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
计量
- 文章访问数: 282
- HTML全文浏览量: 90
- PDF下载量: 39
- 被引次数: 0
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

HTML全文

图 1 微涡流澄清池

Figure 1. Micro-vortex clarifier

下载: 全尺寸图片幻灯片

图 2 涡流反应器

Figure 2. vortex reactor

下载: 全尺寸图片幻灯片

图 3 涡流澄清池模型

Figure 3. Vortex clarifier model

下载: 全尺寸图片幻灯片

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)

下载: 全尺寸图片幻灯片

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)

下载: 全尺寸图片幻灯片

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)

下载: 全尺寸图片幻灯片

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)

下载: 全尺寸图片幻灯片

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

下载: 全尺寸图片幻灯片

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

下载: 全尺寸图片幻灯片

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

下载: 导出CSV

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

下载: 导出CSV

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
${\rm{R} }{ {\text{e} }_{{\rm{DH}}} } = \dfrac{ {\rho \nu d} }{\mu } = \dfrac{ {\nu d} }{\upsilon }$	$I = 0.16{{ { {\rm{Re} } } _{ {\rm{DH} } } }^{ - \frac{1}{8} } }$	$k = \dfrac{3}{2}{({\mu _{{\rm{avg}}} }I)^2}$	$\varepsilon = {C\mu }^{^{\frac{3}{4} } }\dfrac{ { {k^{\frac{3}{2} } } }}{l}$	$G = \sqrt {\dfrac{ {\rho \varepsilon } }{\mu } }$

下载: 导出CSV

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

下载: 导出CSV

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

下载: 导出CSV

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

下载: 导出CSV

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

下载: 导出CSV

参考文献(20)

