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锦屏水电站地下厂房初始地应力场反演分析 被引量:4

Regression Analysis of Initial Geostress Field of Underground Workshop of Jinping Hydropower Station
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摘要 结合锦屏二级水电站复杂的地质条件,运用有限元法和BP人工神经网络对研究区的初始地应力场进行了反演分析。结果表明:主应力的变化规律为从上到下逐渐增大,主应力的分布随埋深的增加而增大,主应力等值线在浅层区域受地形起伏影响很大;在靠近地表及河谷底部,等值线分布较密集,应力变化梯度较大,出现应力集中现象;地下厂房区域表层及浅层主应力倾角与山体坡角基本相同,在深部区域,最大主应力倾角随深度的增加逐渐增大;数值模拟反演计算得到的初始应力场分布与研究区的地形地貌关系密切,而岩性对地应力场的分布影响较小;BP人工神经网络反演值与实测值较接近,反演精度可以满足工程实际需要。 Combined with complex geological conditions of Jinping Hydropower Station,the finite element method and BP artificial neural network had been used for regression analysis of initial geostress field in research area. The results show that the principal stress increases gradually from top to bottom,the distribution of principal stress increases with the increasing buried depth,the main stress contour is greatly affected by topography in the shallow area;close to the surface and the bottom of the valley,the distribution of stress contour is more intensive,the change gradient of stress is greater and stress concentration phenomenon appeared;the surface and shallow principal stress dip angle is basically the same as the mountain slope angle in the underground workshop area,in the deep region,the maximum principal stress inclination increased with the increasing of depth;the initial stress field distribution calculated by numerical simulation is closely related to the topography in the study area,while the lithology has smaller influence on the distribution of stress field;stress measured value is closer to the regression value of BP artificial neural network and regres-sion accuracy can meet the actual needs of the project.
出处 《人民黄河》 CAS 北大核心 2014年第5期116-119,共4页 Yellow River
基金 武汉市科技局社会发展科技攻关计划项目(201160823268)
关键词 初始地应力 回归分析 人工神经网络 锦屏水电站 initial geostress regression analysis artificial neural network Jinping Hydropower Station
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