Application of artificial neural network to predict the wave characteristics to improve the sea waves and currents forces applied on the jacket platform legs
Article Sidebar
-
Neural networks, offshore structures analysis, Airy’s linear theory, SMB and Bretschneider equations, Morison equation
Abstract
It is essential for all offshore structures analysis to estimate the forces generated by the wave and current by developing a program for modeling wave and current forces on offshore structural members. This study investigates the possibility of utilizing the relatively current technique of artificial neural networks (ANN) to predict the wave characteristics. Besides, the comparison of ANN models with the most two widely used empirical models included Bretschneider and Sverdrup-Munk and Bretschneider (SMB) equations showed a better performance for ANN models rather than empirical models. Furthermore, a developed program was studied for calibration and comparison purposes, where the program was checked against well-known professional software package called Structural Analysis Computer System (SACS). Airy wave theory (linear theory) has been implemented in the present study to calculate the water particles kinematics. Also, the Morison equation was used for converting the velocity and acceleration terms into resultant forces.
Full text article
Authors
This work is licensed under a Creative Commons Attribution 4.0 International License.
In a brief statement, the rights relate to the publication and distribution of research published in the journal of the University of Sebha where authors who have published their articles in the journal of the university of Sebha should how they can use or distribute their articles. They reserve all their rights to the published works, such as (but not limited to) the following rights:
- Copyright and other property rights related to the article, such as patent rights.
- Research published in the journal of the University of Sebha and used in its future works, including lectures and books, the right to reproduce articles for their own purposes, and the right to self-archive their articles.
- The right to enter a separate article, or for a non-exclusive distribution of their article with an acknowledgment of its initial publication in the journal of Sebha University.
Privacy Statement The names and e-mail addresses entered on the Sabha University Journal site will be used for the aforementioned purposes only and for which they were used.
