MATEC Web Conf.
Volume 203, 2018International Conference on Civil, Offshore & Environmental Engineering 2018 (ICCOEE 2018)
|Number of page(s)||11|
|Section||Coastal and Offshore Engineering|
|Published online||17 September 2018|
Development of ANN Model for the Prediction of VIV Fatigue Damage of Top-tensioned Riser
Department of Mechanical Engineering, Universiti Teknologi PETRONAS,
2 Graduate Institute of Ferrous Technology, POSTECH, Pohang, Republic of Korea
3 Department of Civil and Environmental Engineering, Universiti Teknologi PETRONAS, Seri Iskandar, Malaysia
Marine riser experiences vortex-induced vibration (VIV) caused by current, leading to fatigue damage if VIV is not considered in design of riser. Estimation of VIV fatigue damage is essential in designing feasible and operable riser. A simplified approach for predicting fatigue damage is required to reduce the computation time to analyze the fatigue damage. This study aims to explore the applicability of artificial neural network (ANN) approach in developing top-tensioned riser fatigue damage prediction model. A total of 2100 riser model is generated with different combination of four main input parameters: riser outer diameter, wall thickness, top tension and uniform current velocity. The modal analysis is performed using OrcaFlex and VIV fatigue damage of the riser is computed using SHEAR7. The four input parameters and corresponding fatigue damage results make up the database for training a 2-layer neural network. Weight and bias values acquired from the training of ANN are used to develop the VIV fatigue damage prediction model of the riser. The results show ANN approach is suitable for prediction of the riser fatigue damage due to VIV. The proposed approach requires further refinements and extension to more input features to improve the accuracy and usefulness of the developed prediction model.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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