Datasets for "Importance of Data Richness in Identification of Ship Maneuvering Hydrodynamic Models"
Abstract
Dataset for the paper:"Importance of Data Richness in Identification of Ship Maneuvering Hydrodynamic Models" Authors:Vallabh DeogaonkarAbhilash SomayajulaMarine Autonomous Vessels LaboratoryDepartment of Ocean EngineeringIndian Institute of Technology Madras, India Description:This archive contains trajectory datasets generated through simulation for the study of system identification of ship maneuvering models. The datasets were usedfor training hydrodynamic coefficient identification models in the above-mentioned paper. The trajectories correspond to simulated free-running maneuvers of the vessel models described in the manuscript. These trajectories were generated using thegoverning maneuvering equations and hydrodynamic coefficients provided in the paper. File contents:- KCS : Training trajectories for KCS vessel model - StandardManeuversLit - StandardManeuversExt - DEM- Mariner : Training trajectories for Mariner vessel model - StandardManeuversLit - StandardManeuversExt - DEM Each dataset contains time histories of nondimensional vessel states used for system identification. For details of the governing equations, hydrodynamic coefficients, and maneuverdesign, please refer to the manuscript.
Fields of Study & Subjects
Ship Hydrodynamics and Maneuverability
Maritime Navigation and Safety
Control Systems and Identification
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 15 March 2026
- Language
- EN
- Document type
- Dataset