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黄金科学技术 ›› 2023, Vol. 31 ›› Issue (6): 1014-1022.doi: 10.11872/j.issn.1005-2518.2023.06.078

• 采选技术与矿山管理 • 上一篇    下一篇

干堆尾矿库稳定性影响因素的敏感性分析

许云美(),袁利伟(),龙皓楠   

  1. 昆明理工大学公共安全与应急管理学院,云南 昆明 650093
  • 收稿日期:2023-05-23 修回日期:2023-08-21 出版日期:2023-12-31 发布日期:2024-01-26
  • 通讯作者: 袁利伟 E-mail:18487223851@163.com;yuanLW@kust.edu.cn
  • 作者简介:许云美(1997-),女,云南宣威人,硕士研究生,从事矿山安全研究工作。18487223851@163.com
  • 基金资助:
    国家自然科学基金项目“高海拔高寒矿区边坡失稳与地表形变行为模式研究”(53264020);云南省社会发展专项重点研究开发项目 “生产过程与灾害演化安全监测及预警技术研究”(202003AC100002)

Sensitivity Analysis of Stability Influencing Factors of Dry Heap Tailings Reservoir

Yunmei XU(),Liwei YUAN(),Haonan LONG   

  1. Faculty of Public Security and Emergency Management,Kunming University of Science and Technology,Kunming 650093,Yunnan,China
  • Received:2023-05-23 Revised:2023-08-21 Online:2023-12-31 Published:2024-01-26
  • Contact: Liwei YUAN E-mail:18487223851@163.com;yuanLW@kust.edu.cn

摘要:

为了探究干堆尾矿库的尾矿坝高和堆积尾粉土的物理参数对尾矿库稳定性的敏感性,基于MIDAS数值计算模型,模拟尾矿库在不同工况下的稳定性,并运用正交试验设计与灰色关联分析相结合的方法,分析尾矿库不同参数与安全系数之间的关联性。结果表明:尾矿库的子坝坝高、内摩擦角、弹性模量、黏聚力和渗透系数对尾矿库安全系数的关联程度分别为0.746、0.620、0.581、0.542和0.490,采用定量化方法直观地反映了各影响因素对干堆尾矿库安全系数的敏感程度。由此可知,影响尾矿库稳定性的因素主次顺序为子坝坝高>内摩擦角>弹性模量>黏聚力>渗透系数。

关键词: 尾矿库, 影响因素, MIDAS, 正交试验, 灰色关联分析, 敏感性分析

Abstract:

In order to explore the sensitivity of the tailings dam height and the physical parameters of accumulated tailings silt of dry tailings reservior to the factors affecting the stability of the tailings reservior,the sensitivity of influencing factors of tailings reservior to the factors affecting the stability of the tailings reservior was quantitatively and intuitively analyzed by the combination method of orthogonal design and grey correlation analysis.After analysis,five factors of dam height of tailings reservior,cohesion of tailing silt,internal friction angle,permeability coefficient and elastic modulus of tailings reservoir were determined as test factors.Five test factors were selected according to the dam height of tailings reservior and the physical parameters of tailing silt.The orthogonal design scheme was designed and the safety factor of the orthogonal test scheme was calculated by MIDAS numerical simulation software.Then the grey correlation analysis method was used to analyze the five different factors,and the correlation degree of five values of dam height,cohesion,internal friction angle,permeability coefficient and elastic modulus of tailings reservoir to the stability of tailings pond is analyzed.The analysis results show that the correlation degree of dam height,internal friction angle,elastic modulus,cohesion and permeability coefficient of tailings reservoir to the safety factor of tailings pond was 0.746,0.620,0.581,0.542 and 0.490 respectively.It can be concluded that the order of influence factors of the stability on tailings reservior stability is as follows:sub-dam height>internal friction angle>elastic modulus>cohesion>permeability coefficient.It can be seen that the most significant influence on the stability of tailing reservior is the dam height of tailing reservior,followed by the internal friction angle,elastic modulus and cohesion of tailing silt,while the permeability coefficient of tailing silt has the least significant influence on the stability of tailings reservior.Therefore,in the process of the design and daily management of tailings reservior,the balance between dam height and storage capacity of tailings pond should be considered.In the process of daily treatment,the flood discharge management of tailings reservior should be strengthened to reduce the erosion of water on the tailings silt.

