Response prediction of offshore floating structure using artificial neural network

Uddin, M.A. and Jameel, M. and Razak, H.A. and Saiful Islam, A.B.M. (2012) Response prediction of offshore floating structure using artificial neural network. Advanced Science Letters, 14 (1). pp. 186-189. ISSN 19367317

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Abstract

For deep-water oil and gas exploration, spar platform is considered to be the most economic and suitable floating offshore structure. Analysis of spar platform is complex due to various nonlinearities such as geometric, variable submergence, varying pretention, etc. The Finite Element Method (FEM) is an important technique to deal with this type of analysis. However, FEM is computationally very expensive and highly time-consuming process. Artificial Neural Network (ANNs) can provide meaningful solutions and can process information in extremely rapid mode ensuring high accuracy of prediction. This paper presents dynamic response prediction of spar mooring line using ANN. FEM-based time domain response of spar platform such as surge, heave and pitch is trained by ANN. Mooring line top tension is predicted after 7200 sec (2 hours) of wave loading. The response obtained using ANN is validated by conventional FEM analysis. Results show that ANN approach is found to be very efficient and it significantly reduces the time for predicting long response time histories. Thus ANN approach is recommended for efficient designing of floating structures. © 2012 American Scientific Publishers. All rights reserved.

Item Type: Article
Additional Information: Cited By (since 1996):2 Export Date: 16 December 2013 Source: Scopus Language of Original Document: English Correspondence Address: Uddin, M. A.; Department of Civil Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia References: Mazaheri, S., Downie, M.J., (2005) Ocean Engg., p. 32; Mazaheri, S., (2006) J. of Marine Engg., 3, p. 48; Elshafey, A.A., Haddara, M.R., Marzouk, H., (2011) Ocean Systems Engg., p. 1; Zhou, X., Luan, S., (2009) 5th International Conference on Wireless Communications, Networking and Mobile Computing, , WiCom, Beijing, China; Guarize, R., Matos, N.A.F., Sagrilo, L.V.S., Lima, E.C.P., (2007) Applied Ocean Research, p. 29; Mandal, S., Hegde, G., Gupta, K.G., (2004) Proceeding of National Seminar on Construction Management: Latest Trends and Developments, , Pune, India; Yasseri, S., Bahai, H., Bazargan, H., Aminzadeh, A., (2010) Ocean Engg., p. 37; Simoes, G., Tiquilloca, L.M., Morishita, M., (2002) IEEE Transactions on Industry Applications, p. 38; Hong-Yu, C., De-You, Z., (2010) J. of Dalian University of Technol.; Cui, H.Y., Zhao, D.Y., (2007) Harbin Gongcheng Daxue Xuebao/J. of Harbin Engg. University, p. 28; Jameel, M., Ahmad, S., Islam, A., Jumaat, M.Z., (2011) International Offshore and Polar Engg. Conference (ISOPE), , Maui, Hawaii, USA, June; Islam, A.B.M.S., Jameel, M., Jumaat, M.Z., (2011) International J. of Green Energy., , In Press Corrected Proof; Jameel, M., Ahmad, S., Islam, A.B.M.S., Jumaat, M.Z., (2011) J. of Civil Engg. and Management, , In Press, Corrected Proof; Jameel, M., (2008), Ph.D. Thesis, Indian Institute of Technol, Delhi, IndiaJameel, M., Ahmad, S., (2011) Proceedings of the ASME 2011 30th International Conference on Ocean, , Offshore and Arctic Engineering, OMAE, Rotterdam, The Netherlands, June; Islam, A.B.M.S., Jameel, M., Jumaat, M.Z., (2011) International J. of the Physical Sciences, p. 2671; Jameel, M., Islam, A.B.M.S., Salman, F.A., Khaleel, M., Jumaat, M.Z., (2011) Advanced Science letters, , In Press, Corrected proof
Uncontrolled Keywords: Artificial neural network, Deep water platforms, Dynamic response, Mooring line tension, Offshore floating structure, Prediction, Spar platform
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Engineering
Depositing User: Mr Jenal S
Date Deposited: 24 Jan 2014 07:23
Last Modified: 24 Jan 2014 07:23
URI: http://eprints.um.edu.my/id/eprint/9117

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