TY - GEN

T1 - Efficient environmental and structural response analysis by clustering of directional wave spectra

AU - Vogel, M.

AU - Hanson, J.

AU - Fan, S.

AU - Forristall, G.Z.

AU - Li, Y.

AU - Fratantonio, R.

AU - Jonathan, P.

PY - 2016/5/2

Y1 - 2016/5/2

N2 - Estimation of environmental and complex structural responses, such as fatigue for risers on deepwater floating production systems, is a critical and generally computationally intensive process. Long term damage estimates require the determination of host vessel motions used for riser stress calculations. In principle, riser stress could be calculated for each of a large number of directional sea states, a considerable computational burden. However, it might be possible to identify a representative subset of directional sea states for vessel motion and subsequent riser stress analysis, such that estimated fatigue characteristics (from the full set of sea states and the subset thereof) were equivalent. This would be advantageous as it would require considerably less computational effort. In this work we use non hierarchical K-MEANS cluster analysis to partition a large set of directional wave spectra for contiguous sea states at a location offshore Brazil, corresponding to a period of approximately 2 years into a number of clusters. We adopt the set comprised of cluster centroids only as representative sea states for efficient characterization of the environment and structural response. We demonstrate that the representative sea states provide an efficient basis for estimation of overall sea state bulk, wind sea and swell characteristics. We evaluate the effect of cluster size on the performance of the representative sea states using custom built visualization tools utilizing the Kolmogorov-Smirnov test statistics. The representative sea states are further used as input for a VLCC-class FPSO vessel motion analysis. For heave at the turret, roll motions, and relative vessel heading, distributions of vessel motions from analysis of representative sea states are in excellent agreement with those from analysis of all sea states. Guidelines for the application of the methodology are provided. Copyright 2016, Offshore Technology Conference.

AB - Estimation of environmental and complex structural responses, such as fatigue for risers on deepwater floating production systems, is a critical and generally computationally intensive process. Long term damage estimates require the determination of host vessel motions used for riser stress calculations. In principle, riser stress could be calculated for each of a large number of directional sea states, a considerable computational burden. However, it might be possible to identify a representative subset of directional sea states for vessel motion and subsequent riser stress analysis, such that estimated fatigue characteristics (from the full set of sea states and the subset thereof) were equivalent. This would be advantageous as it would require considerably less computational effort. In this work we use non hierarchical K-MEANS cluster analysis to partition a large set of directional wave spectra for contiguous sea states at a location offshore Brazil, corresponding to a period of approximately 2 years into a number of clusters. We adopt the set comprised of cluster centroids only as representative sea states for efficient characterization of the environment and structural response. We demonstrate that the representative sea states provide an efficient basis for estimation of overall sea state bulk, wind sea and swell characteristics. We evaluate the effect of cluster size on the performance of the representative sea states using custom built visualization tools utilizing the Kolmogorov-Smirnov test statistics. The representative sea states are further used as input for a VLCC-class FPSO vessel motion analysis. For heave at the turret, roll motions, and relative vessel heading, distributions of vessel motions from analysis of representative sea states are in excellent agreement with those from analysis of all sea states. Guidelines for the application of the methodology are provided. Copyright 2016, Offshore Technology Conference.

KW - Cluster analysis

KW - Mooring

KW - Statistical tests

KW - Stress analysis

KW - Structural analysis

KW - Computational burden

KW - Computational effort

KW - Deepwater floating productions

KW - Directional wave spectrum

KW - Fatigue characteristics

KW - Hierarchical k-means

KW - Kolmogorov-Smirnov test

KW - Structural response analysis

KW - Ocean currents

U2 - 10.4043/27039-MS

DO - 10.4043/27039-MS

M3 - Conference contribution/Paper

SN - 9781510824294

SP - 1904

EP - 1921

BT - Offshore Technology Conference 2016 (OTC 2016)

PB - Curran Associates, Inc.

ER -