河床砂卵石介质渗透特性的试验研究及应用

发布时间：2018-04-24 19:03

本文选题：砂卵石介质 + 渗透系数　；参考：《太原理工大学》2013年博士论文

【摘要】：黄河取水含沙量高是影响区域地表水资源开发利用的一个难题,而采用人工滤床配合渗渠进行取水,可通过人为调节同时满足取水中质和量两方面的需求,是一种很有推广和应用前景的取水手段,在该技术中如何合理地确定滤床的过滤体型式和结构是取水成败的关键。文章试图从柳林县黄河滩地原状砂卵石介质的室内大尺度物理模型试验出发,通过分析不同形状和尺度漂石对砂卵石介质渗透能力的影响,构建漂石存在条件下砂卵石介质的渗透模型；然后基于不同级配砂卵石介质的渗透系数试验,从特征粒径指标的角度分析了影响渗透系数的因素及规律,建立了用特征粒径参数预测渗透系数的线性和非线性预报模型；最后对不同砂卵石组合型式对高含沙水的过滤效果进行试验分析,提出了黄河滩地人工滤床推荐的过滤层和支撑层结构,其研究成果可以为山西省乃至全国傍河取高含沙水的滤床工程建设提供技术参考。论文研究取得的主要成果包括： (1)漂石存在对砂卵石介质渗流特性影响的临界点为0.177,当渗流水力梯度大于该值后,影响效果越来越显著,反之则基本无影响；漂石的形状、截面积和体积均会对砂卵石介质的渗透系数产生不同的影响,过流界面越粗糙,或截面积越大,或体积越大时,产生的渗流阻力越大,渗流速度就越小;而在漂石存在条件下砂卵石介质的渗流模型可用二次多项式来描述。 (2)单一粒级组的砂卵石介质,随着粒径的减小其渗透系数逐渐降低,而它受压力水头的影响也越来越小；不同级配组合的砂卵石介质,其渗透系数的变化跟介质的特征粒径参数有关,即有效粒径、限制粒径、不均匀系数和曲率系数,而只有在其他参数给定范围的情况下,才能确定渗透系数随某一个参数的变化规律；最后,通过试验研究筛选出渗透性能最优的砂卵石颗粒级配和结构。 (3)通过对大量不同级配砂卵石介质渗透系数的试验数据进行研究,发现可以用特征粒径参数对渗透系数进行预测预报；然后构建了以限制粒径、有效粒径、不均匀系数和曲率系数为自变量的多元线性和非线性回归模型,模型预测值与实测值平均相对误差分别为12.4%和26.2%,说明多元线性回归模型的预测精度较高。 (4)在砂卵石介质人工滤床过滤体的技术参数试验中发现,采用0.25～1.Omm细颗粒介质与土工布复合覆盖层作为主过滤层、等粒径介质分层填筑作为支撑层,其水质和水量均能满足取水要求,且又便于淤泥的机械清除和清洗,阻泥、保渗、清洗效果都很好,是一种值得推荐的过滤型式。论文的研究中在漂石对砂卵石介质渗流影响分析、利用特征粒径参数预报渗透系数及黄河滩地人工滤床的过滤体型式等方面有所创新。研究提出的人工滤床过滤取水方式可以更便捷的利用黄河高含沙水,是缓解区域水资源供需矛盾的一种新的有效途径。而研究的主要成果都在试验室内取得的,其在工程中的实用性及模型预测的精度等方面需在以后的实践中进一步完善和提高。
[Abstract]:The high sediment concentration in the Yellow River water intake is a difficult problem to influence the development and utilization of surface water resources in the region, and the use of artificial filter bed and Seepage Canal for water intake can meet the demand of two aspects of the quality and quantity of water in the water intake by artificial adjustment. It is a kind of water taking means which has a good prospect of popularization and application. In this technology, how to determine the filter bed reasonably Filter type and structure are the key to the success of water intake.
In this paper, the effect of different shapes and scale blebbles on the permeability of sand and gravel medium is analyzed from the large scale physical model test of the original sand and gravel medium in the Yellow River beach, Liulin County. The permeability model of gravel medium under the existence of blebstone is constructed, and the permeability coefficient test based on different graded gravel medium is then based on the analysis. From the angle of characteristic particle size, the factors and laws affecting the permeability coefficient are analyzed. A linear and nonlinear prediction model is established to predict the permeability coefficient with the characteristic particle size parameters. Finally, the filtration effect of different sand gravel combination types on the high sediment concentration water is tested and analyzed, and the filter layer recommended by artificial filter bed in the Yellow River beach land is proposed. The research results can provide technical reference for the construction of filter bed project for high sand water in Shanxi and even the whole country.
The main achievements of this research include:
(1) the critical point of the influence of blebstone on the percolation characteristics of sand gravel medium is 0.177. When the seepage hydraulic gradient is greater than that, the effect is more and more significant, and conversely, there is no influence. The shape, area and volume of the blebstone will have different influence on the permeability coefficient of the gravel medium, the more rough the overflow interface, the larger the cross section area. When the larger the volume is, the larger the seepage resistance is, the smaller the seepage velocity is, and the seepage model of the gravel medium can be described by the two polynomial.
(2) the sand gravel medium in the single particle group decreases with the decrease of the particle size, and it is less and less affected by the pressure water head; the permeability coefficient varies with the characteristic particle size parameters of the medium, that is, the effective particle size, the grain size, the inhomogeneous coefficient and the curvature coefficient, but only the effective particle size, the inhomogeneous coefficient and the curvature coefficient. In the case of a given range of other parameters, the variation of the permeability coefficient with a certain parameter can be determined. Finally, the particle size distribution and structure of the sand boulder with the best permeability are selected through the experimental study.
(3) through the study of the experimental data on the permeability coefficient of a large number of different graded gravel media, it is found that the permeability coefficient can be predicted and predicted with the characteristic particle size parameters, and then a multivariate linear and nonlinear regression model is constructed to restrict the particle size, effective particle size, nonuniform coefficient and curvature coefficient as independent variables. The average relative error of measured values is 12.4% and 26.2% respectively, indicating that the prediction accuracy of multivariate linear regression model is high.
(4) in the technical parameters test of sand gravel medium filter bed filter body, it is found that the composite covering layer of 0.25 ~ 1.Omm fine particle medium and geotextile is used as the main filter layer, and the water quality and water can meet the requirement of water intake, and the water quality and water can meet the requirements of water intake, and it also facilitates the cleaning and cleaning of silt, mud resistance, infiltration and cleaning. The washing effect is very good. It is a recommended filter type.
In the study of this paper, the influence of blebstone on the seepage of sand and gravel is analyzed, the characteristic particle size parameters are used to predict the permeability coefficient and the filter type of the artificial filter bed in the Yellow River beach. The proposed method of filtering the water from the artificial filter bed can be more convenient to use the high sediment water in the Yellow River to alleviate the contradiction between the supply and demand of water resources in the region. The main achievements of the study are obtained in the laboratory, and the practicality of the project and the accuracy of the model prediction need to be further improved and improved in the future practice.

【学位授予单位】：太原理工大学
【学位级别】：博士
【学位授予年份】：2013
【分类号】：TV139.1;TU991.1

【参考文献】