| 基于认知聚类分区方法的边坡可靠度分析 |
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| 引用本文： | 唐小松,李典庆,周创兵.基于认知聚类分区方法的边坡可靠度分析[J].岩土力学,2011,32(2):571-578. |
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| 作者姓名： | 唐小松 李典庆 周创兵 |
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| 作者单位： | 武汉大学水资源与水电工程科学国家重点实验室,武汉,430072;武汉大学水工岩石力学教育部重点实验室,武汉,430072 |
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| 基金项目： | 国家自然科学基金重点项目，教育部新世纪优秀人才计划，湖北省青年杰出人才基金 |
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| 摘 要： | 提出了边坡可靠度分析的一种新的全局优化方法——认知聚类分区方法。该方法主要包括5个步骤:分区、随机抽样、计算极径L、回代、计算可靠指标及验算点。给出了相应的计算流程图,并编写了基于C语言的计算程序KCPREL。最后,以岩质边坡稳定可靠度问题为例证明了所提方法的有效性。结果表明,认知聚类分区方法能同时计算出可靠指标和验算点,并能获得全局最优解。该方法的计算精度和蒙特卡洛模拟方法相当,计算效率远远高于传统的蒙特卡洛模拟方法。此外,该方法在分析含有复杂的隐式及非线性功能函数的边坡稳定可靠度问题方面体现出明显的优越性。等步长认知聚类分区方法能全面且均匀地搜索角度,从而得到更准确的验算点。为了保证足够的计算精度及减小计算量,建议步长取10o以内。
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| 关 键 词： | 边坡 可靠度 认知聚类分区方法 验算点 等步长 |
| 收稿时间： | 2010-03-26 |
Knowledge-based clustered partitioning method for reliability analysis of slope stability |
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| TANG Xiao-song,LI Dian-qing,ZHOU Chuang-bing.Knowledge-based clustered partitioning method for reliability analysis of slope stability[J].Rock and Soil Mechanics,2011,32(2):571-578. |
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| Authors: | TANG Xiao-song LI Dian-qing ZHOU Chuang-bing |
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| Institution: | 1. State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China; 2. Key Laboratory of Rock Mechanics in Hydraulic Structural Engineering of Education Ministry, Wuhan University, Wuhan 430072, China |
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| Abstract: | A new global optimization reliability method, knowledge-based clustered partitioning (KCP) method, is proposed. The proposed method includes five steps, namely, partitioning, random sampling, calculation of the polar radius, backtracking, and calculations of reliability index and design points. A flowchart for the proposed method is presented. Moreover, a C-language based computer program is developed to carry out the reliability computations. Two examples of reliability analysis for rock slope stability with plane failure are presented to demonstrate the validity and capability of the proposed method. The results indicate that the proposed method can obtain the reliability index and the design points simultaneously. Furthermore, the global optimization solutions can be obtained. The proposed method can ensure sufficient accuracy for reliability computations; and its efficiency is significantly higher than the traditional Monte Carlo simulations, which can be considered as a potential method for reliability analysis of slope stability, especially for slope stability involving implicit and nonlinear performance function. The proposed KCP method with equal-step-length can search the angles systematically, which results in the accurate design points. It is recommended that angle below ten degree should be adopted to ensure sufficient accuracy and reduce the computational effort as low as possible. |
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| Keywords: | slope reliability knowledge-based clustered partitioning (KCP) method design point equal-step-length |
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