Research Papers: Structures and Safety Reliability

Predicting the Probability of Riser Collision Under Stochastic Excitation and Multiple Uncertainties

[+] Author and Article Information
Jian Wen He

e-mail: heji0006@ntu.edu.sg

Ying Min Low

e-mail: ymlow@ntu.edu.sg
Nanyang Technological University,
School of Civil and Environmental Engineering,
Nanyang Avenue,
639798, Singapore

1Corresponding author.

Contributed by the Ocean, Offshore, and Arctic Engineering Division of ASME for publication in the JOURNAL OF OFFSHORE MECHANICS AND ARCTIC ENGINEERING. Manuscript received September 14, 2012; final manuscript received April 15, 2013; published online June 12, 2013. Assoc. Editor: Arvid Naess. This paper was presented at the 32nd International Conference on Ocean OffShore and Arctic Engineering, Nantes, France, June 9-14, 2013. Paper No. OMAE2013-10381.

J. Offshore Mech. Arct. Eng 135(3), 031602 (Jun 12, 2013) (9 pages) Paper No: OMAE-12-1089; doi: 10.1115/1.4024270 History: Received September 14, 2012; Revised April 15, 2013

As the offshore industry moves to deeper waters, riser collision becomes a more crucial concern. Riser interference assessments need to rely on time domain simulations due to nonlinearities such as hydrodynamic interferences, however, one difficulty is that riser collision is an extreme event. In a recent work, the authors proposed an efficient procedure for predicting the probability of riser collision, based on extrapolating the dynamic response characteristics; thus obviating the need to capture actual collisions during simulation. However, the prior work considers randomness only from the irregular waves. This paper extends the prior work by developing a method to account for multiple uncertainties. The random variables considered herein are the current, drag coefficient, vessel motions, and riser mass. The proposed method is computationally efficient; the additional simulations necessary to incorporate four random variables are only slightly more than the original simulation case. Using a top-tensioned riser system as a case study, the likelihood of collision predicted by the proposed method is found to compare well with the Monte Carlo simulation. Moreover, it is shown that the random variables can increase the probability by an order of magnitude and all of the considered variables meaningfully contribute to this increase.

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Grahic Jump Location
Fig. 6

Linear fitting by the Naess method for (a) V2,z′, and (b) V2,z'

Grahic Jump Location
Fig. 1

Global riser model

Grahic Jump Location
Fig. 4

Extrapolation of Vj,z': (a) j = 1, (b) j = 2, (c) j = 3, and (d) j = 4

Grahic Jump Location
Fig. 2

Crossing rate extrapolations of the baseline case (6 h and 30 h simulation data)

Grahic Jump Location
Fig. 5

Extrapolation of Vj,z′: (a) j = 1, (b) j = 2, (c) j = 3, and (d) j = 4

Grahic Jump Location
Fig. 3

Crossing rates obtained by varying each variable Uj by ±Δuj: (a) j = 1, (b) j = 2, (c) j = 3, and (d) j = 4



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