Skip to main content
Log in

Mooring System Optimisation and Effect of Different Line Design Variables on Motions of Truss Spar Platforms in Intact and Damaged Conditions

  • Published:
China Ocean Engineering Aims and scope Submit manuscript

Abstract

This paper presents the effect of mooring diameters, fairlead slopes and pretensions on the dynamic responses of a truss spar platform in intact and damaged line conditions. The platform is modelled as a rigid body with three degrees-of-freedom and its motions are analysed in time-domain using the implicit Newmark Beta technique. The mooring restoring force-excursion relationship is evaluated using quasi-static approach. MATLAB codes DATSpar and QSAML, are developed to compute the dynamic responses of truss spar platform and to determine the mooring system stiffness. To eliminate the conventional trial and error approach in the mooring system design, a numerical tool is also developed and described in this paper for optimising the mooring configuration. It has a graphical user interface and includes regrouping particle swarm optimisation technique combined with DATSpar and QSAML. A case study of truss spar platform with ten mooring lines is analysed using this numerical tool. The results show that optimum mooring system design benefits the oil and gas industry to economise the project cost in terms of material, weight, structural load onto the platform as well as manpower requirements. This tool is useful especially for the preliminary design of truss spar platforms and its mooring system.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Agarwal, A.K. and Jain, A.K., 2003. Dynamic behavior of offshore spar platforms under regular sea waves, Ocean Engineering, 30(4), 487–516.

    Article  Google Scholar 

  • Albrecht, C.H., 2005. Algoritmos Evolutivos Aplicados À Síntese E Otimização de Sistemas de Ancoragem, Ph.D. Thesis, Rio de Janeiro, RJ, Brasil.

    Google Scholar 

  • Al-geelani, N.A., Piah, M.A.M., Adzis, Z. and Algeelani, M.A., 2013. Hybrid regrouping PSO based wavelet neural networks for characterization of acoustic signals due to surface discharges on H.V. glass insulators, Applied Soft Computing, 13(12), 4622–4632.

    Article  Google Scholar 

  • American Petroleum Institute, 2005. Design and Analysis of Stationkeeping Systems for Floating Structures, API RP 2SK, API Publishing Services, Washington, USA.

    Google Scholar 

  • Brits, R., Engelbrecht, A.P. and Van Den Bergh, F., 2002. A niching particle swarm optimizer, Proceedings of the Fourth Asia-Pacific Conference on Simulated Evolution and Learning, Singapore.

    Google Scholar 

  • Cao, P.M., 1996. Slow Motion Responses of Compliant Offshore Structures, MSc. Thesis, Texas A&M University, Texas.

    Google Scholar 

  • Chakrabarti, S.K., 1987. Hydrodynamics of Offshore Structures, Computational Mechanics Publications, Southampton.

    Google Scholar 

  • Coello Coello, C.A., Luna, E.H. and Aguirre, A.H., 2003. Use of particle swarm optimization to design combinational logic circuits, Proceedings of the International Conference on Evolvable Systems: From Biology to Hardware, Springer, Trondheim, Norway, pp. 398–409.

    Chapter  Google Scholar 

  • Eberhart, R.C. and Shi, Y., 2000. Comparing inertia weights and constriction factors in particle swarm optimization, Proceedings of the Congress on Evolutionary Computation, IEEE, La Jolla, CA, USA, pp. 84–88.

    Google Scholar 

  • Evers, G.I., 2009. An Automatic Regrouping Mechanism to Deal with Stagnation in Particle Swarm Optimization, MSc. Thesis, The University of Texas — Pan American, Edinburg, TX.

    Google Scholar 

  • Glanville, R.S., Paulling, J.R., Halkyard, J.E. and Lehtinen, T.J., 1991. Analysis of the spar floating drilling production and storage structure, Proceedings of the 23rd Offshore Technology Conference, OTC, Houston, Texas.

    Google Scholar 

  • Hassan, R., Cohanim, B., De Weck, O. and Venter, G., 2005. A comparison of particle swarm optimization and the genetic algorithm, Proceedings of the 46th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference, AIAA, Austin, Texas.

    Google Scholar 

  • Horton, E.E. and Halkyard, J.E., 1992. A spar platform for developing deep water oil fields, MTS’92, Marine Technology Society, Washington, DC, USA, pp. 998–1005.

    Google Scholar 

  • Hu, X.H., Eberhart, R.C. and Shi, Y.H., 2003. Engineering optimization with particle swarm, Proceedings of 2003 IEEE Swarm Intelligence Symposium, IEEE, Indianapolis, IN, USA, pp. 53–57.

    Google Scholar 

  • Kathiravan, R. and Ganguli, R., 2007. Strength design of composite beam using gradient and particle swarm optimization, Composite Structures, (4), 471–479.

    Google Scholar 

  • Kennedy, J. and Eberhart, R., 1995. Particle swarm optimization, Proceedings of ICNN’95 — International Conference on Neural Networks, IEEE, Perth, WA, Australia, pp. 1942–1948.

