Abstract
Slender marine structures such as deep-water marine risers are subjected to currents and will normally experience Vortex Induced Vibrations (VIV), which can cause fast accumulation of fatigue damage. The ocean current is often three-dimensional (3D), i.e., the direction and magnitude of the current vary throughout the water column.
Today, semi-empirical tools are used by the industry to predict VIV induced fatigue on risers. The load model and hydrodynamic parameters in present VIV prediction tools are developed based on two-dimensional (2D) flow conditions, as it is challenging to consider the effect of 3D flow along the risers. Accordingly, the current profiles must be purposely made 2D during the design process, which leads to significant uncertainty in the prediction results.
Further, due to the limitations in the laboratory, VIV model tests are mostly carried out under 2D flow conditions and thus little experimental data exist to document VIV response of riser subjected to varying directions of the current. However, a few experiments have been conducted with 3D current. We have used results from one of these experiments to investigate how well (1) traditional and (2) an alternative method based on a data driven prediction can describe VIV in 3D currents.
Data driven modelling is particularly suited for complicated problems with many parameters and non-linear relationships. We have applied a data clustering algorithm to the experimental 3D flow data in order to identify measurable parameters that can influence responses. The riser responses are grouped based on their statistical characteristics, which relate to the direction of the flow. Furthermore we fit a random forest regression model to the measured VIV response and compare its performance with the predictions of existing VIV prediction tools (VIVANA-FD).
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Breiman, L.: Random forests. Mach. Learn. 45(1), 5–32 (2001). https://doi.org/10.1023/A:1010933404324
Campello, R.J.G.B., Moulavi, D., Sander, J.: Density-based clustering based on hierarchical density estimates. In: Pei, J., Tseng, V.S., Cao, L., Motoda, H., Xu, G. (eds.) PAKDD 2013. LNCS (LNAI), vol. 7819, pp. 160–172. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-37456-2_14
Hastie, T., Tibshirani, R., Friedman, J.H.: The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer Series in Statistics, 2nd edn. Springer, New York (2009). https://doi.org/10.1007/978-0-387-84858-7. http://www.worldcat.org/oclc/300478243
Lie, H., Braaten, H., Jhingran, V., Sequeiros, O.E., Vandiver, K.: Comprehensive riser VIV model tests in uniform and sheared flow. In: 31st International Conference on Ocean, Offshore and Arctic Engineering, ASME 2012, vol. 5 (2012). https://doi.org/10.1115/OMAE2012-84055
Lie, H., Mo, K., Vandiver, J.: VIV model test of a bare- and a staggered buoyancy riser in a rotating rig. In: Offshore Technology Conference, OTC-8700-MS, Houston, Texas (1998). https://doi.org/10.4043/8700-MS
McInnes, L., Healy, J., Astels, S.: HDBSCAN: hierarchical density based clustering. J. Open Source Softw. 2(11) (2017). https://doi.org/10.21105/joss.00205
Passano, E., Larsen, C., Lie, H., Wu, J.: VIVANA - Theory Manual Version 4.4 (2014)
Srivilairit, T., Manuel, L.: Vortex-induced vibration and coincident current velocity profiles for a deepwater drilling riser. J. Offshore Mech. Arct. Eng. 131, 021101 (2009). https://doi.org/10.1115/1.3058684
Thorsen, M., Sævik, S., Larsen, C.: A simplified method for time domain simulation of cross-flow vortex-induced vibrations. J. Fluids Struct. 49, 135–148 (2014). https://doi.org/10.1016/j.jfluidstructs.2014.04.006
Thorsen, M., Sævik, S., Larsen, C.: Non-linear time domain analysis of cross-flow vortex-induced vibrations. Mar. Struct. 51, 134–151 (2017). https://doi.org/10.1016/j.marstruc.2016.10.007
Triantafyllou, M., Triantafyllou, G., Tein, Y.D., Ambrose, B.D.: Pragmatic riser VIV analysis. In: Offshore Technology Conference, OTC-10931-MS, Houston, Texas (1999). https://doi.org/10.4043/10931-MS
Trim, A., Braaten, H., Lie, H., Tognarelli, M.: Experimental investigation of vortex-induced vibration of long marine risers. J. Fluids Struct. 21(3), 335–361 (2005). https://doi.org/10.1016/j.jfluidstructs.2005.07.014. Marine and Aeronautical Fluid-Structure Interactions
Vandiver, J.: Predicting lock-in on drilling risers in sheared flows. In: Flow-Induced Vibration Conference, Lucerne, Switzerland (2000)
Vandiver, J., Li, L.: Shear7 v4.5 Program Theoretical Manual (2007)
Vandiver, J.K., Swithenbank, S.B., Jaiswal, V., Jhingran, V.: Fatigue damage from high mode number vortex-induced vibration. In: 25th International Conference on Ocean, Offshore and Arctic Engineering, ASME 2006, vol. 4 (2006). https://doi.org/10.1115/OMAE2006-92409
Westfall, P.H.: Kurtosis as peakedness, 1905–2014. R.I.P. Am. Stat. 68(3), 191–195 (2014). https://doi.org/10.1080/00031305.2014.917055
Acknowledgements
The authors would like to thank Anne Marthine Rustad for discussions and suggestions. This study was sponsored by Equinor, BP, Kongsberg Maritime, Trelleborg Offshore, Aker Solutions and Subsea7.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Riemer-Sørensen, S., Wu, J., Lie, H., Sævik, S., Kim, SW. (2019). Data-Driven Prediction of Vortex-Induced Vibration Response of Marine Risers Subjected to Three-Dimensional Current. In: Bach, K., Ruocco, M. (eds) Nordic Artificial Intelligence Research and Development. NAIS 2019. Communications in Computer and Information Science, vol 1056. Springer, Cham. https://doi.org/10.1007/978-3-030-35664-4_8
Download citation
DOI: https://doi.org/10.1007/978-3-030-35664-4_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-35663-7
Online ISBN: 978-3-030-35664-4
eBook Packages: Computer ScienceComputer Science (R0)