Optimization model of dust suppressant component ratio based on response surface methodology

doi:10.16265/j.cnki.issn1003-3033.2023.01.0175

Abstract

Abstract:

In order to solve the nonlinear problem of the optimization process for dust suppressants composed of multi-functional components, a ratio optimization model was proposed based on the response surface method. The variation laws among the influencing factors and between the influence factors and response values were discussed, and the optimal formula of dust suppressant was obtained according to the results of response surface analysis. Based on the central composite design method, the volume fractions of wetting, moisturizing and bonding components were taken as the independent variables, and the dust deposition time, water loss rate and wind erosion rate were taken as the dependent variables. The equation fitting of multiple linear and variance analysis were carried out according to the data of the laboratory experiment, and the prediction results of the optimal formula were obtained, and then a test was carried out to verify the results. The variance analysis and verification test show that the deviation between the predicted values and the experimental values is less than 6.0%. Compared with the control group (water), the dust deposition time of the optimized group is 23 times faster. The water loss rate and wind erosion rate are 3.00% and 2.64% lower, respectively. It shows that the optimized group has excellent wetting, moisturizing and bonding properties, which proves that the optimization model has good predictive performance for the nonlinear problem of the optimization process for multi-components dust suppressant.

Key words: response surface methodology(RSM), dust suppressant, ratio optimization, central composite design, nonlinear optimization

LI Ming, TANG Jiao, SONG Xinzhu, YANG Huaizhen, LI Zhi. Optimization model of dust suppressant component ratio based on response surface methodology[J]. China Safety Science Journal, 2023, 33(1): 88-94.

Figures/Tables 7

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因素/ %	水平(代码)
因素/ %	-1.682	-1	0	+1	+1.682
ϕ(A)	0.050	0.161	0.325	0.489	0.600
ϕ(B)	0.500	1.007	1.750	2.493	3.000
ϕ(C)	0.002	0.003	0.004	0.005	0.006

序号	ϕ(A)	ϕ(B)	ϕ(C)	Y₁/s	Y₂/%	Y₃/%
1	-1	-1	-1	7.0	12.87	1.78
2	1	-1	-1	5.0	12.35	1.89
3	-1	1	-1	6.0	12.13	1.52
4	1	1	-1	4.0	11.98	1.87
5	-1	-1	1	5.0	13.58	0.98
6	1	-1	1	6.0	13.72	1.15
7	-1	1	1	11.0	12.29	1.05
8	1	1	1	6.0	12.29	1.28
9	-α	0	0	7.0	13.52	1.34
10	α	0	0	6.0	13.19	1.64
11	0	-α	0	15.0	13.85	1.83
12	0	α	0	14.0	11.29	1.27
13	0	0	-α	7.0	13.69	2.03
14	0	0	α	5.0	12.82	1.08
15	0	0	0	11.0	13.09	1.12
16	0	0	0	14.0	13.89	1.39
17	0	0	0	13.0	13.71	0.93
18	0	0	0	13.0	13.64	0.96
19	0	0	0	14.0	13.34	1.07
20	0	0	0	15.0	14.05	1.29

项目	粉尘沉降时间			失水率			风蚀率
变量	均方	F值	P值	均方	F值	P值	均方	F值	P值
模型	29.320 0	6.770 0	0.003 1	0.992 3	4.000 0	0.020 7	0.228 5	7.590 0	0.002 0
A	6.860 0	1.580 0	0.236 7	0.086 2	0.347 7	0.568 5	0.136 3	4.530 0	0.059 3
B	0.393 5	0.090 8	0.769 3	4.850 0	19.550 0	0.001 3	0.076 5	2.540 0	0.142 2
项目	粉尘沉降时间			失水率			风蚀率
C	0.509 0	0.117 5	0.738 9	0.086 5	0.348 9	0.567 8	1.290 0	42.840 0	< 0.000 1
AB	4.500 0	1.040 0	0.332 1	0.006 6	0.026 7	0.873 5	0.011 2	0.373 5	0.554 7
AC	0.000 0	0.000 0	1.000 0	0.082 0	0.330 8	0.577 9	0.000 5	0.014 9	0.905 1
BC	8.000 0	1.850 0	0.204 0	0.324 0	1.310 0	0.279 6	0.028 8	0.956 2	0.351 2
A²	124.630 0	28.770 0	0.000 3	0.430 2	1.740 0	0.217 1	0.155 7	5.170 0	0.046 3
B²	0.182 0	0.042 0	0.841 7	2.920 0	11.790 0	0.006 4	0.225 7	7.490 0	0.020 9
C²	140.070 0	32.330 0	0.000 2	0.624 3	2.520 0	0.143 6	0.232 1	7.710 0	0.019 6
残差	4.330 0	—	—	0.247 9	—	—	0.030 1	—	—
失拟项	6.800 0	3.640 0	0.091 2	0.370 7	2.960 0	0.129 2	0.027 1	0.817 3	0.584 9
纯误差	1.870 0	—	—	0.125 1	—	—	0.033 1	—	—