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Explicit prediction of expanding channels hydraulic jump characteristics using gene expression programming approach

机译：利用基因表达程序设计方法明确预测扩径水力跃变特征

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摘要

Hydraulic jump is a useful means of dissipating excess energy of a supercritical flow so that objectionable scour downstream is minimized. The present study applies gene expression programming (GEP) to estimate hydraulic jump characteristics in sudden expanding channels. Three types of expanding channels were considered: channels without appurtenances, with a central sill, and with a negative step. 1,000 experimental data were considered as input data to develop models. The results proved the capability of GEP in predicting hydraulic jump characteristics in expanding channels. It was found that the developed models for channel with a central sill performed better than other channels. In the jump length prediction, the model with input parameters Fr _(1)and (y _(2)— y _(1))/y_(1), and in the sequent depth ratio and relative energy dissipation prediction the model with input parameters Fr _(1)and y _(1)/ B led to more accurate outcomes ( Fr _(1), y _(1), y _(2), and B are Froude number, sequent depth of upstream and downstream, and expansion ratio, respectively). Sensitivity analysis showed that Fr _(1)had the key role in modeling. The GEP models were compared with existing empirical equations and it was found that the GEP models yielded better results. It was also observed that channel and appurtenances geometry affected the modeling.
机译：水力跃变是消散超临界流多余能量的有用手段，因此可将下游有害的冲刷最小化。本研究应用基因表达编程（GEP）来估计突然扩展的通道中的水力跳跃特征。考虑了三种类型的扩展渠道：没有附属设备，带有中央门槛和带有负面阶梯的渠道。将1,000个实验数据视为开发模型的输入数据。结果证明了GEP预测扩张通道水力跃变特征的能力。结果发现，开发的带有中央门槛的通道模型的性能优于其他通道。在跳跃长度预测中，具有输入参数Fr _（1）和（y _（2）-y _（1））/ y_（1）的模型，在后续深度比和相对能量耗散预测中，模型具有输入参数Fr _（1）和y _（1）/ B导致更准确的结果（Fr _（1），y _（1），y _（2）和B是弗洛德数，上游的后续深度和下游和膨胀率）。敏感性分析表明，Fr _（1）在建模中起关键作用。将GEP模型与现有的经验方程进行比较，发现GEP模型产生了更好的结果。还观察到通道和附件的几何形状会影响建模。

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