Parametric Identification of Hydrodynamic Characteristics From Ship Maneuvering Trials Using Neural Networks
M.R. Haddara, G. C. W. Sabin
Abstract
M.R. Haddara, G. C. W. Sabin
Abstract
The success of a ship in performing its mission depends on the ability of the naval architect to understand how the design features of a ship affect its performance. The ability to relate the performance of a ship in a seaway to its design features is one of the basic goals of a naval architect. Ship's performance is a matrix of parameters that describe its stability, maneuverability, response to wave excitation, ... etc. The efforts in relating design features to the different parameters of the performance matrix have met different degrees of success, greater with regard to powering and seakeeping and with regard to maneuverability.
OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
The success of a ship in performing its mission depends on the ability of the naval architect to understand how the design features of a ship affect its performance. The ability to relate the performance of a ship in a seaway to its design features is one of the basic goals of a naval architect. Ship's performance is a matrix of parameters that describe its stability, maneuverability, response to wave excitation, ... etc. The efforts in relating design features to the different parameters of the performance matrix have met different degrees of success, greater with regard to powering and seakeeping and with regard to maneuverability.
Key concepts: Seakeeping, Naval architecture, Marine engineering, Identification (biology), Artificial neural network, Engineering, Parametric statistics, Parametric design