Stochastic analysis of the non-Gaussian airgap response of a semi-submersible using frequency domain analysis

• Published in: Marine structures Vol. 67; p. 102636
• Main Authors: Wang, Zizhe, Low, Ying Min, Li, Binbin
• Format: Journal Article
• Language: English
• Published: Barking Elsevier Ltd 01.09.2019; Elsevier BV
• Subjects: Air gaps; Airgap; Computer simulation; Crossing rate; Dependence; Design parameters; Drag; Extreme statistics; Extreme values; Frequency analysis; Frequency domain analysis; Gaussian process; Linearization; Non-Gaussian; Phase relationships; Radiation; Random waves; Second-order; Statistical analysis; Statistical methods; Statistics; Stochastic processes; Stochasticity; Submersibles; Transfer functions; Wave amplification; Wave diffraction; Wave forces; Crossing rate; Non-Gaussian; Airgap; Extreme statistics; Second-order; Linearization
• ISSN: 0951-8339; 1873-4170
• DOI: 10.1016/j.marstruc.2019.102636

Airgap is a crucial design parameter for semi-submersibles. The analysis of the extreme airgap statistics is challenging due to nonlinearities in the wave elevation and platform motions, as well as their interactions and phase relationships. In this paper, an efficient frequency domain approach is developed for airgap analysis, using second-order diffraction analysis to model the wave loads. The wave amplification effect is predicted using second-order random wave theory together with linear diffraction/radiation analysis, and the drag forces are linearized. The linear and quadratic transfer functions (sum- and difference frequencies) of the airgap response are derived, preserving all the phase relationships. The crossing rate is a key quantity for characterizing the extreme of a stochastic process. Using the transfer functions, the crossing rate of the non-Gaussian airgap process is derived via a statistical method that preserves the statistical dependency between the linear, sum- and difference-frequency components. In the case studies, the spectral density of the airgap obtained from frequency domain analysis are compared to time domain simulations (which are performed as a benchmark), and the results are found to be in excellent agreement. Moreover, the proposed approach generally provides good estimation of the crossing rate. The results also reveal insights into the airgap behavior; for example, the airgap at the platform center is nearly Gaussian, whereas the off-center locations are significantly non-Gaussian. Finally, the influence of various nonlinearities on the airgap statistics are systematically investigated. •Efficient statistical approach for predicting the extreme airgap for semi-submersible.•Proposed approach based on frequency domain analysis; drag forces are linearized.•Non-Gaussian statistics and correlation of wave elevation and motion are considered.•Airgap spectra and crossing rates obtained agree well with time domain simulation.•Systematic study of influence of various nonlinearities on the airgap statistics.