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隧洞支洞群施工及运行期围岩及衬砌结构应力变形数值分析
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作者 赵冬莲 王志刚 《水利水电技术》 CSCD 北大核心 2010年第11期45-47,66,共4页
采用弹塑性D-P模型对缅甸太平江水电站引水发电洞支洞群稳定性进行了分析,探讨了在开挖及运行工况下围岩稳定性、衬砌混凝土结构的应力变形分布规律以及不同开挖顺序对围岩应力变形影响。结果表明:在施工及运行工况下,围岩稳定,运行工... 采用弹塑性D-P模型对缅甸太平江水电站引水发电洞支洞群稳定性进行了分析,探讨了在开挖及运行工况下围岩稳定性、衬砌混凝土结构的应力变形分布规律以及不同开挖顺序对围岩应力变形影响。结果表明:在施工及运行工况下,围岩稳定,运行工况下现有衬砌结构能够满足要求,不同开挖方案对围岩应力变形影响不大。分析成果为该工程设计及施工提供参考。 展开更多
关键词 支洞群 围岩 衬砌 引水隧 结构应力 变形分析 太平江水电站 缅甸
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RandWPSO-LSSVM optimization feedback method for large underground cavern and its engineering applications 被引量:2
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作者 聂卫平 徐卫亚 刘兴宁 《Journal of Central South University》 SCIE EI CAS 2012年第8期2354-2364,共11页
According to the characteristics of large underground caverns, by using the safety factor of surrounding rock mass point as the control standard of cavern stability, RandWPSO-LSSVM optimization feedback method and flo... According to the characteristics of large underground caverns, by using the safety factor of surrounding rock mass point as the control standard of cavern stability, RandWPSO-LSSVM optimization feedback method and flow process of large underground cavern anchor parameters were established. By applying the optimization feedback method to actual project, the best anchor parameters of large surge shaft five-tunnel area underground cavern of the Nuozhadu hydropower station were obtained through optimization. The results show that the predicted effect of LSSVM prediction model obtained through RandWPSO optimization is good, reasonable and reliable. Combination of the best anchor parameters obtained is 114131312, that is, the locked anchor bar spacing is 1 m x 1 m, pre-stress is 100 kN, elevation 580.45-586.50 m section anchor bar diameter is 36.00 mm, length is 4.50 m, spacing is 1.5 m × 2.5 m; anchor bar diameter at the five-tunnel area side wall is 25.00 mm, length is 7.50 m, spacing is 1 m× 1.5 m, and the shotcrete thickness is 0.15 m. The feedback analyses show that the optimization feedback method of large underground cavern anchor parameters is reasonable and reliable, which has important guiding significance for ensuring the stability of large underground caverns and for saving project investment. 展开更多
关键词 random weight particle swarm optimization least squares support vector machine large undergrotmd cavern anchor oarameters optimization feedback rock-ooint safety factor
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