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Hydrodynamic Modeling and Parameter Identification of a Bionic Underwater Vehicle: RobDact

In this paper, the hydrodynamic modeling and parameter identification of the RobDact, a bionic underwater vehicle inspired by Dactylopteridae, are carried out based on computational fluid dynamics (CFD) and force measurement experiment. Firstly, the paper briefly describes the RobDact, then establis...

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Detalles Bibliográficos
Autores principales: Cao, Qiyuan, Wang, Rui, Zhang, Tiandong, Wang, Yu, Wang, Shuo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AAAS 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9494701/
https://www.ncbi.nlm.nih.gov/pubmed/36285303
http://dx.doi.org/10.34133/2022/9806328
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author Cao, Qiyuan
Wang, Rui
Zhang, Tiandong
Wang, Yu
Wang, Shuo
author_facet Cao, Qiyuan
Wang, Rui
Zhang, Tiandong
Wang, Yu
Wang, Shuo
author_sort Cao, Qiyuan
collection PubMed
description In this paper, the hydrodynamic modeling and parameter identification of the RobDact, a bionic underwater vehicle inspired by Dactylopteridae, are carried out based on computational fluid dynamics (CFD) and force measurement experiment. Firstly, the paper briefly describes the RobDact, then establishes the kinematics model and rigid body dynamics model of the RobDact according to the hydrodynamic force and moment equations. Through CFD simulations, the hydrodynamic force of the RobDact at different speeds is obtained, and then, the hydrodynamic model parameters are identified. Furthermore, the measurement platform is developed to obtain the relationship between the thrust generated by the RobDact and the input fluctuation parameters. Finally, by combining the rigid body dynamics model and the fin thrust mapping model, the hydrodynamic model of the RobDact at different motion states is constructed.
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spelling pubmed-94947012022-10-24 Hydrodynamic Modeling and Parameter Identification of a Bionic Underwater Vehicle: RobDact Cao, Qiyuan Wang, Rui Zhang, Tiandong Wang, Yu Wang, Shuo Cyborg Bionic Syst Research Article In this paper, the hydrodynamic modeling and parameter identification of the RobDact, a bionic underwater vehicle inspired by Dactylopteridae, are carried out based on computational fluid dynamics (CFD) and force measurement experiment. Firstly, the paper briefly describes the RobDact, then establishes the kinematics model and rigid body dynamics model of the RobDact according to the hydrodynamic force and moment equations. Through CFD simulations, the hydrodynamic force of the RobDact at different speeds is obtained, and then, the hydrodynamic model parameters are identified. Furthermore, the measurement platform is developed to obtain the relationship between the thrust generated by the RobDact and the input fluctuation parameters. Finally, by combining the rigid body dynamics model and the fin thrust mapping model, the hydrodynamic model of the RobDact at different motion states is constructed. AAAS 2022-05-31 /pmc/articles/PMC9494701/ /pubmed/36285303 http://dx.doi.org/10.34133/2022/9806328 Text en Copyright © 2022 Qiyuan Cao et al. https://creativecommons.org/licenses/by/4.0/Exclusive Licensee Beijing Institute of Technology Press. Distributed under a Creative Commons Attribution License (CC BY 4.0).
spellingShingle Research Article
Cao, Qiyuan
Wang, Rui
Zhang, Tiandong
Wang, Yu
Wang, Shuo
Hydrodynamic Modeling and Parameter Identification of a Bionic Underwater Vehicle: RobDact
title Hydrodynamic Modeling and Parameter Identification of a Bionic Underwater Vehicle: RobDact
title_full Hydrodynamic Modeling and Parameter Identification of a Bionic Underwater Vehicle: RobDact
title_fullStr Hydrodynamic Modeling and Parameter Identification of a Bionic Underwater Vehicle: RobDact
title_full_unstemmed Hydrodynamic Modeling and Parameter Identification of a Bionic Underwater Vehicle: RobDact
title_short Hydrodynamic Modeling and Parameter Identification of a Bionic Underwater Vehicle: RobDact
title_sort hydrodynamic modeling and parameter identification of a bionic underwater vehicle: robdact
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9494701/
https://www.ncbi.nlm.nih.gov/pubmed/36285303
http://dx.doi.org/10.34133/2022/9806328
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