摘要
针对碾压混凝土重力坝的渗漏问题,以某实际的高碾压混凝土重力坝防渗结构为研究对象,实现了基于伽辽金法的渗控结构渗流数值模拟分析,以"变态混凝土-二级配碾压混凝土"为主要防渗材料,对采用不同厚度的上游防渗材料、不同布置方式的碾压混凝土坝渗控结构进行了计算和对比分析。结果表明:不同上游防渗材料的厚度变化对坝体渗流量影响不同,二级配碾压混凝土的厚度对坝体渗流量的影响是近似线性的,而变态混凝土的厚度对其影响则是非线性的;渗控结构的布置对坝体渗流场的宏观特性起决定性作用,排水孔幕能降低约80%的坝体渗流量和约60%的渗水溢出高程;坝体渗控结构的布置方式对坝基渗流无影响。在规范许可和条件允许的前提下,建议采用厚度为5m以上的二级配碾压混凝土厚度、不超过0.8m的上游变态混凝土和0.5m左右的下游变态混凝土,并在阻渗结构后加密布置排水孔幕以增大坝体局部垂向渗透性,这样既能保证施工质量,也能取得不错的防渗效果。
Aiming at the seepage problem of Roller Compacted Concrete(RCC) gravity dams, a solution to simulate the seepage field and optimize the impervious structures is realized based on the Galerkin method for an actual project. Grout enriched vibrated RCC(GEVR) and two-graded RCC are used as the main anti-seepage materials. Considering various thicknesses of impervious materials and layouts of drainage systems, different structure schemes are designed. Some critical parameters are computed and contrasted for different schemes, such as seepage flow and free seepage surface. The results show that thickness changes of different impervious materials have different effects on seepage field. Thickness of two-graded RCC has linear relationship with seepage flow while GEVR shows up as nonlinear one. Layouts of seepage control systems are important to dam seepage behaviors. A proper drainage system can reduce seepage flow by 80% as well as drop free seepage surface by 60%. It is suggested that the two-graded RCC of non-less-than-5.0m thick with GEVR of non-lower-than-0.8m thick could be a proper candidate for the upstream impervious layer. A GEVR of 0.5m downstream is recommended. A set of complete drainage systems after impervious structures should be used in dam structures and foundation. The optimized scheme could offer better anti-seepage effect under good construction quality.
出处
《应用力学学报》
CAS
CSCD
北大核心
2016年第6期1064-1070,1123,共7页
Chinese Journal of Applied Mechanics
基金
国家重点基础研究发展(973)计划(2013CB035903)
国家自然科学基金(51321065
51209159)
关键词
碾压混凝土重力坝
防渗层
渗控结构
有限元法
优化
RCC gravity dam
impervious structures
layouts of drainages systems
FEM
optimization