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Pregled bibliografske jedinice broj: 1232415

Joint optimisation for improving ship energy efficiency considering speed and trim control


Fan, Ailong; Yang, Jian; Yang, Liu; Liu, Weiqin; Vladimir, Nikola
Joint optimisation for improving ship energy efficiency considering speed and trim control // Transportation research part d-transport and environment, 113 (2022), 103527, 19 doi:10.1016/j.trd.2022.103527 (međunarodna recenzija, članak, znanstveni)


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Naslov
Joint optimisation for improving ship energy efficiency considering speed and trim control

Autori
Fan, Ailong ; Yang, Jian ; Yang, Liu ; Liu, Weiqin ; Vladimir, Nikola

Izvornik
Transportation research part d-transport and environment (1361-9209) 113 (2022); 103527, 19

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Inland river ship ; Ship energy efficiency ; Speed-trim joint optimisation ; Computational fluid dynamics ; Artificial neural networks

Sažetak
Operational optimisation is one of the most important methods for reducing energy consumption and emissions related to ships. In this study, a speed-trim joint optimisation method is proposed. First, the propulsion power for various operating conditions was estimated by numerical simulation, two-dimensional method, and ship-engine-propeller principle. Second, the obtained data, consisting of ship power, draft, trim angle, and speed, were further expanded to form a joint optimisation decision database using the artificial neural network method. Subsequently, a dynamic programming algorithm was used to calculate the optimal speed for each segment of the voyage. The optimal trim angle corresponding to the speed was obtained based on the joint optimisation decision database. Finally, a 7500 ton inland bulk carrier was chosen as the case ship to validate the proposed method. The results showed that the method could reduce the total ship power consumption by up to 7.64%.

Izvorni jezik
Engleski

Znanstvena područja
Brodogradnja, Strojarstvo, Tehnologija prometa i transport



POVEZANOST RADA


Ustanove:
Fakultet strojarstva i brodogradnje, Zagreb

Profili:

Avatar Url Nikola Vladimir (autor)

Poveznice na cjeloviti tekst rada:

doi

Citiraj ovu publikaciju:

Fan, Ailong; Yang, Jian; Yang, Liu; Liu, Weiqin; Vladimir, Nikola
Joint optimisation for improving ship energy efficiency considering speed and trim control // Transportation research part d-transport and environment, 113 (2022), 103527, 19 doi:10.1016/j.trd.2022.103527 (međunarodna recenzija, članak, znanstveni)
Fan, A., Yang, J., Yang, L., Liu, W. & Vladimir, N. (2022) Joint optimisation for improving ship energy efficiency considering speed and trim control. Transportation research part d-transport and environment, 113, 103527, 19 doi:10.1016/j.trd.2022.103527.
@article{article, author = {Fan, Ailong and Yang, Jian and Yang, Liu and Liu, Weiqin and Vladimir, Nikola}, year = {2022}, pages = {19}, DOI = {10.1016/j.trd.2022.103527}, chapter = {103527}, keywords = {Inland river ship, Ship energy efficiency, Speed-trim joint optimisation, Computational fluid dynamics, Artificial neural networks}, journal = {Transportation research part d-transport and environment}, doi = {10.1016/j.trd.2022.103527}, volume = {113}, issn = {1361-9209}, title = {Joint optimisation for improving ship energy efficiency considering speed and trim control}, keyword = {Inland river ship, Ship energy efficiency, Speed-trim joint optimisation, Computational fluid dynamics, Artificial neural networks}, chapternumber = {103527} }
@article{article, author = {Fan, Ailong and Yang, Jian and Yang, Liu and Liu, Weiqin and Vladimir, Nikola}, year = {2022}, pages = {19}, DOI = {10.1016/j.trd.2022.103527}, chapter = {103527}, keywords = {Inland river ship, Ship energy efficiency, Speed-trim joint optimisation, Computational fluid dynamics, Artificial neural networks}, journal = {Transportation research part d-transport and environment}, doi = {10.1016/j.trd.2022.103527}, volume = {113}, issn = {1361-9209}, title = {Joint optimisation for improving ship energy efficiency considering speed and trim control}, keyword = {Inland river ship, Ship energy efficiency, Speed-trim joint optimisation, Computational fluid dynamics, Artificial neural networks}, chapternumber = {103527} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • Social Science Citation Index (SSCI)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus


Citati:





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