Role of Transient Characteristics in Fish Trajectory Modeling

In this experiment, we analyzed live fish (silver carp) trajectories recorded in an experimental vertical-slot fishway. Combined with a numerical simulation, we demonstrated that randomness shown in fish trajectories might not merely be attributed to the fish’s random choices in its swimming, but co...
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Autor*in:	Gao Zhu [verfasserIn] Zuhao Zhou [verfasserIn] Helge I Andersson [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2020

Schlagwörter:	fishway trajectory CFD measurement modeling

Übergeordnetes Werk:	In: Sustainability - MDPI AG, 2009, 12(2020), 17, p 6765
Übergeordnetes Werk:	volume:12 ; year:2020 ; number:17, p 6765

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/su12176765

Katalog-ID:	DOAJ01410458X

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520			\|a In this experiment, we analyzed live fish (silver carp) trajectories recorded in an experimental vertical-slot fishway. Combined with a numerical simulation, we demonstrated that randomness shown in fish trajectories might not merely be attributed to the fish’s random choices in its swimming, but could also be a consequence of adaption to the bulk unsteady turbulent flow structures. Simple superposition of a fish trajectory on the time-averaged flow field obtained either by interpolating on discrete point measurements or numerical simulation data is not an ideal method for description of fish movement. How to model the fish paths in transient flow and the necessity of simultaneous recording of the flow field and the fish locomotion are challenging topics. We also discussed the possible integration of currently existing methods to promote the development of fish trajectory modeling.
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allfieldsSound	10.3390/su12176765 doi (DE-627)DOAJ01410458X (DE-599)DOAJ91aed5cf3fe24ac6933eac5467c3c0a7 DE-627 ger DE-627 rakwb eng TD194-195 TJ807-830 GE1-350 Gao Zhu verfasserin aut Role of Transient Characteristics in Fish Trajectory Modeling 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier In this experiment, we analyzed live fish (silver carp) trajectories recorded in an experimental vertical-slot fishway. Combined with a numerical simulation, we demonstrated that randomness shown in fish trajectories might not merely be attributed to the fish’s random choices in its swimming, but could also be a consequence of adaption to the bulk unsteady turbulent flow structures. Simple superposition of a fish trajectory on the time-averaged flow field obtained either by interpolating on discrete point measurements or numerical simulation data is not an ideal method for description of fish movement. How to model the fish paths in transient flow and the necessity of simultaneous recording of the flow field and the fish locomotion are challenging topics. We also discussed the possible integration of currently existing methods to promote the development of fish trajectory modeling. fishway trajectory CFD measurement modeling Environmental effects of industries and plants Renewable energy sources Environmental sciences Zuhao Zhou verfasserin aut Helge I Andersson verfasserin aut In Sustainability MDPI AG, 2009 12(2020), 17, p 6765 (DE-627)610604120 (DE-600)2518383-7 20711050 nnns volume:12 year:2020 number:17, p 6765 https://doi.org/10.3390/su12176765 kostenfrei https://doaj.org/article/91aed5cf3fe24ac6933eac5467c3c0a7 kostenfrei https://www.mdpi.com/2071-1050/12/17/6765 kostenfrei https://doaj.org/toc/2071-1050 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4367 GBV_ILN_4700 AR 12 2020 17, p 6765
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callnumber-first	T - Technology
author	Gao Zhu
spellingShingle	Gao Zhu misc TD194-195 misc TJ807-830 misc GE1-350 misc fishway misc trajectory misc CFD misc measurement misc modeling misc Environmental effects of industries and plants misc Renewable energy sources misc Environmental sciences Role of Transient Characteristics in Fish Trajectory Modeling
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topic_title	TD194-195 TJ807-830 GE1-350 Role of Transient Characteristics in Fish Trajectory Modeling fishway trajectory CFD measurement modeling
topic	misc TD194-195 misc TJ807-830 misc GE1-350 misc fishway misc trajectory misc CFD misc measurement misc modeling misc Environmental effects of industries and plants misc Renewable energy sources misc Environmental sciences
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title	Role of Transient Characteristics in Fish Trajectory Modeling
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title_sort	role of transient characteristics in fish trajectory modeling
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title_auth	Role of Transient Characteristics in Fish Trajectory Modeling
abstract	In this experiment, we analyzed live fish (silver carp) trajectories recorded in an experimental vertical-slot fishway. Combined with a numerical simulation, we demonstrated that randomness shown in fish trajectories might not merely be attributed to the fish’s random choices in its swimming, but could also be a consequence of adaption to the bulk unsteady turbulent flow structures. Simple superposition of a fish trajectory on the time-averaged flow field obtained either by interpolating on discrete point measurements or numerical simulation data is not an ideal method for description of fish movement. How to model the fish paths in transient flow and the necessity of simultaneous recording of the flow field and the fish locomotion are challenging topics. We also discussed the possible integration of currently existing methods to promote the development of fish trajectory modeling.
abstractGer	In this experiment, we analyzed live fish (silver carp) trajectories recorded in an experimental vertical-slot fishway. Combined with a numerical simulation, we demonstrated that randomness shown in fish trajectories might not merely be attributed to the fish’s random choices in its swimming, but could also be a consequence of adaption to the bulk unsteady turbulent flow structures. Simple superposition of a fish trajectory on the time-averaged flow field obtained either by interpolating on discrete point measurements or numerical simulation data is not an ideal method for description of fish movement. How to model the fish paths in transient flow and the necessity of simultaneous recording of the flow field and the fish locomotion are challenging topics. We also discussed the possible integration of currently existing methods to promote the development of fish trajectory modeling.
abstract_unstemmed	In this experiment, we analyzed live fish (silver carp) trajectories recorded in an experimental vertical-slot fishway. Combined with a numerical simulation, we demonstrated that randomness shown in fish trajectories might not merely be attributed to the fish’s random choices in its swimming, but could also be a consequence of adaption to the bulk unsteady turbulent flow structures. Simple superposition of a fish trajectory on the time-averaged flow field obtained either by interpolating on discrete point measurements or numerical simulation data is not an ideal method for description of fish movement. How to model the fish paths in transient flow and the necessity of simultaneous recording of the flow field and the fish locomotion are challenging topics. We also discussed the possible integration of currently existing methods to promote the development of fish trajectory modeling.
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