| 基于广义子集模拟的土坡系统可靠度分析 |
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| 引用本文： | 杨智勇,李典庆,曹子君,唐小松. 基于广义子集模拟的土坡系统可靠度分析[J]. 岩土力学, 2018, 39(3): 957-966. DOI: 10.16285/j.rsm.2016.0780 |
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| 作者姓名： | 杨智勇 李典庆 曹子君 唐小松 |
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| 作者单位： | 1. 武汉大学 水资源与水电工程科学国家重点实验室，湖北 武汉 430072；2. 武汉大学 水利水电学院，湖北 武汉 430072 |
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| 基金项目： | 国家自然科学基金项目（No.51329901，No.51579190，No.51679174，No.51528901）；湖北省自然科学基金创新群体项目（No.2014CFA001） |
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| 摘 要： | 如何有效地评价边坡的系统可靠度并识别出对边坡稳定性具有重要影响的关键滑面一直是边坡稳定性分析的关键问题。提出了基于广义子集模拟的边坡系统可靠度分析方法及代表性滑面识别方法，并推导了基于广义子集模拟的边坡系统可靠度计算公式及边坡中滑面对边坡系统失效的相对贡献量化公式。基于广义子集模拟计算结果，采用概率网络评价方法识别边坡代表性滑面。以一个双层黏性土坡和芝加哥国会切坡算例验证了所提方法的有效性。结果表明：提出的基于广义子集模拟的边坡系统可靠度分析方法可有效地估计边坡系统及其单一滑面的失效概率，对于具有低失效概率水平边坡可靠度的求解，其计算效率明显优于传统蒙特卡洛模拟方法。此外，对于单个失效模式而言，广义子集模拟与子集模拟计算效率相当。对于多个失效模式的失效概率计算问题，广义子集模拟不需要重复对每个失效模式失效概率进行计算，计算效率明显优于子集模拟。提出的代表性滑面选择方法是在系统失效概率及单滑面失效概率的高效计算基础上实现的，代表性滑动面能够较好地代表边坡系统失效，从而有效地降低了边坡系统失效概率对代表性滑面数目及代表性滑面失效概率估计准确性的依赖性。
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| 关 键 词： | 边坡 广义子集模拟 概率网络评价 系统可靠度 潜在滑动面 代表性滑面 |
| 收稿时间： | 2016-04-18 |
System reliability of soil slope using generalized subset simulation |
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| YANG Zhi-yong,LI Dian-qing,CAO Zi-jun,TANG Xiao-song. System reliability of soil slope using generalized subset simulation[J]. Rock and Soil Mechanics, 2018, 39(3): 957-966. DOI: 10.16285/j.rsm.2016.0780 |
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| Authors: | YANG Zhi-yong LI Dian-qing CAO Zi-jun TANG Xiao-song |
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| Affiliation: | 1. State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, Hubei 430072, China; 2. School of Water Resources and Hydropower Engineering, Wuhan University, Wuhan, Hubei 430072, China |
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| Abstract: | How to effectively assess the system reliability of slope containing unlimited number of potential slip surfaces and how to accurately identify key slip surfaces significantly contributing to slope failure are critical questions in slope engineering. To address these questions, this study proposed an approach to assess slope system reliability and to identify the representative slip surfaces based on generalized subset simulation (GSS). The equations for the evaluation of slope and quantification of the relative contribution of individual slip surface to slope are derived in this study. Using the reliability analysis results of GSS, the independent representative slip surfaces (RSSs) are identified from possible slip surfaces using probabilistic network evaluation technique (PNET). Finally, the proposed approach is verified using examples of a two-layered cohesive slope and a case of Congress Street Cut in Chicago. Results show that the proposed approach provides proper estimates of failure probabilities of individual slip surfaces and the slope system simultaneously by a single GSS run. This can avoid repeated simulations for each failure mode. The proposed approach is more efficiency than Monte Carlo simulation (MCS) especially for failure modes at low probability level and simultaneously overcome the limitations of subset simulation (SS). The RSSs are selected using PNET after obtaining the failure probabilities of the slope system and its corresponding potential slip surfaces. The slope system can be represented effectively by the RSSs identified in this study. The proposed approach effectively avoids the dependence of the accuracy of system failure probability on the number of RSS and the accuracy of failure probability of RSS. |
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| Keywords: | slope generalized subset simulation probabilistic network evaluation technique system reliability potential slip surfaces representative slip surfaces |
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