微涡流絮凝工艺处理高浊水的数值模拟与响应面优化试验

徐琪珂; 戴红玲; 赵国强; 胡锋平

doi:10.12153/j.issn.1674-991X.20210620

微涡流絮凝工艺处理高浊水的数值模拟与响应面优化试验

doi: 10.12153/j.issn.1674-991X.20210620

徐琪珂^{1, 2,},
戴红玲^{1, 2, ,},
赵国强^{1, 2},
胡锋平^{1, 2}

1.
华东交通大学土木建筑学院
2.
华东交通大学土木工程国家实验教学示范中心

基金项目: 江西省自然科学基金项目（20192BAB206038）；国家自然科学基金项目（61872141）；江西省省级重点实验室项目(20192BCD40013)；江西省教育厅科技计划项目（GJJ190298）

详细信息

作者简介:
徐琪珂（1996—），女，硕士研究生，主要从事给水、废水物化处理理论与技术研究，398023810@qq.com

通讯作者:
戴红玲（1980—），女，副教授，主要从事给水、废水物化处理理论与技术研究， dhl781228@126.com

中图分类号: X524
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出版历程
- 收稿日期: 2021-10-28

Numerical simulation and response surface optimization of micro-vortex flocculation process for high turbidity water treatment

XU Qike^{1, 2
,},
DAI Hongling^{1, 2
, ,},
ZHAO Guoqiang^{1, 2},
HU Fengping^{1, 2}

1.
School of Civil Engineering and Architecture, East China Jiaotong University
2.
National Experimental Teaching Demonstration Center of Civil Engineering, East China Jiaotong University

摘要

摘要: 针对微涡流絮凝工艺处理高浊水开展连续性工艺优化研究，采用计算流体力学（CFD）数值模拟软件，探究不同流量（流速）下絮凝区液流状态变化，确定最佳絮凝时间；应用响应面Box-Behnken设计方法，研究流量、混凝剂投加量与回流比及其交互作用对微涡流絮凝工艺处理高浊水效果的影响。结果表明：随着流量（流速）增大，絮凝区内湍动能、有效能耗、速度梯度及其变化率逐渐增大，但流速过大会导致絮凝时间不足，最佳流量为4.2~7.0 m³/h（最佳流速为0.41~0.67 m/s）；回流比是微涡流絮凝工艺的极显著影响因素，其次是混凝剂投加量，最后是流量，三者间具有协同作用；微涡流絮凝工艺处理高浊水的最佳工艺参数，流量为5.9 m³/h，混凝剂投加量为34.8 mg/L，回流比为0.8，浊度、UV₂₅₄、COD_Mn去除率分别可达99.23%、95.03%、71.42%。优化后的微涡流絮凝工艺为高浊水处理提供了新途径，具有一定的应用前景。
- 高浊水 /
- 微涡流絮凝 /
- CFD数值模拟 /
- 响应面 /
- 工艺优化
Abstract: The optimization of continuous process was conducted for the treatment of high turbidity water by micro-vortex flocculation process. The computational fluid dynamics (CFD) numerical simulation software was applied to explore the changes of liquid flow state in the flocculation area under different flow rate (flow velocity) so as to determine the optimal flocculation time. By using response surface Box-Behnken design method, the effects of flow rate, coagulant dosing and reflux ratio and their interactions on the treatment effectiveness of high turbidity water by micro-vortex flocculation process were studied. The research showed that as the flow rate (flow velocity) increased, the turbulent kinetic energy, effective energy consumption, G-value and its rate of change in the flocculation zone gradually increased, but too excessive flow velocity could lead to insufficient flocculation time, and thus the optimal flow rate range was 4.2-7.0 m³/h. or the optimal flow velocity was 0.41-0.67 m/s. The reflux ratio was a highly significant factor affecting the micro-vortex flocculation process, followed by the coagulant dosage and flow rate, with a synergistic effect between the three. The best process parameters of micro-vortex flocculation process for treating high turbidity water were: flow rate 5.9 m³/h, coagulant dosage 34.8 mg/L, and reflux ratio 0.8; the removal rates of turbidity, UV₂₅₄ and COD_Mn were 99.23%, 95.03%, and 71.42%, respectively. The optimized micro-vortex flocculation process could provide a new way for high turbidity water treatment technology with certain application prospects.
- high turbidity water /
- micro-vortex flocculation /
- CFD numerical simulation /
- response surface /
- process optimization

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图 1 微涡流澄清池

Figure 1. Micro-vortex clarifier

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图 2 涡流反应器

Figure 2. vortex reactor

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图 3 涡流澄清池模型

Figure 3. Vortex clarifier model

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图 4 不同流量（流速）下絮凝反应区速度矢量

Figure 4. Velocity diagram of flocculation reaction zone under different flow rates (flow velocities)

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图 5 不同流量（流速）下涡流澄清池湍动能

Figure 5. Cloud chart of turbulent kinetic energy in vortex clarifier under different flow rates (flow velocities)

