Tailings accumulation dam safety state analysis by integrating heterogeneous hierarchical graph

doi:10.16265/j.cnki.issn1003-3033.2024.07.1892

Abstract

Abstract:

In order to investigate the influence of internal and external factors on the safety state of the tailings dam, a method for analysing the safety state of the tailings dam based on heterogeneous hierarchical diagrams was proposed. Firstly, a hierarchical causal graph was constructed based on a priori knowledge to link key factors such as environment, seepage field and stress field with the safety status of tailing dams, and an evaluation index system was established by combining the attribute characteristics of heterogeneous nodes. Secondly, the cloud model and set-pair analysis theory were used to quantitatively calculate the potential logical relationship between the heterogeneous causal graph and the safety stability of the tailings dam. A dynamic interval calculation method for quantitative indicators and a safety status level calculation model were proposed to convert the fuzziness and uncertainty of complex and diverse evaluation indicators into quantitative expressions. Finally, a tailings dam in Luoyang was used as an example to verify the scientificity of the model.The results show that the model can quantitatively analyse the link between factors and states and identify the causes of negative changes in stacked dams. The conclusions of the model analysis can be used for the safety management of the dam-building process.

Key words: heterogeneous hierarchical causal graph, tailings accumulation dam, safety situation, cloud model, set pair analysis

CLC Number:

X936

RUAN Shunling, HAN Simiao, YIN Yihan, LIU Di, LIU Jiajia, JIANG Song. Tailings accumulation dam safety state analysis by integrating heterogeneous hierarchical graph[J]. China Safety Science Journal, 2024, 34(7): 53-62.

Figures/Tables 14

Fig.1

Fig.2

Fig.3

Fig.4

Fig.5

Fig.6

Table 1

Smaller-is-better indicator dynamic class intervals

等级	等级标准
等级	$H e > E n 3$	$H e ≤ E n 3$
等级Ⅰ	[ $y m i n, E x + 0.67 S$ ]	[ $y m i n, E x + 0.67 E n$ ]
等级Ⅱ	[ $E x + 0.67 S, E x + S$ ]	[ $E x + 0.67 E n, E x + E n$ ]
等级Ⅲ	[ $E x + S, E x + 2 S$ ]	[ $E x + E n, E x + 2 E n$ ]
等级Ⅳ	[ $E x + 2 S, 3 S$ ], $y m a x < E x + 3 S$ [ $E x + 2 S, y m a x$ ], $y m a x ≥ E x + 3 S$	[ $E x + 2 E n, E x + 3 E n$ ], $y m a x < E x + 3 E n$ [ $E x + 2 E n, y m a x$ ], $y m a x ≥ E x + 3 E n$

Table 1

Table 2

Larger-is-better indicator dynamic class intervals

等级	等级标准
等级	$H e > E n 3$	$H e ≤ E n 3$
等级Ⅰ	[ $E x - 0.67 S, y m a x$ ]	[ $E x - 0.67 E n, y m a x$ ]
等级Ⅱ	[ $E x - S, E x - 0.67 S$ ]	[ $E x - E n, E x - 0.67 E n$ ]
等级Ⅲ	[ $E x - 2 S, E x - S$ ]	[ $E x - 2 E n, E x - E n$ ]
等级Ⅳ	[ $E x - 3 S, E x - 2 S$ ], $y m i n ≥ E x - 3 S$ [ $y m i n, E x - 2 S$ ], $y m i n < E x + 3 S$	[ $E x - 3 E n, E x - 2 E n$ ], $y m i n ≥ E x - 3 E n$ [ $y m i n, E x - 2 E n$ ], $y m i n < E x - 3 E n$

