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基于个体的幼鳗运动模型,通过计算流体动力学得出的流场进行参数化,为改进鱼道设计提供了依据。

Individual-based model of juvenile eel movement parametrized with computational fluid dynamics-derived flow fields informs improved fish pass design.

作者信息

Padgett Thomas E, Thomas Robert E, Borman Duncan J, Mould David C

机构信息

Centre for Doctoral Training in Fluid Dynamics, University of Leeds, Leeds, LS2 9JT, UK.

Energy and Environment Institute, University of Hull, Hull, HU6 7RX, UK.

出版信息

R Soc Open Sci. 2020 Jan 15;7(1):191505. doi: 10.1098/rsos.191505. eCollection 2020 Jan.

DOI:10.1098/rsos.191505
PMID:32218968
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7029934/
Abstract

European eel populations have declined markedly in recent decades, caused in part by in-stream barriers, such as weirs and pumping stations, which disrupt the upstream migration of juvenile eels, or elvers, into rivers. Eel passes, narrow sloping channels lined with substrata that enable elvers to ascend, are one way to mitigate against these barriers. Currently, studded eel tiles are a popular substrate. This study is the first to evaluate the flow fields within studded eel tiles and to model the swimming performance of elvers using cellular automata (CA) and individual- (or agent-) based models. Velocities and flow depths predicted by a computational fluid dynamics model of studded eel tiles are first validated against published values for a single installation angle-discharge combination. The validated model is then used to compute three-dimensional flow fields for eel passes at five different installation angles and three inflow discharges. CA and individual-based models are employed to assess upstream passage efficiency for a range of elver sizes. The individual-based model approximates measured passage efficiencies better than the CA model. Passage efficiency is greatest for shallow slopes, low discharges and large elvers. Results are synthesized into an easy-to-understand graphic to help practitioners improve eel pass designs.

摘要

近几十年来,欧洲鳗鱼种群数量显著下降,部分原因是诸如堰闸和泵站等河道内障碍物,这些障碍物阻碍了幼鳗(鳗线)向上游洄游进入河流。鳗鱼通道是一种缓解这些障碍物影响的方法,它是内衬基质的狭窄倾斜通道,能让鳗线向上游游动。目前,带孔鳗鱼瓷砖是一种常用的基质。本研究首次评估了带孔鳗鱼瓷砖内的流场,并使用细胞自动机(CA)和基于个体(或智能体)的模型来模拟鳗线的游泳性能。首先,针对单个安装角度-流量组合的已发表数据,对带孔鳗鱼瓷砖的计算流体动力学模型预测的速度和水深进行验证。然后,使用经过验证的模型计算五个不同安装角度和三种入流流量下鳗鱼通道的三维流场。采用细胞自动机模型和基于个体的模型评估一系列鳗线尺寸的上游洄游效率。基于个体的模型比细胞自动机模型更接近实测的洄游效率。对于浅坡度、低流量和大型鳗线,洄游效率最高。研究结果被综合成一张易于理解的图表,以帮助从业者改进鳗鱼通道设计。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f256/7029934/3a50d327cf4d/rsos191505-g11.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f256/7029934/91d15d205b6a/rsos191505-g1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f256/7029934/e02219cc69a0/rsos191505-g2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f256/7029934/3a5ee0d3de13/rsos191505-g3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f256/7029934/305838ef3dff/rsos191505-g4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f256/7029934/854f82f81e7f/rsos191505-g5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f256/7029934/c4daaa13516c/rsos191505-g6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f256/7029934/10aa0e9fd771/rsos191505-g7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f256/7029934/55f17699a221/rsos191505-g8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f256/7029934/43d47c898c20/rsos191505-g9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f256/7029934/f3a28e5aba01/rsos191505-g10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f256/7029934/3a50d327cf4d/rsos191505-g11.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f256/7029934/91d15d205b6a/rsos191505-g1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f256/7029934/e02219cc69a0/rsos191505-g2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f256/7029934/3a5ee0d3de13/rsos191505-g3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f256/7029934/305838ef3dff/rsos191505-g4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f256/7029934/854f82f81e7f/rsos191505-g5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f256/7029934/c4daaa13516c/rsos191505-g6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f256/7029934/10aa0e9fd771/rsos191505-g7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f256/7029934/55f17699a221/rsos191505-g8.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f256/7029934/43d47c898c20/rsos191505-g9.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f256/7029934/f3a28e5aba01/rsos191505-g10.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f256/7029934/3a50d327cf4d/rsos191505-g11.jpg

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本文引用的文献

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Proc Natl Acad Sci U S A. 2014 Apr 8;111(14):5277-82. doi: 10.1073/pnas.1311874111. Epub 2014 Mar 24.