基于NSGA-Ⅱ算法的废石及尾砂混合充填料配比优化

doi:10.11872/j.issn.1005-2518.2022.01.102

Abstract

Abstract:

With the increasing attention on the environmental protection of resource development and the strict requirements for the discharge of waste rocks，tailings，waste residues and other wastes generated in resource development，it is particularly important to dispose these wastes.The mixed filling of waste rocks and tailings is the most effective way to solve the discharge of mine waste.Taking the underground filling of Gaofeng mine as an example，It is necessary to determine the optimal ratio of waste rock and tailings mixed filling materials.The particle size of tailings and waste rock were analyzed by laser method and sieve method.The chemical composition of waste rock and tailings was obtained by X-ray spectrometry.The orthogonal experiment with four factors and four levels was designed，and the range analysis of the experimental data was carried out.The primary and secondary factors affecting the strength of filling body，slurry bleeding rate and slurry slump were explored，and the filling material ratio that preliminarily met the requirements of the mine was obtained.The slurry concentration is 83%，the ash sand ratio is 0.25，the waste tail ratio is 1.5 and the amount of pumping agent is 0.5%.According to the experimental data，the quadratic polynomial regression model of 28 d filling body strength，slurry bleeding rate and slump was established.The theoretical value and experimental value of the regression model were compared and analyzed.It is found that the relative error is within a reasonable range，indicating that the model has certain reliability for the prediction of filling body performance.Multi-objective optimization Pareto solution set obtained based on NSGA-II algorithm.The mixture ratio of waste rock and tailings filling slurry with good performance and lowest cost was determined.The results are as follows：According to range analysis，The ratio of ash to sand has the greatest influence on the strength of filling body，and the influence of slurry concentration，waste tail ratio and pumping agent decreases in turn.The ash sand ratio has obvious control effect on the slurry bleeding rate，and the waste tail ratio，slurry concentration and pumping agent effect decrease in turn.The slurry concentration has the greatest influence on slump，and the influence of pumping agent，ash sand ratio and waste tail ratio decreases in turn.Without increasing the cost of additional materials，the proportion of waste rock can be appropriately increased to improve the strength of the filling body.The cost of filling material for the optimized scheme is reduced by 2.9% compared with the preliminary scheme determined by orthogonal test，the optimized filling ratio is slurry concentration 82.989%，ash sand ratio 0.240，waste tail ratio 1.419 and pumping agent 0.537%.

Key words: orthogonal test, mixed filling materials, regression model, multi-objective optimization, NGSA-Ⅱ algorithm, gamultiobj function

CLC Number:

TD853

Feng GAO,Haoquan AI,Yaodong LIANG,Zengwu LUO,Xin XIONG,Keping ZHOU,Gen YANG. Optimization of Proportioning of Waste Rock and Tailings Mixed Filling Materials Based on NSGA-II Algorithm[J].Gold Science and Technology, 2022, 30(1): 46-53.

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材料种类	真密度/（g·cm^-3）	松散密度/（g·cm^-3）	紧密密度/（g·cm^-3）	孔隙率/%	堆积密实度
废石	2.722	1.597	1.934	29.47	0.709
尾砂	3.091	1.313	1.760	43.06	0.569

水平	因素
水平	A（料浆浓度）	B（灰砂比）	C（废尾比）	D（泵送剂）
1	77%	1∶4	3∶7	0%
2	79%	1∶5	4∶6	0.5%
3	81%	1∶6	5∶5	1.0%
4	83%	1∶7	6∶4	2.0%

试验编号	因素				指标
试验编号	料浆浓度/%	灰砂比	废尾比	泵送剂 /%	28 d抗压强度/MPa	泌水率/%	坍落度/cm
1	77	1∶4	3∶7	0	3.176	12.87	27.8
2	77	1∶5	4∶6	0.5	2.570	12.84	28.6
3	77	1∶6	5∶5	1.0	2.498	11.59	27.2
4	77	1∶7	6∶4	2.0	1.698	17.68	28.7
5	79	1∶4	4∶6	1.0	5.408	10.45	28.8
6	79	1∶5	3∶7	2.0	3.019	9.86	29.8
7	79	1∶6	6∶4	0	2.912	17.29	28.4
8	79	1∶7	5∶5	0.5	2.233	12.43	29.3
9	81	1∶4	5∶5	2.0	5.337	10.34	28.8
10	81	1∶5	6∶4	1.0	3.761	12.96	27.6
11	81	1∶6	3∶7	0.5	3.022	13.53	28.0
12	81	1∶7	4∶6	0	1.943	13.02	26.8
13	83	1∶4	6∶4	0.5	7.622	7.070	26.0
14	83	1∶5	5∶5	0	4.990	9.72	25.5
15	83	1∶6	4∶6	2.0	3.073	14.55	26.6
16	83	1∶7	3∶7	1.0	2.747	14.29	22.3

指标	因素	A	B	C	D	因素主次
28 d抗压强度/MPa	k₁	2.486	5.386	2.991	3.255	B>A>C>D
	k₂	3.393	3.585	3.249	3.862
	k₃	3.516	2.876	3.765	3.604
	k₄	4.608	2.155	3.998	3.282
	R	2.122	3.231	1.007	0.607
泌水率/%	k₁	13.75	10.18	12.64	13.23	B>C>A>D
	k₂	12.51	11.35	12.72	11.47
	k₃	12.46	14.24	11.02	12.32
	k₄	11.41	14.36	13.75	13.11
	R	2.34	4.18	2.73	1.76
坍落度/cm	k₁	28.1	28.7	27.0	27.1	A>D>B>C
	k₂	29.1	27.9	27.7	28.9
	k₃	27.8	27.6	27.7	26.5
	k₄	25.1	26.8	27.6	28.5
	R	4.1	1.8	0.70	2.20

组号	料浆浓度/%	灰砂比	废尾比	泵送剂/%	28 d抗压强度/MPa	泌水率/%	坍落度/cm
1	82.988	0.248	1.371	1.087	7.185	6.517	26.72
2	82.988	0.250	1.130	0.807	7.888	6.512	27.35
3	82.991	0.246	1.307	0.645	7.508	6.653	26.66
4	82.990	0.250	1.072	1.044	7.824	6.468	27.50
5	82.993	0.248	1.298	0.737	7.575	6.523	26.75
6	82.989	0.240	1.419	0.537	7.066	6.897	26.16
7	82.990	0.242	1.412	0.499	7.213	6.891	26.19
8	82.999	0.245	1.412	0.458	7.365	6.896	26.21
9	82.995	0.247	1.221	0.524	7.651	6.845	26.89
10	82.990	0.250	1.187	0.994	7.694	6.367	27.26

Optimization of Proportioning of Waste Rock and Tailings Mixed Filling Materials Based on NSGA-II Algorithm

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组号	成本/（元/吨）	组号	成本/（元/吨）
1	129.37	6	120.38
2	127.66	7	120.80
3	124.06	8	121.58
4	130.29	9	123.34
5	125.84	10	128.31

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