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图 6 不同流量（流速）下涡流澄清池有效能耗

Figure 6. Cloud chart of effective energy consumption in vortex clarifier under different flow rates (flow velocities)

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图 7 不同流量（流速）下涡流澄清池絮凝区湍动能、有效能耗和G的变化曲线

Figure 7. Variation curves of turbulent energy, effective energy consumption and G-value in the flocculation zone of vortex clarifiers under different flow rates (flow velocities)

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图 8 各因素对浊度、UV₂₅₄、COD_Mn去除率的交互作用响应面

Figure 8. Response surface diagram of the interaction effect of factors on turbidity, UV₂₅₄, COD_Mn removal rate

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图 9 最优工况下浊度、UV₂₅₄、COD_Mn的去除率

Figure 9. Removal rate of turbidity, UV₂₅₄, COD_Mn under the optimal conditions

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表 1 配水水质

Table 1. Distributed water quality

水温/℃	pH	浊度/NTU	COD_Mn/（mg/L）	UV₂₅₄/cm⁻¹
15.3~21.8	6.2~7.5	195~213	7.8~12.5	0.256~0.282

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表 2 Fluent数值模拟工况的进口参数

Table 2. Inlet parameters of Fluent numerical simulation conditions

流量/（m³/h）	絮凝时间/min	进口流速/（m/s）	雷诺数	湍流强度/%
4	25.4	0.39	7 765.64	1.87
6	17	0.59	11 648.46	1.97
8	12.7	0.79	15 531.29	2.04

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表 3 评价指标

Table 3. Result evaluation indicators

雷诺数	湍流强度/%	湍动能/ (m²/s²)	有效能耗/ (m^2/s³)	涡旋速度梯度/s⁻¹
${\rm{R} }{ {\text{e} }_{{\rm{DH}}} } = \dfrac{ {\rho \nu d} }{\mu } = \dfrac{ {\nu d} }{\upsilon }$	$I = 0.16{{ { {\rm{Re} } } _{ {\rm{DH} } } }^{ - \frac{1}{8} } }$	$k = \dfrac{3}{2}{({\mu _{{\rm{avg}}} }I)^2}$	$\varepsilon = {C\mu }^{^{\frac{3}{4} } }\dfrac{ { {k^{\frac{3}{2} } } }}{l}$	$G = \sqrt {\dfrac{ {\rho \varepsilon } }{\mu } }$

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表 4 边界条件和求解方法

Table 4. Boundary conditions and algorithm

类别	结构参数求解设置
进口边界	流速进口（velocity inlet）、湍流强度、水力直径
出口边界	自由出流（outflow）
壁面边界	标准壁面函数
自由面边界	对称边界、刚盖定律
求解方法	SIMPLE格式求解，收敛初始值设置为10⁻⁵，标准k-ε湍流模型

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表 5 高浊水中试试验响应面分析因素与水平

Table 5. Response surface analysis factors and levels for high turbidity water pilot test

水平	流量/（m³/h）	混凝剂投加量/（mg/L）	回流比
−1	4	15	0.5
0	6	30	1.0
1	8	45	1.5

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表 6 优化试验设计及结果

Table 6. Optimization of experimental design and analysis of results

序号	X₁/（m³/h）	X₂/（mg/L）	X₃	Y₁/%	Y₂/%	Y₃/%
1	8	20	1.0	92.26	75.17	42.44
2	6	25	1.0	97.55	89.44	65.55
3	8	30	1.0	98.85	93.72	68.41
4	6	20	1.5	89.81	70.03	38.12
5	6	30	0.5	90.56	73.48	41.98
6	4	20	1.0	93.09	76.30	50.34
7	8	25	0.5	99.32	93.86	68.95
8	6	25	1.0	94.77	84.94	61.18
9	6	20	0.5	98.59	93.63	67.20
10	6	25	1.0	95.03	86.78	62.10
11	6	25	1.0	90.94	74.25	41.98
12	4	25	0.5	93.62	83.68	51.15
13	4	25	1.5	99.44	94.84	69.26
14	6	25	1.0	99.82	96.12	69.36
15	4	30	1.0	95.50	86.93	63.71
16	6	30	1.5	97.88	89.74	66.10
17	8	25	1.5	94.77	86.39	61.31

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表 7 浊度、COD_Mn和UV₂₅₄去除率回归方程显著性检验

Table 7. Significance test of regression equation of turbidity, COD_Mn and UV₂₅₄ removal rate

模型	均值	变异系数	相关系数（R²）	信噪比	校正后相关系数（ $R_{{\rm{adj}}}^2$）	失拟项	显著性
Y₁	0.95	1.14	0.953 3	11.849	0.893 2	0.017	显著
Y₂	0.85	2.94	0.961 7	12.492	0.912 5	0.11	显著
Y₃	0.58	7.17	0.939 6	9.783	0.861 9	0.19	显著

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