首页> 外文会议>Hydrovision International Conference and Exhibition >DEVELOPMENT AND APPLICATION OF A MECHANISTIC MODEL TO PREDICT JUVENILE SALMON SWIM PATHS
【24h】

DEVELOPMENT AND APPLICATION OF A MECHANISTIC MODEL TO PREDICT JUVENILE SALMON SWIM PATHS

机译:一种机制模型的开发与应用预测少年鲑鱼游泳道

获取原文

摘要

The understanding of the relation between juvenile salmon behavior and flow conditions is of paramount importance to design fish bypass systems. The combined analysis of measured swim paths and Computational Fluid Dynamics (CFD) simulations can provide that understanding. This paper presents the development and application of a mechanistic model tailored to simulate swimming patterns of downstream migrants in forebays of dams. The model simulates different swimming behavior for Chinook, Sockeye, and Steelhead. Movements of fish are simulated using a two-tier approach. First, fish decisions are based on probability distributions which are developed from correlating measured swim paths and CFD results. Second, the movement of fish is simulated by solving Newton’s second law. Swim paths for Chinook were measured at Rocky Reach Dam and for Sockeye and Steelhead at Priest Rapids Dam. The numerical model was tested for the three species at Priest Rapids Dam. Results show that the model is capable of predicting fish forebay residence times, on average, within 20% of relative error. Predictions of final migration route are on average within 12% of measured values. The methodology presented in this paper has the potential to allow the application of knowledge gained from hydroacoustic studies developed in one dam to a different dam.
机译:对少年三文鱼行为和流动条件之间的关系的理解至关重要设计鱼旁路系统。测量的游泳路径和计算流体动力学(CFD)模拟的综合分析可以提供这种理解。本文介绍了机械模型的制定和应用,以模拟水坝前下游移民的游泳模式。该模型模拟了Chinook,Sockeye和Steelhead的不同游泳行为。使用两层方法模拟鱼类的运动。首先,鱼类决策是基于从相关测量的游泳路径和CFD结果相关的概率分布。其次,通过解决牛顿的第二法来模拟鱼的运动。 Chinook的游泳道路是在岩石到达水坝和牧师急流大坝的钢铁和钢头上测量的。在牧师迅速水坝的三种物种测试了数值模型。结果表明,该模型能够在相对误差的20%以内预测鱼类前宿宿时间。最终迁移路线的预测平均值在测量值的12%以内。本文提出的方法具有允许在一个大坝中开发的水声学研究中获得的知识应用于不同的大坝。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号