Abstract
Offshore drilling platform plays an important role in the exploitation of offshore natural resources. Safety is the top priority in offshore platform operations. Among various risks, dropping objects is a major source of risk that threatens personal safety, platform structure and environment safety. In this paper, simulations are performed using finite element simulation software. As the custom objects in platform crane operations, the oil drum is used as the research object in the simulation of damage caused by dropping objects on the drilling platform deck structure at different contact angles. Through the analysis of the simulation test results, the relationship between the angle of the dropping object and the energy impact of the deck is obtained. As the result of the impact and the contact angle is a highly nonlinear mapping, the radial basis function neural network based on partial least squares is implemented for interpolation purposes. The approach of PLS-RBF (Partial Least Square-Radial Basis Function) method takes advantage of the RBF network and PLS regression method can obtain high generalization accuracy for nonlinear system mappings. The results are compared with other approaches to illustrate its effectiveness.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Kenny, J.P.: Protection of offshore Installations Against Impact offshore Technology Report. OTI-88535 (1991)
Arabzadeh, H., Zeinoddini, M.: Dynamic response of pressurized submarine pipelines subjected to transverse impact loads. Procedia Eng. 14(2259), 648–655 (2011)
Fujii, Y., et al.: Some factors affecting the frequency of accidents in marine traffic. J. Navig. 27(2), 239–247 (1974)
Yan, S., Tian, Y.: Analysis of pipeline damage to impact load by dropped objects. Trans. Tianjin Univ. 12, 138–141 (2006)
Abosbaia, A.S., Mahdi, E., Hamouda, A.M.S., et al.: Energy absorption capability of laterally loaded segmented composite tubes. Compos. Struct. 70(3), 356–373 (2005)
Thapa, P., Khan, F.: Dropped object effect in offshore subsea structures and pipeline approach. Technical report (2016)
Kawsar, M.R.U., Youssef, S.A., Faisal, M., et al.: Assessment of dropped object risk on corroded subsea pipeline. Ocean Eng. 106, 329–340 (2015)
Awotahegn, M.B.: Experimental investigation of accidental drops of drill pipes and containers during offshore operations. University of Stavanger, Norway (2015)
Sun, L.P., Ma, G., Nie, C.Y., et al.: The simulation of dropped objects on the offshore structure. Adv. Mater. Res. 339, 553–556 (2011)
Amdahl, J., Eberg, E.: Ship collision with offshore structures. In: Proceedings of 2nd European Conference on Structural Dynamics, Trondheim, Norway, pp. 495–504 (1993)
Pedersen, P.T., Jensen, J.J.: Ship impact analysis for bottom supported offshore structures. Adv. Mar. Struct. 276–295 (1991)
Gu, Y., Wang, Z.L.: An inertia equivalent model for numerical simulation of ship-ship collisions. In: 2nd International Conference on Collision and Grounding of Ships ICCGS, Copenhagen, Denmark, pp. 155–160 (2001)
Yin, J.C., Wang, N., Perakis, A.: A real-time sequential ship roll prediction scheme based on adaptive sliding data window. IEEE Trans. Syst. Man Cybern.: Syst. 99, 1–11 (2017)
Acknowledgement
This work is supported by grant from the 7th Generation Ultra-Deep-water Drilling Rig Innovation Project, the Liaoning Natural Science Foundation of China, and the Natural Science Foundation of China under Grant 51609132 [13].
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Liu, H., Zhang, W., Liu, S., Li, Y. (2018). PLS-Based RBF Network Interpolation for Nonlinear FEM Analysis of Dropped Drum in Offshore Platform Operations. In: Qiao, J., et al. Bio-inspired Computing: Theories and Applications. BIC-TA 2018. Communications in Computer and Information Science, vol 952. Springer, Singapore. https://doi.org/10.1007/978-981-13-2829-9_12
Download citation
DOI: https://doi.org/10.1007/978-981-13-2829-9_12
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-2828-2
Online ISBN: 978-981-13-2829-9
eBook Packages: Computer ScienceComputer Science (R0)