, and their coefficients are obtained from the least squares method. Statistical characteristics of the responses, such as mean value and variance, can be evaluated with the obtained PC coefficients. Three numerical examples are studied in this paper. The first example is a simple structural model, which is used to demonstrate the convergence and accuracy of the uncertainty analysis method. The second example is a benchmark dam break problem. Statistical characteristics of the fluid particles position due to uncertainties in the mass density are evaluated. Numerical results are verified with experimental data and observations. In the third example, PFEM-FEM scheme is used to conduct fluid–structure interaction analysis. The marine riser structure is modelled with beam elements. In the fluid domain, PFEM is used. Uncertainties in both the fluid domain and structural domain are considered. Results demonstrate that the proposed approach can be used to evaluate the statistical characteristics of responses in the fluid-structure interaction analysis accurately and efficiently.