One of the standardized procedures used in the design of floating systems and their mooring and production lines is the so-called short-term design approach where the system is analyzed for some specific extreme environmental conditions. Along with this procedure, a nonlinear time-domain coupled dynamic analysis, considering the floater and its risers and mooring lines, can nowadays be incorporated as a feasible part of the design practice. One very important and challenging aspect of this process is concerned with the estimation of the characteristic short-term extreme values of the system response parameters based on the sampled time-series. In this paper a common procedure used to establish these extreme values for floater system response parameters, which is based upon a Weibull distribution model for the peaks of the time-series, is reviewed in the light of a recently proposed approach based on a general parametric model for the average conditional exceedance rate of peaks. It is shown that the former model corresponds to a particular case of the latter one. Numerical results are presented for the response parameters of a turret-moored Floating, Production, Storage and Offloading (FPSO) unit considering a short-term coupled analysis of the whole system under an extreme environmental condition of wind, wave, and current. Specifically, the extreme response of surge motion, top tension of the most loaded mooring line, and Det norske Veritas (DnV) codes utilization factor for the most critical section of an 0.20 m outer diameter SLWR (steel lazy wave riser) are investigated.

References

References
1.
DnV, 2001, “
Offshore Standard DnV OS F201–Dynamic Risers
,” Hovik, Norway.
2.
DnV, 2004, “
Offshore Standard DnV OS E301–Positioning Mooring
,” Hovik, Norway.
3.
DnV
, 2002, “
DeepC Program—Deep Water Coupled Floater Motion Analysis
,” Hovik, Norway.
4.
ANFLEX-TPN, 2003, “
Coupled Dynamic Floater Analysis Program
,” User’s Manual, São Paulo University and PETROBRAS Numerical Wave Tank, Sao Paulo, Brazil.
5.
Ormberg
,
H.
, and
Larsen
,
K.
, 1998, “
Coupled Analysis of Floater Motion and Mooring Dynamics for a Turret-Moored Ship
,”
Appl. Ocean Res.
,
20
, pp.
55
67
.
6.
Naess
,
A.
,
Stansberg
,
C. T.
,
Gaidai
,
O.
, and
Baarholm
,
R. J.
, 2009, “
Statistics of Extreme Events in Airgap Measurements
,”
ASME J. Offshore Mech. Arct. Eng.
,
131
, p.
041107
.
7.
Zurita
,
B. I. G.
, 1999, “
Extreme Value Analysis of Gaussian and Non-Gaussian Time Series
,”
Master’s of Science dissertation, COPPE - Federal University of Rio de Janeiro
,
Rio de Janeiro
,
Brazil
(in Portuguese).
8.
Sagrilo
,
L. V. S.
,
Siqueira
,
M. Q.
,
Ellwanger
,
G. B.
,
Lima
,
E. C. P.
,
Mourelle
,
M. M.
, and
Ferreira
,
M. D. A.
, 2002, “
A Coupled Approach for Dynamic Analysis of CALM Systems
,”
Appl. Ocean Res.
,
24
, pp.
47
58
.
9.
Naess
,
A.
, and
Gaidai
,
O.
, 2009, “
Estimation of Extreme Values From Sampled Time Series
,”
Struct. Saf.
,
31
, pp.
325
334
.
10.
Naess
,
A.
,
Stansberg
,
C. T.
, and
Batsevych
O.
, 2009, “
Prediction of Extreme Tether Tension for a TLP
,”
Proceedings 28th International Conference on Offshore Mechanics and Arctic Engineering (OMAE)
,
Honolulu, HI
.
11.
Naess
,
A.
, 1984, “
A Rational Approach to Extreme Value Analysis
,”
Appl. Ocean Res.
,
6
, pp.
173
174
.
12.
Naess
,
A.
,
Gaidai
,
O.
, and
Haver
,
S.
, 2007, “
Efficient Estimation of Extreme Response of Drag-Dominated Offshore Structures by Monte Carlo Simulation
,”
Ocean Eng.
,
34
, pp.
2188
2197
.
13.
Ang
,
A. H. S.
, and
Tang
,
W. H.
, 1975,
Probability Concepts in Engineering Planning and Design
,
John Willey and Sons
,
New York
, Vol.
1
.
14.
Efron
,
B.
, and
Tibshirani
,
R. J.
, 1993, “
An Introduction to the Bootstrap
,” Chapman & Hall/CRC, Boca Raton, Florida.
15.
Bazan
,
F. A. V.
, 2005, “
Bootstrap Technique Applied to Uncertainty Evaluation of Extreme Response Parameters
,” Master’s of Science dissertation, COPPE - Federal University of Rio de Janeiro, Rio de Janeiro, Brazil (in Portuguese).
16.
Madsen
,
H.
,
Krenk
,
S.
, and
Lind
,
N. C.
, 1986, “
Methods of Structural Safety
.” Englewood-Cliffs, NJ.
17.
Farnes
,
K. A.
, 1990, “
Long-Term Statistics of Response in Non-Linear Marine Structures
,” Ph.D thesis, Department of Marine Technology, Norwegian University of Science and Technology, Trondheim, Norway.
18.
Der Kiureghian
,
A.
, and
Liu
,
P. L.
, 1986, “
Structural Reliability Under Incomplete Probability Information
,”
J. Eng. Mech.
,
112
(
1
), pp.
85
104
.
19.
ANFLEX, 1995, “
Non-Linear Time-Domain Dynamic Analysis of Risers and Mooring Lines
,” User’s Manual, PETROBRAS Research Center and COPPE-Federal University of Rio de Janeiro.
20.
Sagrilo
,
L. V. S.
,
Gao
,
Z.
,
Naess
,
A.
, and
Lima
,
E. C. P.
, 2011, “
A Straightforward Approach for Using Single Time Domain Simulations to Assess Characteristic Extreme Responses
,”
Ocean Eng.
,
38
,(
13
), pp.
1464
1471
.
You do not currently have access to this content.