[1]	HOU C Y, SONG J E, YAN J G, et al. Growth indicator response of Zostera japonica under different salinity and turbidity stresses in the Yellow River Estuary, China[J]. Marine Geology,2020,424:106169. doi: 10.1016/j.margeo.2020.106169
[2]	SUN Y J, ZHU C Y, SUN W Q, et al. Plasma-initiated polymerization of chitosan-based CS-g-P(AM-DMDAAC) flocculant for the enhanced flocculation of low-algal-turbidity water[J]. Carbohydrate Polymers,2017,164:222-232. doi: 10.1016/j.carbpol.2017.02.010
[3]	陈永平, 罗雯, 许春阳, 等.高浓度黏性泥沙絮团微观结构及其对沉降特性的影响[J]. 泥沙研究,2020,45(6):8-14. CHEN Y P, LUO W, XU C Y, et al. Microstructure of cohesive sediment flocs with high concentration and its influence on the deposition characteristics[J]. Journal of Sediment Research,2020,45(6):8-14.
[4]	祝苑, 潘丁瑞, 汪艳, 等.新型助凝剂海藻酸钠的助凝效能及作用机制研究[J]. 环境工程技术学报,2019,9(6):680-684. doi: 10.12153/j.issn.1674-991X.2019.05.150 ZHU Y, PAN D R, WANG Y, et al. Study on coagulation aid efficiency and mechanism of new coagulant sodium alginate[J]. Journal of Environmental Engineering Technology,2019,9(6):680-684. doi: 10.12153/j.issn.1674-991X.2019.05.150
[5]	王艺, 戴红玲, 周政, 等.微涡流絮凝工艺处理低温低浊微污染水的优化[J]. 中国给水排水,2019,35(23):41-47. WANG Y, DAI H L, ZHOU Z, et al. Optimization of micro Vortex flocculation process for treatment of low temperature and low turbidity micro-polluted water[J]. China Water & Wastewater,2019,35(23):41-47.
[6]	DAI H L, QIU Z M, HU F P, et al. Floc Performance parameters during water treatment in a micro-Vortex flocculation process determined by machine vision[J]. Environmental Technology,2019,40(23):3062-3071. doi: 10.1080/09593330.2018.1465127
[7]	伏雨, 龙云, 肖波, 等.栅条絮凝池内部流场及颗粒运动状态模拟分析[J]. 环境工程,2021,39(4):25-29. FU Y, LONG Y, XIAO B, et al. Numerical simulation and analysis of flow field and particle motion in grid flocculation tank[J]. Environmental Engineering,2021,39(4):25-29.
[8]	陈玉, 王军, 张培璇.穿孔旋流絮凝池加网格板的数值模拟[J]. 中国给水排水,2019,35(1):48-51. CHEN Y, WANG J, ZHANG P X. Numerical simulation of revolving flow flocculation tank with grid plates[J]. China Water & Wastewater,2019,35(1):48-51.
[9]	HE W P, LU W J, XU S R, et al. Comparative analysis on floc morphological evolution in cylindrical and square stirred-tank flocculating reactors with or without baffles: flocculation-test and CFD-aided investigations[J]. Chemical Engineering Research and Design,2019,147:278-291. doi: 10.1016/j.cherd.2019.05.012
[10]	GANJARE A V, PATWARDHAN A W. CFD simulations of single-phase flow in settling tanks: comparison of turbulence models[J]. Indian Chemical Engineer,2020,62(4):413-426. doi: 10.1080/00194506.2019.1677514
[11]	王璐, 熊乐航, 张远, 等.LNG接收站冷排水的温降及余氯对水环境影响的数值模拟: 以湄洲湾东吴港区为例[J]. 环境工程技术学报,2021,11(5):962-969. doi: 10.12153/j.issn.1674-991X.20210007 WANG L, XIONG L H, ZHANG Y, et al. Numerical simulation of temperature drop and residual chlorine effect on water environment in LNG receiving station: a case study in Dongwu port area of Meizhou Bay[J]. Journal of Environmental Engineering Technology,2021,11(5):962-969. doi: 10.12153/j.issn.1674-991X.20210007
[12]	刘昶, 郑明霞, 孙源媛, 等.河道硬化对傍河地下水源补给结构及范围的影响[J]. 环境科学研究,2020,33(12):2820-2828. LIU C, ZHENG M X, SUN Y Y, et al. Effects of river hardening on recharging structure and range of riverside groundwater source field[J]. Research of Environmental Sciences,2020,33(12):2820-2828.
[13]	王子凌, 信欣, 刘琴, 等.响应面法优化CANON工艺处理猪场沼液脱氮性能研究[J]. 环境科学研究,2020,33(10):2326-2334. WANG Z L, XIN X, LIU Q, et al. Optimization of denitrification performance of CANON process for treating anaerobic digester liquor of swine wastewater by response surface methodology[J]. Research of Environmental Sciences,2020,33(10):2326-2334.
[14]	RAHMANNEZHAD J, MIRBOZORGI S A. CFD analysis and RSM-based design optimization of novel grooved micromixers with obstructions[J]. International Journal of Heat and Mass Transfer,2019,140:483-497. doi: 10.1016/j.ijheatmasstransfer.2019.05.107
[15]	SABETI M B, HEJAZI M A, KARIMI A. Enhanced removal of nitrate and phosphate from wastewater by Chlorella vulgaris: multi-objective optimization and CFD simulation[J]. Chinese Journal of Chemical Engineering,2019,27(3):639-648. doi: 10.1016/j.cjche.2018.05.010
[16]	林炜琛, 邵瑞朋, 王乔, 等.基于CFD和RSM的全效膜元件进水流道优化研究[J]. 膜科学与技术,2020,40(6):88-95. LIN W C, SHAO R P, WANG Q A, et al. Optimization of feed channel of full-effective membrane modules based on CFD simulation and RSM analysis[J]. Membrane Science and Technology,2020,40(6):88-95.
[17]	赵国强, 戴红玲, 王艺, 等.低温低浊水絮凝工艺的数值模拟与响应面优化试验研究[J]. 水资源与水工程学报,2021,32(1):117-124. ZHAO G Q, DAI H L, WANG Y, et al. Numerical simulation and response surface optimization of low temperature and turbidity water flocculation process[J]. Journal of Water Resources and Water Engineering,2021,32(1):117-124.
[18]	TOOR U A, DUONG T T, KO S Y, et al. Optimization of Fenton process for removing TOC and color from swine wastewater using response surface method (RSM)[J]. Journal of Environmental Management,2021,279:111625. doi: 10.1016/j.jenvman.2020.111625
[19]	GHAFFARIRAAD M, GHANBARZADEH LAK M. Landfill leachate treatment through coagulation-flocculation with lime and bio-sorption by Walnut-shell[J]. Environmental Management,2021,68(2):226-239. doi: 10.1007/s00267-021-01489-4
[20]	TASCA A L, MANNARINO G, GORI R, et al. Phosphorus recovery from sewage sludge hydrochar: process optimization by response surface methodology[J]. Water Science and Technology,2020,82(11):2331-2343. □ doi: 10.2166/wst.2020.485