Table 2

Fig.7

Table 3

Classification results of indicators

参数指标	分级标准
参数指标	I级	Ⅱ级	Ⅲ级	Ⅳ级
降雨量X₁₁/mm	[0,0.11)	[0.11,0.214)	[0.214,9.4)	[9.4,80]
地震烈度 $X 1 2$ /度	[0,3)	[3,6)	[6,9)	[9,15]
地形地质 $X 1 3$	[0.8,1)	[0.35,0.8)	[0.05,0.35)	[0,0.05]
排放工艺 $X 1 4$	[1.3,1.37)	[1.37,1.38)	[1.38,1.40)	[1.40,1.43]
库水位X₂₁/m	[1 431.67,1 432.19)	[1 432.19,1 432.23)	[1 432.23,1 432.35)	[1 432.35,1 432.48]
浸润线X₂₂/m	[19.32,37.65)	[37.65,39.52)	[39.52,45.19)	[45.19,50.86]
干滩长度X₂₃/m	[310.58,546.58]	[298.55,310.58)	[262.09,298.55)	[224.8,262.09)
渗流量X₂₄/(L·s^-1)	[0,0.01)	[0.01,1)	[1,10)	(10,20]
表面位移X₃₁/mm	[-0.28,0]	[-0.34, -0.28)	[-0.52, -0.34)	[-13.29, -0.52)
表面位移X₃₁/mm	[0,1.98)	[1.98,2.79)	[2.79,5.23)	[5.23,40]
内部位移X₃₂/mm	[-0.77,0]	[-1.10, -0.77)	[-2.10, -1.10)	[-20.30, -2.10)
内部位移X₃₂/mm	[0,0.80)	[0.80,1.14)	[1.14,2.17)	[2.17,20.30]
安全超高X₃₃/m	[4.19,7.21]	[4.03,4.19)	[3.54,4.03)	[3.05,3.54)
尾矿性质X₃₄/mm	[0,0.1)	[0.1,0.3)	[0.3,0.6)	[0.6,1.0]

Table 3

Table 4

Table 5

Results of status level assessment

参数指标	评估等级	参数指标	评估等级
$X 11$	Ⅲ	$X 23$	Ⅱ
$X 12$	Ⅱ	$X 24$	Ⅲ
$X 13$	Ⅱ	$X 31$	Ⅱ
$X 14$	Ⅱ	$X 32$	Ⅲ
$X 21$	Ⅲ	$X 33$	Ⅱ
$X 22$	Ⅱ	$X 34$	Ⅱ