Key words: tailings reservoir, influencing factors, MIDAS, orthogonal test, grey correlation analysis, sensitivity analysis

中图分类号: 

  • TD926.4

表1

坝体岩土层主要物理力学参数"

地层编号岩土名称天然密度ρ/(g·cm-3内聚力Ck/kPa内摩擦角φk/(°)承载力特征值Fak/kPa渗透系数/(cm·s-1
尾粉土1.3015.5025.21704.58×10-3
粉质黏土1.8017.6015.42001.01×10-4
黏土1.7231.6412.62201.18×10-7

图1

尾矿库地层分布"

图2

尾矿库模型图"

表2

尾矿坝影响因素水平"

水平

子坝坝高

/m

黏聚力

/kPa

内摩擦角

/(°)

渗透系数

/(m·d-1

弹性模量

/MPa

13010.520.2215.6
23515.525.2420.6
34020.530.2625.6
44525.535.2830.6
55030.540.21035.6

表3

正交试验方案及分析结果"

子坝坝高

/m

黏聚力

/kPa

内摩擦角

/(°)

渗透

系数

(m·d-1

弹性模量

/MPa

最大整体位移

/m

最大

剪应力

/(kN·m-2

安全系数Fs
13010.520.2215.62.256138.3981.523
23015.525.2420.62.213137.5991.575
33020.530.2625.62.131136.1621.594
43025.535.2830.62.015135.1951.604
53030.540.21035.62.000135.1551.606
63510.525.2630.62.649160.8761.428
73515.530.2835.62.570159.9331.438
83520.535.21015.62.505159.4111.444
93525.540.2220.62.419158.5261.452
103530.520.2425.62.449159.2701.445
114010.530.21020.62.782181.0991.326
124015.535.2225.62.799181.4391.325
134020.540.2430.62.741180.9201.331
144025.520.2635.62.734180.6401.332
154030.525.2815.62.696179.8341.339
164510.535.2435.63.000190.6851.280
174515.540.2615.62.946181.5981.287
184520.520.2820.63.074184.9821.283
194525.525.21025.62.935181.6421.288
204530.530.2230.62.945184.9721.287
215010.540.2825.63.270211.4001.222
225015.520.21030.63.414213.7221.203
235020.525.2235.63.360213.4811.206
245025.530.2415.63.242210.2641.229
255030.535.2620.63.233209.3661.238

图3

安全系数随各参数变化情况"

图4

最大整体位移和最大剪应力随安全系数变化情况"

图5

尾矿库整体位移和最大剪切应力极值云图"

图6

模拟工况下y方向位移云图"

表4

2021—2022年尾矿库InSAR沉降量监测结果"

监测年份沉降点位移量/mm
123
202163.251.64.7
202254.643.510.0

图7

各岩体参数与安全系数的关联程度"

