A comprehensive evaluation model for rockburst risk prediction based on analytic hierarchy process and probabilistic optimization
文献类型：会议论文
| 作者 | Feng, G. L.; Feng, X. T.; Chen, B. R.; Xiao, Y. X.; Ming, H. J. |
| 出版日期 | 2012 |
| 会议日期 | OCT 14-16, 2011 |
| 会议地点 | Beijing, PEOPLES R CHINA |
| 页码 | 869-874 |
| 英文摘要 | The rockburst problems cause serious casualties and economic loss and become a major disaster in the field of industrial safety. According to the shortcomings both of the single assessment index and the comprehensive evaluation methods for rockburst prediction at present, and considering the randomness and relative accuracy of basic factors in geotechnical engineering, a comprehensive evaluation model for rockburst risk prediction on the base of analytic hierarchy process and probabilistic optimization is put forward. The model adopts multiclass indexes and a normalized thinking, coupled with the combination of qualitative and quantitative analysis. It can predict not only the intensity grade but also the occurring probability of rockburst. Moreover, a method with extended application including its condition is presented to make the model more applicable. The model is applied to deep-buried tunnel section of auxiliary tunnels of Jinping II hydropower station. The result shows that this model is more than available, but also comprehensive, simple and convenient. |
| 源文献作者 | Cai, M |
| 会议录 | ROCK MECHANICS: ACHIEVEMENTS AND AMBITIONS
 |
| 会议录出版者 | CRC PRESS-TAYLOR & FRANCIS GROUP |
| 会议录出版地 | BOCA RATON |
| 语种 | 英语 |
| WOS研究方向 | Engineering |
| WOS记录号 | WOS:000347395400160 |
| 源URL | [http://119.78.100.198/handle/2S6PX9GI/4662]  |
| 专题 | 岩土力学所知识全产出_会议论文 国家重点实验室知识产出_会议论文 |
| 作者单位 | Chinese Acad Sci, Inst Rock & Soil Mech, State Key Lab Geomech & Geotech Engn |
| 推荐引用方式 GB/T 7714 | Feng, G. L.,Feng, X. T.,Chen, B. R.,et al. A comprehensive evaluation model for rockburst risk prediction based on analytic hierarchy process and probabilistic optimization[C]. 见:. Beijing, PEOPLES R CHINA. OCT 14-16, 2011. |
入库方式： OAI收割
来源：武汉岩土力学研究所
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