Table 5

Table 6

Table 7

References 25

[1]	OWEN J R, KEMP D, LÈBRE E, et al. Catastrophic tailings dam failures and disaster risk disclosure[J]. International Journal of Disaster Risk Reduction, 2020, 42:101361-101 371.
[2]	CLARKSON L, WILLIAMS D. An overview of conventional tailings dam geotechnical failure mechanisms[J]. Mining Metallurgy & Exploration, 2021, 38(3): 1305-1328.
[3]	BAKER E. Mine tailings storage: safety is no accident[M]. Nairobi and Arendal: United Nations Environment Programme and GRID-Arendal, 2017:1-37.
[4]	LUMBROSO D, MCELROY C, GOFF C, et al. The potential to reduce the risks posed by tailings dams using satellite-based information:ScienceDirect[J]. International Journal of Disaster Risk Reduction, 2019, 38:101209-101 222.
[5]	DU Zheyuan, GE Linlin, NG A H M, et al. Risk assessment for tailings dams in Brumadinho of Brazil using InSAR time series approach[J]. Science of The Total Environment, 2020, 717:137125-137 138.
[6]	BUSELLI G, LU Kanglin. Groundwater contamination monitoring with multichannel electrical and electromagnetic methods[J]. Journal of Applied Geophysics, 2001, 48(1):11-23.
[7]	蒋卫东, 李夕兵, 邱更生. 基于最大Lyapunov指数分析的尾矿坝浸润线控制混沌方法[J]. 安全与环境学报, 2003, 3(5):16-20.
	JIANG Weidong, LI Xibing, QIU Gengsheng. A new method for chaos-controlling of seepage line in tailings dam based on analysis of largest Lyapunov exponent[J]. Journal of Safety and Environment, 2003, 3(5):16-20.
[8]	WANG Ligang, YANG Xiaocong, HE Manchao. Research on safety monitoring system of tailings dam based on internet of things[C]. Institute of Physics.International Symposium on Application of Materials Science and Energy Materials, Part 1 of 2, 2018:716-722.
[9]	杨春和, 张超, 李全明, 等. 大型高尾矿坝灾变机制与防控方法[J]. 岩土力学, 2021, 42(1):1-17.
	YANG Chunhe, ZHANG Chao, LI Quanming, et al. Disaster mechanism and prevention methods of large-scale high tailings dam[J]. Rock and Soil Mechanics, 2021, 42(1):1-17.
[10]	颜学军. 上游法尾矿堆筑坝坝体沉积规律探讨[J]. 稀有金属与硬质合, 2008, 36(2):54-58.
	YAN Xuejun. Investigation on the depositing law of tailings dam by upstream damming[J]. Rare Metals and Cemented Carbides, 2008, 36(2):54-58.
[11]	张东明, 郑彬彬, 尹光志, 等. 高浓缩分级尾矿上游法堆坝及模型试验研究[J]. 岩土力学, 2016, 37(7):1832-1838,1 867.
	ZHANG Dongming, ZHENG Binbin, YIN Guangzhi, et al. Model tests on upstream dam-building method using concentrated and classified tailings[J]. Rock and Soil Mechanics, 2016, 37(7):1832-1838,1 867.
[12]	李辉, 易富, 张佳. 基于因素空间的尾矿坝稳定性综合评价[J]. 中国安全科学学报, 2019, 29(12): 28-34. doi: 10.16265/j.cnki.issn1003-3033.2019.12.005
	LI Hui, YI Fu, ZHANG Jia. Comprehensive stability evaluation of tailing dam based on factor space[J]. China Safety Science Journal, 2019, 29(12): 28-34. doi: 10.16265/j.cnki.issn1003-3033.2019.12.005
[13]	潘科, 许开立, 刘琛. 基于三角模糊理论的尾矿库风险评价研究[J]. 安全与环境学报, 2012, 12(2):242-245.
	PAN Ke, XU Kaili, LIU Chen. Risk evaluation model of tailings pond based on the triangular fuzzy theory[J]. Journal of Safety and Environment, 2012, 12(2): 242-245.
[14]	戴剑勇, 王雯雯, 黄晓庆. 基于网络云模型的尾矿库溃坝安全评估[J]. 安全与环境学报, 2022, 22(1):1-7.
	DAI Jianyong, WANG Wenwen, HUANG Xiaoqing. Safety assessment of tailings reservoir dam break based on network cloud model[J]. Journal of Safety and Environment, 2022, 22(1):1-7.
[15]	柯丽华, 黄畅畅, 李全明, 等. 尾矿库安全态势分析及其敏感因素研究[J]. 金属矿山, 2021(11):165-172.
	KE Lihua, HUANG Changchang, LI Quanming, et al. Safety situation analysis and sensitive factors study of tailings pond[J]. Metal Mine, 2021(11): 165-172.
[16]	DONG Kai, YANG Dewei, YAN Jihao, et al. Anomaly identification of monitoring data and safety evaluation method of tailings dam[J]. Frontiers in Earth Science, 2022, 10: 1 016 458-1 016 470.
[17]	刘迪, 卢才武, 连民杰, 等. 基于贝叶斯决策的尾矿坝干滩长度预警研究[J]. 中国安全科学学报, 2022, 32(增1):120-126.
	LIU Di, LU Caiwu, LIAN Minjie, et al. Dry beach length pre-warning of tailings dam based on Bayesian decision[J]. China Safety Science Journal, 2022, 32(S1):120-126. doi: 10.16265/j.cnki.issn1003-3033.2022.S1.0650
[18]	SITHARAM T G, HEGDE A M. Stability analysis of rock-fill tailing dam: an Indian case study[J]. International Journal of Geotechnical Engineering, 2017, 11(4): 332-342.
[19]	BAUDRIT C, TAILLANDIER F, CURT C, et al. Graph based knowledge models for capitalizing, predicting and learning: a proof of concept applied to the dam systems[J]. Advanced Engineering Informatics, 2022, 52: 101 551-101 571.
[20]	杨春和, 张超, 马昌坤, 等. 高应力条件下尾矿破碎特性及坝体稳定性研究[J]. 中国安全生产科学技术, 2022, 18(2):20-26.
	YANG Chunhe, ZHANG Chao, MA Changkun, et al. Study on tailings breakage characteristics and dam stability under high stress conditions[J]. Journal of Safety Science and Technology, 2022, 18(2):20-26.
[21]	曾纪涵, 章光, 吴浩, 等. 改进POT模型下尾矿坝综合预警值确定方法[J]. 中国安全科学学报, 2022, 32(5):134-139. doi: 10.16265/j.cnki.issn1003-3033.2022.05.1699
	ZENG Jihan, ZHANG Guang, WU Hao, et al. Determination method of comprehensive early-warning indexes for tailing dam based on improved POT model[J]. China Safety Science Journal, 2022, 32(5):134-139. doi: 10.16265/j.cnki.issn1003-3033.2022.05.1699
[22]	李全明, 段志杰, 于玉贞, 等. 尾矿坝沉积结构特征与性能演化规律研究进展[J]. 中国安全生产科学技术, 2022, 18(2):6-19.
	LI Quanming, DUAN Zhijie, YU Yuzhen, et al. Research progress on deposition structure characteristics and performance evolution law of tailings dam[J]. Journal of Safety Science and Technology, 2022, 18(2):6-19.
[23]	赵冰, 王光进, 刘文连, 等. 尾矿库坝体三维渗流场的数值模拟与试验分析[J]. 有色金属工程, 2020, 10(8):99-106.
	ZHAO Bing, WANG Guangjin, LIU Wenlian, et al. Numerical simulation and experimental analysis of three-dimensional seepage field in tailings dam body[J]. Nonferrous Metals Engineering, 2020, 10(8):99-106.
[24]	GB 39496—2020,尾矿库安全规程[S].
	GB 39496-2020, Safety regulation for tailings pond[S].
[25]	阳雨平, 黄丕森, 陈国国. 基于改进FIM-未确知测度的尾矿库风险评价模型及应用[J]. 安全与环境学报, 2021, 21(3):996-1004.
	YANG Yuping, HUANG Pisen, CHEN Guoguo. Safety evaluation of tailings pond based on FIM-optimization unascertained measure[J]. Journal of Safety and Environment, 2021, 21(3):996-1004.

