峡江库区土工检测数据分析及堤防渗流的数值模拟研究

发布时间：2018-08-11 11:06

【摘要】：渗流问题和渗透变形一直是堤防出现险情的重要原因。探讨堤防渗流分析和渗透破坏类型的研究现状及发展过程，对于合理的分析和评价堤防的安全性能、采取合理的防渗措施具有重要参考价值和实践意义。运用智能算法对土工试验中的击实、颗分、比重、液塑限试验参数进行预测分析，将最大干密度、比重、颗分、界限含水率作为模型输入，渗透系数作为模型预测输出，将模型输出值与渗透试验得出的试验值进行对比分析，以验证智能算法对于数据预测中的可行性，可作为渗透系数试验的参考值，也可作为现场无渗透系数试验条件下，工程所需渗透系数的近似值。本文结合峡江库区某防护工程，利用有限元软件分析该防护工程堤防的渗流状况，从而为该防护工程采取的防渗措施提供依据。本文的主要内容如下： 1．介绍峡江库区工程土工试验中的击实、颗分、比重、液塑限、渗透系数等试验方法，通过该土工试验得出的试验参数，作为智能算法预测分析模型中的输入与输出值。 2．针对峡江库区工程中的土工检测数据较少，选取智能算法中专门解决小样本问题的SVM算法，就该土工检测数据进行分析，并与FOAGRNN和BP算法进行对比，以验证SVM算法对于小样本训练的高精度的特性。 3．结合峡江某堤防工程的设计资料，利用有限元软件对该堤防工程进行建模分析，，得出该堤防的渗流状况，根据渗流分析结果，采用相应的防渗措施，并介绍了该堤防工程防渗措施的施工工艺流程以及施工的主要方法。
[Abstract]:Seepage problem and seepage deformation are always the important reasons for the dangerous situation of embankment. This paper discusses the present situation and development process of seepage analysis and seepage failure type of levees, which has important reference value and practical significance for reasonable analysis and evaluation of levee safety performance and taking reasonable seepage prevention measures. The parameters of compaction, particle fraction, specific gravity and liquid-plastic limit test in geotechnical test are predicted and analyzed by intelligent algorithm. The maximum dry density, specific gravity, particle fraction and limit moisture content are taken as the input of the model, and the permeability coefficient is taken as the predicted output of the model. In order to verify the feasibility of the intelligent algorithm in data prediction, the model output value is compared with the experimental value obtained from the permeation test, which can be used as the reference value of the permeability coefficient test, and it can also be used as the field non-permeability coefficient test condition. Approximate value of the required permeability coefficient for engineering. Combined with a protection project in Xijiang reservoir area, the seepage condition of the levee of the protection project is analyzed by using finite element software, thus providing the basis for the seepage prevention measures taken by the protection project. The main contents of this paper are as follows: 1. The test methods of compaction, particle fraction, specific gravity, liquid-plastic limit, permeability coefficient and so on in the geotechnical test of Xijiang reservoir area are introduced, and the test parameters obtained from the geotechnical test are introduced. As the input and output value of intelligent algorithm prediction and analysis model. 2. Aiming at the lack of geotechnical detection data in Xiajiang reservoir area project, the SVM algorithm is selected to solve small sample problem in intelligent algorithm. The geotechnical testing data are analyzed and compared with the FOAGRNN and BP algorithms to verify the high accuracy characteristics of the SVM algorithm for small sample training. 3. Combining with the design data of a dike project in Xiajiang River, Using finite element software to model and analyze the levee project, the seepage condition of the levee is obtained. According to the seepage analysis result, the corresponding seepage prevention measures are adopted. This paper also introduces the construction process and main methods of seepage prevention measures of the levee project.
【学位授予单位】：南昌大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TV223.4;TV871

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