Development of a Generalized MMG-model for KCS Transient Maneuvering in Calm Water and Waves

Abstract

Research on ship maneuverability is steadily progressing due to the advancement of CFD and tank test technology. Turning motion in calm water and waves can be predicted with practical accuracy. However, in reality, ship maneuvers with a fixed rudder angle such asturning are rare. Actually, more complicated maneuvers are performed. For example, a ship navigating under a time-varying external disturbance steers the rudder port and starboard in relation to the desirable course. In addition, complex ship maneuvers are performed according to the purpose, such as ship maneuvers that aim to increase rudder force by using the booster effect of the propeller,and ship maneuvers that involve reversing the propeller (including backing). One of these maneuvering characteristics is that thereis no stationary motion such as a steady turn. Therefore, we call them transient maneuvers here. Research on the transient maneuvers has been conducted as part of research on zig-zag maneuvers, and berthing and unberthing of ships. However, due to the complexity of the phenomenon and the difficulty in modeling the hydrodynamic force characteristics, a satisfactory maneuvering prediction modelhas not yet been developed. The MMG model has limitations in application, such as the forward speed being dominant and the hull drift angle being up to about 30deg like turning motion. Therefore, the MMG model cannot apply to the motions with a large hull drift angle, stopping motions with backing, and motions when the propeller is reversed. There is a need to remove this limitation and create a more general model (here called a generalized MMG model; gMMG). We propose here to develop the gMMG model for the transient maneuvering predictions in calm water and waves.The objectives of the proposed research are:1.Development of a generalized MMG-model forKCS transient maneuvering in calm water and waves 2.Leverage/extend current steady state maneuvering physical understanding and experimental and prediction capability for grand challenge of transient maneuverers: zig-zag maneuvers, stopping by propeller reversing, acceleration turning, and backing motion with steering.3.Investigations of hydrodynamic interactions between hull, propeller, and rudder including the effects environmental conditions (waves).4.Advancement of experimental and prediction capability and physical understanding.5.Provide capability for improved naval ship designs and aid for standardization activities.In the research, the targetship is the KCS, which has been widely used for the scaled model tests. The measurement data obtained in this research will be usedas benchmark data for international research collaboration. The approach for development of the gMMG model is as follows:1.Implementation of captive model tests to capture the hydrodynamic force characteristics2.Identification of hydrodynamic force coefficients (modelling) for gMMG model3.Implementation of free running model tests to capture the motion characteristics4.Validation of maneuvering simulations using gMMG modelWhen predicting the maneuvering motions using the gMMG model, it is necessary to determine the hydrodynamic force characteristics related to the maneuvering motions in the form of parameters or coefficients. They are identified usingthe captive model test results. In the captive model tests, the hydrodynamic forces acting on the ship, rudder, and propeller are measured by varying parameters such as the ship speed, hull drift angle, yaw rate, propeller revolution, and rudder angle. Therefore,the number of measurement points may become enormous. To supplement the captive model tests, with the cooperation of research collaborators, we will consider using captive CFD and free-run CFD.To validate the maneuvering simulations using the developed gMMG model, we set up representative motions for the transient maneuvers and conduct free-running model tests.

Document Details

Document Type
DoD Grant Award
Publication Date
Nov 09, 2024
Source ID
N629092412112

Entities

People

  • Yasuhisa Hashizume

Organizations

  • Office of Naval Research
  • United States Navy

Tags

Readers

  • Distributed Systems and Data Platform Development
  • Marine Hydrodynamics

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Bayesian Inference