评估等级	Ⅰ	Ⅱ	Ⅲ	Ⅳ
SHI(H)	2.063 9	1.573 2	1.780 0	1.713 3
s	0.289 5	0.220 6	0.249 6	0.240 3
置信区间	0.289 5	0.510 1	—	—

坝体级别	1		2		3
运行工况	瑞典圆弧法	简化毕肖普法	瑞典圆弧法	简化毕肖普法	瑞典圆弧法	简化毕肖普法
正常运行	1.30	1.50	1.25	1.35	1.20	1.30

地层	指标
	天然重度γ/ (kN·m^-3)	固结快剪		渗透系数/ (cm·s^-1)
	天然重度γ/ (kN·m^-3)	黏聚力 C/kPa	内摩擦角 ϕ/(°)	渗透系数/ (cm·s^-1)
人工填土-1	20.0	20	18	—
人工填土-2	22.0	0	40	—
尾细砂	22.6	0	85	—
尾粉砂	21.1	13.0	33.0	1.65^-4
尾粉土	21.4	12.0	30.0	4.93×10^-5
尾粉质黏土	21.7	14.0	26.0	1.34^-5
尾黏土	17.3	18.0	19.0	6.01^-6
粉质黏土	19.1	17.0	15.0	1.65×10^-6
强风化、中风化基岩层	23.0	18.0	19.0	9.32^-6