基于贝叶斯网络理论与仿生技术的翼形量水槽优化

翼形量水槽的工作原理决定其工作必然导致一定的水头损失，保证量水槽自由出流的渠道比降随水头损失增大而增大，本文希望通过仿生优化减小翼形量水槽工作水头损失，扩大其在平原灌区渠道的适用范围。本文探索性的利用鸟类翅膀飞行减阻特性选取3种鸟翼作为仿生原型，截取仿生翼形曲线10条，按10个攻角水平应用处理得到78条仿生翼形量水槽外轮廓线，选取3个收缩比开展3种流量工况的仿真试验，采用极差分析法评价仿生翼形量水槽外轮廓线二因素的显著性水平和优水平，较新颖的运用贝叶斯网络图模型推理分析方法解决仿生翼形曲线和攻角优组合的不确定性问题，通过模型试验验证应用可行性。结果表明：翼形曲线是影响优化的主要因素，赛鸽翼（1）为优曲线、－10°为优攻角；攻角－5°与翼形曲线赛鸽翼（1）联合作用效果最佳，将翼形曲线赛鸽翼（1）按攻角－5°应用处理的仿赛鸽翼截面曲线作为优选仿生翼形量水槽外轮廓线；新型仿赛鸽翼截面曲线型量水槽各工况临界淹没出流状态：测流精度很高（测流平均误差约1.28%）、壅水高度平均降低7.46%、水头损失平均降低5.81%、最大临界淹没度可达0.933、上游佛汝德数均小于0.4（可形成平稳缓流）、最小工作比降可达1/4960。综上，利用仿生技术优化翼形量水槽可行，新型仿赛鸽翼截面曲线型量水槽综合量水性能很好，可用于灌区小比降渠道精细量水。

Optimization of Wing-shaped Measuring Flume Based on Bayesian Network Theory and Bionic Technology

The working principle of wing-shaped measuring flume determines that its work will inevitably lead to a certain head loss, and the channel gradient to ensure the free flow of measuring flume will increase with the increase of head loss. This paper hopes to reduce the working head loss of wing-shaped measuring flume by bionic optimization and expand its application scope in plain irrigation channels. In this paper, three kinds of bird wings are selected as bionic prototypes by exploring the drag reduction characteristics of bird wings, 10 bionic wing curves are intercepted, and 78 bionic wing-shaped measuring flume contour lines are obtained according to 10 angles of attack. Three shrinkage ratios are selected to carry out simulation tests under three flow conditions. Range analysis method is used to evaluate the significance level and superior level of the two factors of bionic wing-shaped measuring flume contour lines. Bayesian network diagram model reasoning analysis method is used to solve the uncertainty problem of the optimal combination of bionic wing-shaped curves and angles of attack, and the application feasibility is verified by model test. The results show that the airfoil curve is the main factor affecting the optimization, and the racing pigeon wing (1) is the optimal curve and-10 is the optimal angle of attack. The combination effect of the angle of attack of-5 and the wing-shaped curve racing pigeon wing (1) is the best, and the cross-section curve of the simulated racing pigeon wing which is processed by the wing-shaped curve racing pigeon wing (1) according to the angle of attack of-5 is used as the preferred contour of the bionic wing-shaped measuring flume. The critical inundation state of the new type of pigeon-wing-section curve measuring flume under various working conditions is as follows: the flow measurement accuracy is very high (the average error of flow measurement is about 1.28%), the backwater height is reduced by 7.46% on average, the head loss is reduced by 5.81% on average, the maximum critical inundation degree can reach 0.933, the upstream Froude number is less than 0.4 (stable slow flow can be formed), and the minimum working gradient can reach 1/40. To sum up, it is feasible to optimize the wing-shaped measuring flume with bionic technology, and the new type of curve-shaped measuring flume imitating the cross section of racing pigeon wings has good comprehensive water measuring performance, and can be used for fine water measuring in small gradient channels in irrigation areas.