基于BP神经网络的复合型挑坎体型参数反演研究BP neural network-based study on inversion of shape parameter of composite flip bucket
张晓萍,张建民
摘要(Abstract):
以某大型水电站溢洪洞工程数据为主要设计依据,采用传统的水力学计算模型,以3种不同的水力参数——斜切角、挑射角及扩散角研究挑流鼻坎水舌落水范围,用挑距、水舌旋转的角度及水舌弧长对落水范围和冲刷强度进行描述。以经过水力计算并试验验证的溢洪洞48个挑流数据为样本,用BP神经网络模型扩大数据样本,再通过BP神经网络优化和反演模型,预测约束水舌落水范围内,水舌弧长最大对应最优的挑坎体型设计参数。结果显示,当约束水舌落水范围靠近河道中泓线,且水舌弧长为最长、冲刷最小时,对应最优挑坎斜切角为25°、挑射角为29°、扩散角为6°。分析表明,此方法可在约束条件下实现最优挑坎体型设计,在效率上、效果上优于物理模型试验和相关数值模拟研究,为实际工程应用BP神经网络模型反演复合型挑流鼻坎体型设计提供了技术支撑。
关键词(KeyWords): 水工结构;复合型鼻坎;落水范围;BP神经网络;反演研究
基金项目(Foundation): 国家杰出青年科学基金项目(51625901)
作者(Author): 张晓萍,张建民
DOI: 10.13928/j.cnki.wrahe.2022.04.012
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