含沙量对U型渠道水流流速横向分布律的影响

探索含沙量变化对U型渠道水流流速沿横向分布的影响,进而从理论上完善挟沙水流流速分布规律,对渠道水沙运动规律的研究有重要意义。引入指数流速分布公式,通过U型渠道水槽试验,测定水流中含沙量为1.12～500kg/m3时,指数公式中流速横向分布系数的变化规律,说明U型渠道挟沙水流流速沿横向分布遵循指数流速分布规律。在含沙量s<300kg/m3下,流速横向分布系数随着含沙量的增大呈线性缓慢增大,当含沙量s≥300kg/m3时,流速横向分布系数由缓慢增大变为急剧增大,说明水流流型已发生了变化;含沙量s≥50kg/m3时,U型渠道的中心出现了核心区,核心区随着含沙量的增大而变宽。     

液电式馈能减振器外特性仿真与试验

为了回收由路面不平引起的车辆振动能量,设计了一种车用液电式馈能减振器,并针对其外特性进行了研究。根据液电式馈能减振器组成与原理,建立了相应的数学模型,模拟试验工况计算得到了示功特性及速度特性曲线;搭建了液电式馈能减振器试验台架并进行台架试验以验证理论模型的合理性;最后,基于所建立的液电馈能式减振器数学模型分析了蓄能器充气压力、蓄能器充气体积、液压马达排量、单向阀节流口面积与液压管路内径对外特性的影响。结果表明:提高高压蓄能器充气压力可以增大系统阻尼力;增大高压蓄能器充气体积、单向阀节流口面积、液压管路内径以及液压马达排量会引起系统阻尼力减小,其中液压马达排量只对伸张行程阻尼力有影响,压缩行程阻尼力不受其影响。     

鱼游泳能力对体长的响应及其在鱼道设计中的应用

为了探讨鱼类体长对游泳能力的影响并为鱼道水流的设计提供参考,该研究在封闭水槽中使用"递增流速法"测试了海南省某水利枢纽鱼道目标对象的游泳能力,并用Origin软件进行了数据统计分析,得到了试验鱼感应流速、临界游泳速度和爆发游泳速度的直线回归方程和Kaplan-Meier曲线.结果表明:1)随着试验鱼体长增大,相对感应流...     

不同频率下的泥石流体特征数值计算方法研究——以大寨沟流域为例

在泥石流定量研究中,泥石流流量、流速、泥石流规模是泥石流体最重要的特征值.能比较准确的确定泥石流这些特征数值既是泥石流计算中的关键问题,也是泥石流防治工程设计研究中的重要因素.利用雨洪法,首先比较一种或两种水文学的计算方法,择优来计算暴雨与洪水特征数值,然后利用暴雨与洪水特征数值来推算泥石流体各种特征数值.比如用暴雨洪峰流量以及配方法来计算泥石流流量,利用洪水总量来推算泥石流规模.     

坡度对降雨径流挟沙能力影响的模拟试验

高陡边坡降雨径流侵蚀输移能力是一个重要的科学问题。通过室内模拟降雨试验研究相同雨强不同坡度和坡长条件下的降雨径流侵蚀输移规律。结果表明：(1)试验条件下,水深与水力坡度的1/3次方呈负相关,与坡长的3/5次方呈正相关,流速与水力坡度和水深呈幂函数增加;(2)相同雨强裸坡条件下,径流含沙量与水力坡度的1/2次方呈正相关,与坡长的4/5次方呈正相关。水流挟沙能力约与水力坡度的1/2次方呈正相关。(3)降雨径流的水流紊动扩散作用与重力作用的比值较明渠水流偏大,表明雨滴打击的紊动作用较明显,给出挟沙能力公式。与常用的河流泥沙挟沙能力公式比较,系数偏大,指数偏小。研究成果对深入分析降雨径流侵蚀输移的机制具有重要意义。     

用于梯形渠道的仿翼形便携式量水槽水力性能

机翼形量水设施水力条件优、量水精度高,但翼形曲线的复杂性制约其推广,为此,该研究基于结构简单的仿翼形便携式量水槽,探究其在末级梯形渠道的适用性。模型试验设计5组收缩比、7组流量进行水力性能试验,在此基础上,基于FLOW-3D软件对比分析仿翼形与机翼形量水槽水力性能的差异,深入研究不同收缩比对仿翼形量水槽水力性能的影响。研究结果表明：数值模拟与试验结果的水深数据吻合,误差小于4.91%,数值模拟的方法准确可靠;简化后未改变机翼形过流顺畅、雍水高度小等特点;所有工况上游佛汝德数均小于0.5,雍水高度小于7.6 cm,满足测流精度和渠道安全的要求,收缩比在0.60~0.64范围时,量水槽水力性能最优;基于能量方程及临界流原理建立的流量公式精度较高,平均测流误差为2.75%。该研究表明仿翼形保持了原机翼形良好的水力性能,测流精度高且曲线形式简单,便于推广,对于促进灌区末级梯形渠道便携式量水槽的推广具有实用价值。     

Soil enzyme activities during the 2011 Texas record drought/heat wave and implications to biogeochemical cycling and organic matter dynamics

Extreme droughts and heat waves due to climate change may have permanent consequences on soil quality and functioning in agroecosystems. During November 2010 to August 2011, the Southern High Plains (SHP) region of Texas, U.S., a large cotton producing area, received only 39.6 mm of precipitation (vs. the historical avg. of 373 mm) and experienced the hottest summer since record keeping began in 1911. Several enzyme activities (EAs) important in biogeochemical cycling were evaluated in two soils (a loam and a sandy loam at 0–10 cm) with a management history of monoculture (continuous cotton) or rotation (cotton and sorghum or millet). Samplings occurred under the most extreme drought and heat conditions (July 2011), after precipitation resulted in a reduction in a drought severity index (March 2012), and 12 months after the initial sampling (July 2012; loam only). Eight out of ten EAs, were significantly higher in July 2011 compared to March 2012 for some combinations of soil type and management history. Among these eight EAs, enzymes key to C (β-glucosidase, β-glucosaminidase) and P cycling (phosphodiesterase, acid and alkaline phosphatases) were significantly higher (19–79%) in July 2011 than in March 2012 for both management histories regardless of the soil type (P > 0.05). When comparing all sampling times, the activities of alkaline phosphatase, aspartase and urease (rotation only) showed this trend: July 2011 > March 2012 > July 2012. Activities of phosphodiesterase, acid phosphatase, α-galactosidase, β-glucosidase and β-glucosaminidase were higher in July 2011 than July 2012 in at least one of the two management histories. Total C was reduced significantly from July 2011 to March 2012 in the rotation for both soils. Only the activities of arylsulfatase (avg. 36%) and asparaginase showed an increase from July 2011 to March 2012 for both soil types, which may indicate they have a different origin/location than the other enzymes. EAs continued to be a fingerprint of the soil management history (i.e., higher EAs in the rotation than in monoculture) during the drought/heat wave. This study provided some of the first evidence of the adverse effects of a natural, extreme drought and heat wave on soil quality in agroecosystems as indicated by EAs involved in biogeochemical cycling.