坡面径流对斜坡散粒体稳定性影响的试验分析

Experimental Analysis of the Effect of Slope Runoff on Stability of Slope Granular Particles

坡面径流是松散介质斜坡上颗粒发生搬运滚动的水动力条件。为研究坡面径流对斜坡散粒体颗粒稳定性的影响,开展室内水槽冲刷试验。试验设置3种粒径和4种坡度,通过高速摄像仪捕获斜坡散粒体受水流冲刷起动过程,获得不同条件下颗粒冲刷起动的临界径流水深hcr。试验结果表明:在同一粒径条件下,起动水深hcr随着斜坡坡度的增大而减小;在坡度为20°、22°时,起动水深hcr随着粒径的增大,出现先增大后减小的情况,而在坡度为24°、26°时,起动水深hcr随着粒径的增大而增大,分析原因可能是当粒径增大引起坡体渗透性的改变是影响颗粒稳定性的主控因素时,颗粒更容易受水流的渗透作用而发生运移。为合理解释试验现象,建立斜坡径流-渗流耦合模型来分析坡面径流条件下颗粒的稳定性变化情况,通过将水流的流速特征与颗粒的受力起动特性结合起来,给出临界水深hcr的理论表达式,其主要受颗粒粒径、颗粒比重、孔隙率、坡体渗透率和斜坡坡度等因素共同控制。通过将试验结果与计算结果进一步对比发现,在同一粒径区间内,临界水深hcr的实测值与理论值均随坡度的增大而减小,而理论值与实测值之间的相对误差随坡度的增大而增大,但其均控制在35%以内,并对产生该误差的原因进行了分析。为修正实测值与计算值之间的误差,应用MATLAB的神经网络模块对数据进行拟合,建立含两个神经网络结构的临界水深hcr修正公式,精度较高。

The slope runoff is a hydrodynamic condition in which particles are transported and rolled on a loose medium slope.In order to study the effect of slope runoff on the stability of slope granular particles,an indoor flume flush test was carried out.Three types of particle sizes and four kinds of slope angles were set in the experiment.The high-speed camera was used to record the slope granular particles being washed by the water flow to obtain the critical runoff depth hcr of the particle scouring under different conditions.The experimental results showed that the hcr decreased with the increase of slope angle under the same particle size,and when the slope angle was 20°and 22°,the hcr increased first and then decreased.However,when the slope angle was 24°and 26°,the hcr increased with the increase of the particle size.The reason for the phenomenon is that when the change in the permeability of the slope caused by the increase of the particle size is the main controlling factor affecting the stability of the particles,the particles are more likely to be migrated by the infiltration of water.In order to explain the experimental phenomenon,a mathematical model coupling slope runoff and seepage was established to analyze the stability of particles under runoff conditions.The theoretical expression of the hcr was given by combining the flow velocity characteristics of the water flow with the force-starting characteristics of the particles,indicating that hcr is controlled by particle size,particle specific gravity,porosity,slope permeability,slop angle and so on.By comparing the experimental data with the calculated results,it was found that the measured value and the theoretical value of the hcr decreases,but the relative errors which are all controlled within 35%between them increases with the increase of the slope angle in the same particle size interval.In order to correct the error between the measured value and the calculated value,the neural network module of MATLAB was used to fit the data,and the critical water depth hcr correction equation with two neural network structures was established with high precision.