竖缝式鱼道内短须裂腹鱼上溯行为模拟

    Simulation of upstream behavior of Schizothorax wangchiachii in vertical slot fishway

    • 摘要: 鱼类行为与水力因子之间的关系是鱼道结构优化的关键。为了探索鱼类行为与水力因子之间的关系。该研究基于欧拉-拉格朗日智能体方法(eulerian-lagrangian-agent method,ELAM)方法,提出兼顾多种水力因子和鱼类变速游动的鱼类上溯行为预测模型。首先,采用主成分分析方法计算流速、湍动能、涡量和应变率对短须裂腹鱼上溯行为的影响;然后,基于鱼类运动特点构建包含上溯、避障、惯性和随机行为的行为模型;并通过水流速度与鱼类游泳速度的响应关系构建鱼类可变游泳速度模型;最后,利用所提模型在竖缝式鱼道内模拟鱼类上溯轨迹,并对涡量、应变率、湍动能和流速对鱼类上溯行为的影响进行分析。结果表明:模拟特征轨迹与实测特征轨迹误差较小,R2为0.935,模型预测精度较高;涡量在鱼类上溯过程中有关键作用,是确保鱼类上溯方向的关键水力因子。所提上溯鱼类行为预测模型可为鱼道设计和优化提供参考。

       

      Abstract: Fishways are an important engineering measures designed to assist fish in migrating upstream over a dam. However, the initial construction of fishways does not consider the combination of hydraulic characteristics and fish behavior, leading to poor effectiveness. The optimization of fishway structure must evaluate the relationship between fish behavior and hydraulic factors. It is necessary to develop an effective mathematical model to simulate fish upstream migratory for exploring the relationship between fish behavior and hydraulic factors. In this study, a model for predicting upstream fish behavior considering multiple hydraulic factors and variable-speed swimming of Schizothorax wangchiachii was proposed, based on the behavior data of S. wangchiachii obtained from physical experiments and the Euler-Lagrangian-agent method (ELAM). The flow velocity, turbulent kinetic energy, vorticity, and strain rate were used as the key hydraulic factors driving fish movement. Firstly, principal component analysis was used to calculate the effects of flow velocity, turbulent kinetic energy, vorticity, and strain rate on the upstream behavior of S. wangchiachii. Next, the preference range of S. wangchiachii for these factors was determined through statistical analysis. Then, a fish behavior model was developed based on the characteristics of fish movement, it includes upstream behavior (the direction of fish movement is opposite to the direction of water flow), obstacle avoidance behavior (fish movement avoids obstacles during movement), inertia behavior(when the fish passes through the vertical seam, it will move forward some distance due to inertia), and random behavior (imitating the random movement of fish under natural conditions). Additionally, a variable fish swimming speed model was developed by analyzing the response relationship between water flow velocity and fish swimming speed. Finally, the proposed model was used to simulate the fish’s upstream trajectory in the vertical slot fishway. The characteristic trajectories of the both simulated and test trajectories were calculated using a ninth-order polynomial regression model. These characteristic trajectories were then compared and analyzed to verify the model’s reliability. To further analyze the impact of vorticity, strain rate, flow velocity and turbulent kinetic energy on fish upstream behavior, four schemes of control experiments were designed. Control experiments were realized by removing the influence weight of vorticity, strain rate, turbulent kinetic energy, and flow velocity in the model, respectively and not changing the fish’s preference range of hydraulic factors. The experimental results indicate that S. wangchiachii has distinct preference ranges for flow velocity, turbulent kinetic energy, vorticity, and strain rate. The error between the characteristic trajectory of the simulated and test trajectory is small (R2 = 0.935, RMSE = 0.043 m), it suggests that the proposed model in this study can accurately predict the upstream behavior of S. wangchiachii in the fishway. Vorticity, strain rate, turbulent kinetic energy and flow velocity have different effects on the upstream behavior of S. wangchiachii. When the effects of vorticity, strain rate, turbulent kinetic energy and flow velocity on the fish upstream behavior are not considered respectively, the R2 of the simulated trajectory and the test trajectory are 0.526, 0.799, 0.861 and 0.910, respectively. Correspondingly, the RMSE values were 0.127 m, 0.09 m, 0.074 m, and 0.054 m, respectively. These errors are all lower than those observed in the original scheme. Therefore, the influence of the above four hydraulic factors on fish tracing can not be ignored. The weight coefficient of vorticity is 0.246, which is relatively small, but it plays a key role in the process of fish upstream to ensure that fish will not get lost. The fish upstream behavior prediction model proposed in this study provides a reference for designing and optimizing fishways.

       

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