Journal
APPLIED OCEAN RESEARCH
Volume 41, Issue -, Pages 76-86Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.apor.2013.03.003
Keywords
Slender structures; Mooring lines; Risers; Nonlinear dynamic analysis; Surrogate models; Artificial neural networks; NARX models
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Funding
- CAPES (Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior)
- FAPERJ (Fundacao Carlos Chagas Filho de Amparo a Pesquisa do Estado do Rio de Janeiro)
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This work presents a new surrogate model based on artificial neural networks (ANNs), comprising a rapid computational tool for the analysis and design of mooring lines and risers. The goal is to obtain results nearly as good as those provided by expensive finite element (FE)-based nonlinear dynamic analyses, with dramatic reductions in processing time. The procedure proposed here associates an ANN with a Nonlinear AutoRegressive model with eXogenous inputs (NARX). Differently from previous models based purely on exogenous inputs (i.e. the platform motions), the NARX model relates the present value of the desired time series not only to the present and past values of the exogenous series, but also to the past values of the desired series itself. Case studies are presented to determine the best configurations for the model, and to evaluate its performance in terms of accuracy and computational time. (C) 2013 Elsevier Ltd. All rights reserved.
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