    Chapter  Google Scholar 

  • Krohling, R.A., dos Coelho, L.S. and Shi, Y.H., 2003. Cooperative particle swarm optimization for robust control system design, in: Advances in Soft Computing: Engineering Design and Manufacturing, Jose Manuel Benítez, Oscar Cordón, Frank Hoffmann, Rajkumar Roy (Eds.), Springer, London.

    Google Scholar 

  • Magee, A.R., Sablok, A., Maher, J., Halkyard, J., Finn, L. and Datta, I., 2000. Heave plate effectiveness in the performance of truss spars, Proceedings of the International Conference on Offshore Mechanics and Arctic Engineering, New Orleans, pp. 469–479.

    Google Scholar 

  • Mavrakos, S.A., Papazoglou, V.J., Triantafyllou, M.S. and Hatjigeorgiou, J., 1996. Deep water mooring dynamics, Marine Structures, 9(2), 181–209.

    Article  Google Scholar 

  • McCluskey, S., 2008. Application of Particle Swarm Optimisation to Reinforced Concrete Beam Design, Faculty of Engineering, UW.

    Google Scholar 

  • Montasir, O.A., Yenduri, A. and Kurian, V.J., 2015. Effect of mooring line configurations on the dynamic responses of truss spar platforms, Ocean Engineering, 96, 161–172.

    Article  Google Scholar 

  • Montasir, O.A., Yenduri, A. and Kurian, V.J., 2016. Evaluation of the dynamic responses of truss spar platforms for various mooring configurations with damaged lines, Ocean Engineering, 123, 411–421.

    Article  Google Scholar 

  • Monteiro, B.F., Albrecht, C.H. and Jacob, B.P., 2010. Application of the particle swarm optimization method on the optimization of mooring systems for offshore oil exploitation, Proceedings of the 2nd International Conference on Engineering Optimization, Lisboa.

    Google Scholar 

  • Pascoal, R., Huang, S., Barltrop, N. and Guedes Soares, C., 2005. Equivalent force model for the effect of mooring systems on the horizontal motions, Applied Ocean Research, 27(3), 165–172.

    Article  Google Scholar 

  • Pascoal, R., Huang, S., Barltrop, N. and Guedes Soares, C., 2006. Assessment of the effect of mooring systems on the horizontal motions with an equivalent force to model, Ocean Engineering, 33(11–12), 1644–1668.

    Article  Google Scholar 

  • Ran, Z.H., 2000. Coupled Dynamic Analysis of Floating Structures in Waves and Currents, Ph.D. Thesis, Texas A&M University, Texas, USA.

    Google Scholar 

  • Shi, Y. and Eberhart, R., 1998. A modified particle swarm optimizer, Proceedings of 1998 IEEE International Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence, IEEE, Anchorage, AK, USA.

    Google Scholar 

  • Smith, R.J. and MacFarlane, C.J., 2001. Statics of a three component mooring line, Ocean Engineering, 28(7), 899–914.

    Article  Google Scholar 

  • Technip document, 2005. In Place Model Test Result Correlation, Technip Marine (M) Sdn. Bhd, Malaysia.

    Google Scholar 

  • Van Den Bergh, F. and Engelbrecht, A.P., 2001. Effects of swarm size on cooperative particle swarm optimisers, Proceedings of the Genetic and Evolutionary Computation Conference, San Francisco, USA.

    Google Scholar 

  • Van Santen, J.A. and De Werk, K., 1976. On the typical qualities of spar type structures for initial or permanent field development, Proceedings of the 8th Offshore Technology Conference, OTC, Houston, Texas.

    Google Scholar 

  • Wang, Z., 2012. An Evolutionary Optimisation Study on Offshore Mooring System Design, Ph.D. Thesis, University of Wollongong, Wollongong, Australia.

    Google Scholar 

  • Yaakob, O., Zainudin, N., Samian, Y., Abdul, A.M., Malik, O.Y. and Palaraman, R.A., 2004. Developing Malaysian ocean wave database using satellite, Proceedings of the 25th Asian Conference on Remote Sensing, Geo-Informatics and Space Technology Development Agency, Chiang Mai, Thailand.

    Google Scholar 

  • Zheng, Y.L., Ma, L.H., Zhang, L.Y. and Qian, J.X., 2003. Robust PID controller design using particle swarm optimizer, Proceedings of 2003 IEEE International Symposium on Intelligent Control, IEEE, Houston, TX, USA, pp. 974–979

    Google Scholar 

Download references

Acknowledgment

This research was partially supported by YUTP-FRG funded by PETRONAS. We thank our colleagues who provided insight and expertise that greatly assisted the research.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to O. A. Montasir.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Montasir, O.A., Yenduri, A. & Kurian, V.J. Mooring System Optimisation and Effect of Different Line Design Variables on Motions of Truss Spar Platforms in Intact and Damaged Conditions. China Ocean Eng 33, 385–397 (2019). https://doi.org/10.1007/s13344-019-0037-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13344-019-0037-1

Key words

Navigation