Datasets for "Importance of Data Richness in Identification of Ship Maneuvering Hydrodynamic Models"

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Authors: Vallabh Deogaonkar, Abhilash Sharma Somayajula
Cited by: 0

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