【作者】 杨丽红；

【导师】 程五一；

【作者基本信息】 中国地质大学（北京） ， 安全技术及工程， 2009， 硕士

【摘要】 除天津、上海没有尾矿库外,我国共有各类尾矿库约8541座。值得注意的是,在我国诸多尾矿库中,目前处于正常运行的不足70%,有的行业44%的尾矿库处于险、病、超期服务状态,情况非常不利。此外,绝大多数尾矿库下游为生活区、工矿企业或重要城镇等,一旦发生溃坝,将会造成重大环境污染、财产损失和人员伤亡。统计数据表明,我国尾矿库的正常运行比例偏低,安全形势相当严峻。因此,开展尾矿坝溃坝机理和安全性评价等方面的研究,提出能够反映尾矿坝溃坝危险性的指标体系和安全评价模型,对提高尾矿库的本质安全状态和安全管理水平,减少和控制尾矿库运行中的危险、有害因素,降低尾矿库生产安全风险和预防事故发生,保护企业及下游居民的财产安全等方面都具有重要意义。目前,在尾矿库安全方面,国内研究的主要内容仍然是变形与稳定的问题。尽管众多学者均认为尾矿坝溃坝是由多因素造成的,然而已有的研究成果大都集中在单个因素对尾矿坝安全的影响分析,缺乏对尾矿坝溃坝的致灾机理方面的系统研究。本文在对我国尾矿坝安全形势现场调研及国内外尾矿坝溃坝事故统计基础上,归纳总结出尾矿坝溃坝的几种主要类型,研究洪水漫顶、稳定破坏、渗流破坏、结构破坏和管理因素等导致的溃坝的致灾机理。应用数值分析方法,研究致灾因素与尾矿坝溃坝危险性之间的关系,建立尾矿坝溃坝危险性指标体系。当前,由于受到历史资料不足以及尾矿库专业人才匮乏等因素的影响,应用于尾矿坝溃坝安全性评价的分析方法主要为事故树分析、安全检查表分析、预先危险性分析、专家分析法等方法,这些方法大多为定性或半定量的评价方法。在研究了几种方法的优缺点后,基于模糊数学可将模糊概念加以量化的理论,本文采用模糊模式识别法对尾矿坝溃坝安全性进行了评价。在指标体系建立的基础上,利用层次分析法确定了各个指标的权重,最后建立了尾矿坝溃坝的模糊综合评价模型,并将其运用于首云铁矿和尚峪尾矿库,得出的评价结论验证了此模型的实用性。本论文依托“十一五”科技支撑计划项目,课题完成后可以为尾矿库风险评价和监测、预警提供关键技术。这些技术的应用与推广,可以提高我国尾矿库的技术装备水平。更多还原

【Abstract】 So far, about 8 541 tailing ponds have been established in nationwide scope except Tianjin and Shanghai. It is worth noting that less than 70 percent of tailings dams are in the normal operation in our country. About 44 percent of tailings dams are in risk, sickness and extended service status in some industries. The situation is very disadvantageous. To make things worse, domestic areas, industrial and mining enterprises or major cities and towns, etc. are located downstream most of these tailing ponds. Once tailings dam break, it will cause significant environmental pollution, property damage and human casualties. Statistics show that the proportion of the normal operation of domestic tailings is low and the security situation is quite grim. Therefore, it is imperative to strength safety management of the tailing ponds and establish tailings dam-break hazard index system and safety evaluation model, which will play a significant role in reducing and preventing the occurrence of tailing dam failing accident, ensuring safe operation of the tailing ponds, making them to better serve safe production of the mines as well as healthy, steady and rapid development of the national economy, etc.At present, in domestic, the main research contents of tailing ponds security is still the problem of deformation and stability. Even though many scholars have the view that tailings dam-break caused by many factors, but research results have been mostly focused on single factors. Now it is lack of system research on tailings dam-break mechanism of the hazard system. With the methods of documentary review, mathematical statistic analysis, and induction and summarization related accidents both in China and abroad, this article provides several main types of dam-break and studies the disaster-causing mechanism relevant to diffuse top floods, damage stability, seepage damage, structural and management, and brings out the comprehensive countermeasures to prevent the dam-break disaster. It also studies and establishes a dam failing hazard index system for the tailing ponds based on engineering analysis of the dam pond indexes as well as correlation analysis. There are several methods used in safety evaluation of tailings dam-break nowadays such as Fault Tree Analysis, Safety Check List, Preliminary Hazard Analysis, Expert Analysis and so on. After some research into the above methods, based on the fuzzy mathematical theory, this paper adopts Fuzzy Pattern Recognition to evaluation the security of tailings dam-break. After a hazard index system is set up, the weight of each index is calculated according to Analytical Hierarchy Process method, finally a Fuzzy Comprehensive Evaluation Model is built and applied to the tailings dam of He Shang Yu. It approves that the model works well.This paper relays on science and technology projects of the Eleventh Five-Year Plan. It can provide the key technology to make risk assessment and monitor and warning early after the subject finished. With the application and extension of these technologies, the level of technical equipment of our tailings will be improved.更多还原