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Gold Science and Technology ›› 2019, Vol. 27 ›› Issue (4): 497-504.doi: 10.11872/j.issn.1005-2518.2019.04.497

• Mining Technology and Mine Management • Previous Articles     Next Articles

Optimization Research on Stope Structural Parameters Based on Vague-RSM-AFSA Model

Guoyan ZHAO(),Zhenyang LI(),Juncheng DAI   

  1. School of Resources and Safety Engineering，Central South University，Changsha 410083，Hunan，China
  • Received:2018-09-03 Revised:2019-04-02 Online:2019-08-31 Published:2019-08-19
  • Contact: Zhenyang LI E-mail:gy.zhao@263.net;735424518@qq.com

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Abstract:

The average dip angle and thickness of a silver ore body are 70 degrees and 10 m respectively.The ore body is unstable and the surrounding rock of the hanging wall and footwall wall is relatively stable.In order to determine the optimum stope structure parameters and optimize the safety and economy of the mining scheme，a Vague-RSM-AFSA model was established to optimize the stope structural parameters.Fifteen schemes of stope structural parameters were designed based on the principle of central composite test method，and the numerical model of each scheme was established by Midas coupled FLAC3D. Stope structural parameters are related to the safety and economy of mine production.The maximum settlement displacement of stope roof，maximum horizontal displacement of pillar，mining-cutting ratio and the ore loss rate were selected as evaluation indexes based on the geological conditions，mining methods and other factors.The Vague theory can accurately express the fuzziness and uncertainty of information，the weight of each index was obtained by calculating Vague entropy of each index.Based on Vague set，the positive and negative ideal schemes within the optimum range of stope structural parameters were obtained，and the superiority of each scheme was calculated by Euclidean distance method.Response surface methodology （RSM） can accurately construct the complex non-linear response relationship between independent variables and dependent variables，response surface method （RSM） was used to establish the response surface model of stope structural parameters and superiority of various schemes in central composite test.The square R 2 of the fitting correlation coefficient of the model is 0.9766.The numerical analysis of three groups of structural parameters in the optimum range but not in the central composite test was carried out.The maximum error between the results and the response surface model is 0.0213，which shows that the established response surface model has high accuracy.Artificial fish swarm algorithms （AFSA） has a strong ability to search global extremum，and can effectively solve complex non-linear multi-objective optimization problems，the artificial fish swarm algorithm （AFSA） was used to optimize the superiority response surface model.The optimum stope structure parameters were obtained as follows： 20 m for stope height，32.8 m for stope length，16.1 m for pillar width.And the superiority is 0.2631，which is higher than the maximum superiority of 0.2271 in the central composite test，and the error between the optimization results and the numerical simulation results is 0.0037. It shows that the Vague-RSM-AFSA model has good optimization ability and high accuracy，which provides a new method for the optimization of stope structural parameters.

Key words: stope structure parameters, Vague, response surface method, artificial fish swarm algorithm, superiority degree

CLC Number: 

  • TD353

Fig.1

Flow chart of model calculation"

Fig.2

Rock mechanics test"

Table 1

Physical and mechanical parameters of rock mass"

岩石类型 密度/（kg ? m-3） 内聚力/MPa 内摩擦角/（°） 抗拉强度/MPa 抗压强度/MPa 弹性模量/GPa 泊松比
花岗岩 2711 6.05 22.03 3.69 53.76 7.03 0.16
板岩 2749 3.38 39.20 9.11 63.01 11.56 0.21
矿体 2926 1.52 35.33 2.54 32.49 9.71 0.21

Table 2

Factors and their levels of central composite test"

水平 因素
X 1/m X 2/m X 3/m
1 20 25 10
2 25 30 15
3 30 35 20

Table 3

Design of central composite test"

方案 X 1/m X 2/m X 3/m
1 20 25 10
2 20 25 20
3 20 30 15
4 20 35 10
5 20 35 20
6 25 25 15
7 25 30 10
8 25 30 15
9 25 30 20
10 25 35 15
11 30 25 10
12 30 25 20
13 30 30 15
14 30 35 10
15 30 35 20

Fig.3

Numerical model"

Table 4

Numerical simulation results of each scheme"

方案 Y 1/mm Y 2/mm Y 3/（ × 10-3 m ? t-1） Y 4/％
1 19.68 7.13 11.33 28.57
2 18.82 5.02 11.33 44.44
3 20.11 5.73 9.44 33.33
4 21.67 8.02 8.10 22.22
5 20.98 5.21 8.10 36.36
6 19.42 5.56 10.67 37.50
7 20.94 7.87 8.89 25.00
8 20.57 5.80 8.89 33.33
9 20.17 5.31 8.89 40.00
10 21.50 5.92 7.62 30.00
11 20.15 7.32 10.22 28.57
12 19.52 5.05 10.22 44.44
13 20.74 5.88 8.52 33.33
14 22.47 8.35 7.30 22.22
15 21.89 6.57 7.30 36.36

Fig. 4

Superiority of each scheme"

Table 5

Parameters and results of verification scheme"

方案 X 1/m X 2/m X 3/m Y 1/mm Y 2/mm Y 3/（ × 10-3 m ? t-1） Y 4/％ 优越度y 模型结果 误差
16 20 30 20 19.81 5.18 9.44 40.00 0.1433 0.1646 0.0213
17 25 25 20 19.26 5.25 10.67 44.44 -0.0019 0.0053 0.0072
18 30 30 20 20.84 5.46 8.52 40.00 0.0765 0.0885 0.0120

Fig.5

Superiority of numerical calculation and RSM prediction"

Fig.6

Moving trajectory of the optimum stope structural parameters"

Fig.7

Transformation process and result of superiority"

Table 6

Comparison of numerical simulation results of scheme 3 and scheme 19"

方案 Y 1/mm Y 2/mm Y 3/（ × 10-3 m ? t-1） Y 4/％ 优越度
3 20.11 5.73 9.44 33.33 0.2271
19 20.49 5.82 8.64 32.92 0.2594
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