Marine propeller optimisation tools for scenario-based design
Doktorsavhandling, 2022
marine propeller design
machine learning
scenario-based design
wind propulsion
interactive optimisation
user-code interaction
cavitation nuisance
Författare
Ioli Gypa
Chalmers, Mekanik och maritima vetenskaper, Marin teknik
Interactive evolutionary computation for propeller design optimization of wind-assisted vessels
AIAA AVIATION 2020 FORUM,;Vol. 1 PartF(2020)p. 1-10
Paper i proceeding
Propeller optimization by interactive genetic algorithms and machine learning
Ship Technology Research,;Vol. 70(2023)p. 56-71
Artikel i vetenskaplig tidskrift
Propeller design procedure for a wind-assisted KVLCC2
Book of Abstracts of PRADS 2022!,;(2022)
Övrigt konferensbidrag
Cavitation nuisance identification through machine learning during propeller optimisation
Proceedings of the seventh International Symposium on Marine Propulsors - smp'22,;(2022)p. 384-391
Paper i proceeding
Controllable-pitch propeller design process for a wind-powered car-carrier optimising for total energy consumption
Ocean Engineering,;Vol. 269(2023)
Artikel i vetenskaplig tidskrift
Marine propeller optimisation through user interaction and machine learning for advanced blade design scenarios
Ships and Offshore Structures,;Vol. In Press(2023)
Artikel i vetenskaplig tidskrift
Ämneskategorier
Maskinteknik
Energiteknik
Beräkningsmatematik
Drivkrafter
Hållbar utveckling
Styrkeområden
Transport
ISBN
978-91-7905-760-2
Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 5226
Utgivare
Chalmers