Pregled bibliografske jedinice broj: 479433
Application of an Artificial Neural Network to the Selection of a Maximum Efficiency Ship Screw Propeller
Application of an Artificial Neural Network to the Selection of a Maximum Efficiency Ship Screw Propeller // Journal of Ship Production and Design (ex Journal of Ship Production), 26 (2010), 3; 199-205 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 479433 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Application of an Artificial Neural Network to the Selection of a Maximum Efficiency Ship Screw Propeller
Autori
Matulja, Dunja ; Dejhalla, Roko ; Bukovac, Ozren
Izvornik
Journal of Ship Production and Design (ex Journal of Ship Production) (8756-1417) 26
(2010), 3;
199-205
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
Propellers
Sažetak
The idea of the present study is to apply the advantages of neural networks to the choice of an optimum ship screw propeller as an introduction to more complex ship design problems. The neural network was created and trained to provide the characteristics of the maximum efficiency propeller. To train the network, data regarding the blade number, advance speed, delivered power, rate of revolution, diameter, pitch ratio, and expanded area ratio as well as thrust and efficiency were set as inputs and outputs. The testing of the network proved its efficiency, which makes it a reliable tool for the preliminary screw propeller selection.
Izvorni jezik
Engleski
Znanstvena područja
Brodogradnja
POVEZANOST RADA
Projekti:
069-0691668-1725 - Numeričke simulacije i optimizacija brodskih dizelskih motora (Medica, Vladimir, MZOS ) ( CroRIS)
069-0691736-1667 - Numeričko modeliranje hidrodinamičkog opterećenja i odziva pomorskih objekata (Prpić-Oršić, Jasna, MZOS ) ( CroRIS)
Ustanove:
Tehnički fakultet, Rijeka
