Artificial Neural Network Model for the Evaluation of Added Resistance of Container Ships in Head Waves
The decrease in ship added resistance in waves fits into both the technical and operational measures proposed by the IMO to reduce the emissions of harmful gases from ships. Namely, the added resistance in waves causes an increase in fuel consumption and the emission of harmful gases in order for th...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-07-01
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| Series: | Journal of Marine Science and Engineering |
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| Online Access: | https://www.mdpi.com/2077-1312/9/8/826 |
| _version_ | 1797523379622772736 |
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| author | Ivana Martić Nastia Degiuli Dubravko Majetić Andrea Farkas |
| author_facet | Ivana Martić Nastia Degiuli Dubravko Majetić Andrea Farkas |
| author_sort | Ivana Martić |
| collection | DOAJ |
| description | The decrease in ship added resistance in waves fits into both the technical and operational measures proposed by the IMO to reduce the emissions of harmful gases from ships. Namely, the added resistance in waves causes an increase in fuel consumption and the emission of harmful gases in order for the ship to maintain the design speed, especially in more severe sea states. For this reason, it is very important to estimate the added resistance in waves with sufficient accuracy in the preliminary design phase. In this paper, the possibility of applying an ANN to evaluate added resistance in waves at the different sea states that the ship will encounter during navigation is investigated. A numerical model, based on the results of hydrodynamic calculations in head waves, and ANN is developed. The model can estimate the added resistance of container ships with sufficient accuracy, based on the ship characteristics, sailing speed, and the sea state using two wave energy spectra. |
| first_indexed | 2024-03-10T08:42:07Z |
| format | Article |
| id | doaj.art-8d2f82bde5234cd9b5e8a9ecad971a94 |
| institution | Directory Open Access Journal |
| issn | 2077-1312 |
| language | English |
| last_indexed | 2024-03-10T08:42:07Z |
| publishDate | 2021-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Marine Science and Engineering |
| spelling | doaj.art-8d2f82bde5234cd9b5e8a9ecad971a942023-11-22T08:14:52ZengMDPI AGJournal of Marine Science and Engineering2077-13122021-07-019882610.3390/jmse9080826Artificial Neural Network Model for the Evaluation of Added Resistance of Container Ships in Head WavesIvana Martić0Nastia Degiuli1Dubravko Majetić2Andrea Farkas3Faculty of Mechanical Engineering and Naval Architecture, University of Zagreb, Ivana Lučića 5, 10002 Zagreb, CroatiaFaculty of Mechanical Engineering and Naval Architecture, University of Zagreb, Ivana Lučića 5, 10002 Zagreb, CroatiaFaculty of Mechanical Engineering and Naval Architecture, University of Zagreb, Ivana Lučića 5, 10002 Zagreb, CroatiaFaculty of Mechanical Engineering and Naval Architecture, University of Zagreb, Ivana Lučića 5, 10002 Zagreb, CroatiaThe decrease in ship added resistance in waves fits into both the technical and operational measures proposed by the IMO to reduce the emissions of harmful gases from ships. Namely, the added resistance in waves causes an increase in fuel consumption and the emission of harmful gases in order for the ship to maintain the design speed, especially in more severe sea states. For this reason, it is very important to estimate the added resistance in waves with sufficient accuracy in the preliminary design phase. In this paper, the possibility of applying an ANN to evaluate added resistance in waves at the different sea states that the ship will encounter during navigation is investigated. A numerical model, based on the results of hydrodynamic calculations in head waves, and ANN is developed. The model can estimate the added resistance of container ships with sufficient accuracy, based on the ship characteristics, sailing speed, and the sea state using two wave energy spectra.https://www.mdpi.com/2077-1312/9/8/826added resistance in wavescontainer shippotential flow theoryartificial neural network (ANN)sea state |
| spellingShingle | Ivana Martić Nastia Degiuli Dubravko Majetić Andrea Farkas Artificial Neural Network Model for the Evaluation of Added Resistance of Container Ships in Head Waves Journal of Marine Science and Engineering added resistance in waves container ship potential flow theory artificial neural network (ANN) sea state |
| title | Artificial Neural Network Model for the Evaluation of Added Resistance of Container Ships in Head Waves |
| title_full | Artificial Neural Network Model for the Evaluation of Added Resistance of Container Ships in Head Waves |
| title_fullStr | Artificial Neural Network Model for the Evaluation of Added Resistance of Container Ships in Head Waves |
| title_full_unstemmed | Artificial Neural Network Model for the Evaluation of Added Resistance of Container Ships in Head Waves |
| title_short | Artificial Neural Network Model for the Evaluation of Added Resistance of Container Ships in Head Waves |
| title_sort | artificial neural network model for the evaluation of added resistance of container ships in head waves |
| topic | added resistance in waves container ship potential flow theory artificial neural network (ANN) sea state |
| url | https://www.mdpi.com/2077-1312/9/8/826 |
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