Chen Congcong, Zhao Yiqing, Jiang Linjing,et al,2021.Linkage analysis of hidden danger factors of tailings ponds based on text mining[J].Mining Research and Development,41(11):26-33.
Chen Peng, Wei Zuo’an, Xia Liyuan,et al,2015.Probability analysis of tailings dam instability considering soil spatial variability[J].The Chinese Journal of Geological Hazard and Control, 26(1):66-70.
Chu Xuewei, Xu Mo, Wang Zhongmei,2016.Seepage stability analysis of a phosphogypsum tailings dam[J].Journal of Engineering Geology,24(4):661-667.
Deng Julong,1988.Grey Prediction and Decision [M].Wuhan:Huazhong University of Science and Technology Press.
Ge Yunfeng, Tang Huiming, Xiong Chengren,et al,2014.Effect of sliding plane mechanical parameters on landslide stability—A case study of Jiweishan rock slide in Wulong,Chongqing[J].Chinese Journal of Rock Mechanics and Engineering,33(Supp.2):3873-3884.
Guo Yanhua, Chen Fangyu, Hu Songlin,2022.Sensitivity analysis of key influencing factors of tailings dam stability[J].Mining Technology, 22(2):99-102.
He Rongxing, Han Zhiyong, Liu Yang,et al,2022.Sensitivity analysis of stability factors of goaf based on numerical simulation orthogonal test[J].China Mining Magazine,31(6):109-117.
Islam S,2021.A study on the mechanical behaviour of three different fine-grained mine tailings[J].Journal of King Saud University-Engineering Sciences,35(5):335-341.
Jiang Shuihua, Zhu Mingming, Huang Jinsong,2019.Stability reliability analysis of tailings dam considering spatial variability of tailings material parameters[J].Journal of Safety Science and Technology,15(12):72-77.
Li Lu,2021.Numerical simulation study on influencing factors of surrounding rock stability based on AHP-Orthogonal experiment model[J].Pearl River, 42(8):55-61.
Li Tao, Liu Guodong, Wang Cong,2019.Instability probability and sensitivity analysis of tailings dam based on reliability theory[J].The Chinese Journal of Geological Hazard and Control, 30(3):81-86.
Liu Lihao, Miao Linchang,2022.Prediction of soil slope stability based on joint grey relational analysis[J].Highway Transportation Technology,39(10):32-39.
Xiaoduo Ou, Lu Xiaojin, Zhong Yihe,2021.Analysis of seismic dynamic response of rockfill dam of large-scale aluminium sludge dump[J].Journal of Disaster Prevention and Mitigation Engineering,41(6):1184-1194.
Piciullo L, Storrøsten E B, Liu Z,et al,2022.A new look at the statistics of tailings dam failures[J].Engineering Geology, 303:106657.
Rahman N U A,2019.Investigation on slope stability using Monte Carlo simulation:A case study of ulu jelai hydroelectric project slope parameters & design concept[J].Materials Today:Proceedings,19:1216-1224.
Vergara Á, Palma S, Álvarez A,et al,2022.Hazards in mining:A novel model for the prediction of run-out distances in tai-lings dams using CFD[J].International Journal of Rock Mechanics and Mining Sciences, 153:105049.
Wang Junqing, Li Jing, Li Qi,et al,2009.Analysis of factors affecting the stability of loess high slope—Taking Baojixia water diversion project as an example[J].Rock and Soil Me-chanics,30(7):2114-2118.
Yin Guangzhi, Wang Wensong, Wei Zuo’an,et al,2018.Analysis of permanent deformation and stability of high pile tailings dam under earthquake [J].Rock and Soil Mechanics,39(10):3717-3726.
Zhang Ning, Li Yulei, Li Zhehui,et al,2022.Stability reliability analysis of tailings dam slope based on Monte-Carlo method[J].Uranium Mining and Metallurgy,41(3):278-282.
Zhao Guoyan, Wu Pan, Zhu Xingfu,et al,2019.Grey correlation analysis of application priority of green mining technology in Sanshandao gold mine[J].Gold Science and Te-chnology,27(6):1-10.
陈聪聪,赵怡晴,姜琳婧,等,2021.基于文本挖掘的尾矿库隐患因素关联分析[J].矿业研究与开发,41(11):26-33.
陈鹏,魏作安,夏丽媛,等,2015.考虑土性空间变异的尾矿坝失稳概率分析[J].中国地质灾害与防治学报, 26(1):66-70.
褚学伟,许模,王中美,2016.某磷石膏尾矿库堆积坝渗透稳定性分析[J].工程地质学报,24(4):661-667.
邓聚龙,1988.灰色预测与决策[M].武汉:华中理工大学出版社.
葛云峰,唐辉明,熊承仁,等,2014.滑动面力学参数对滑坡稳定性影响研究——以重庆武隆鸡尾山滑坡为例[J].岩石力学与工程学报,33(增2):3873-3884.
郭彦华,陈方瑜,扈松林,2022.尾矿库坝体稳定性关键影响因素敏感性分析[J].采矿技术,22(2):99-102.
何荣兴,韩智勇,刘洋,等,2022.基于数值模拟正交试验的采空区稳定性因素的敏感性分析[J].中国矿业,31(6):109-117.
蒋水华,朱明明,黄劲松,2019.考虑尾矿材料参数空间变异性的尾矿坝稳定可靠度分析[J].中国安全生产科学技术,15(12):72-77.
李路,2021.基于AHP-正交试验模型围岩稳定性影响因素数值模拟研究[J].人民珠江, 42(8):55-61.
李涛,刘国栋,王聪,2019.基于可靠度理论的尾矿坝失稳概率及敏感性分析[J].中国地质灾害与防治学报, 30(3):81-86.
刘栗昊,缪林昌,2022.基于联合灰色关联分析的土质边坡稳定性预测[J].公路交通科技,39(10):32-39.
欧孝夺,陆小金,钟一和,2021.大型铝土排泥库堆石坝地震动力响应分析[J].防灾减灾工程学报,41(6):1184-1194.
王俊卿,李靖,李琦,等,2009.黄土高边坡稳定性影响因素分析——以宝鸡峡引水工程为例[J].岩土力学,30(7):2114-2118.
尹光志,王文松,魏作安, 等,2018.地震作用下高堆尾矿坝永久变形与稳定性分析[J].岩土力学,39(10):3717-3726.
张宁,李玉雷,李哲辉,等,2022.基于Monte-Carlo法的尾矿库坝坡稳定可靠度分析[J].铀矿冶,41(3):278-282.
赵国彦,吴攀,朱幸福,等,2019.三山岛金矿绿色开采技术应用优先级的灰色关联分析[J].黄金科学技术,27(6):1-10.
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