【作者】 李玉仙；

【导师】 何文杰； 黄廷林；

【作者基本信息】 西安建筑科技大学 ， 市政工程， 2007， 博士

【摘要】 随着水源水质污染的不断加剧和供水水质标准的进一步提高，对供水工艺的要求也逐渐提高。因此，在满足出水水质约束的条件下，水处理工艺的集成优化成为该领域研究的重要课题。水源水质的变化对给水处理工艺的选择提出了客观要求。本文以北方地区典型代表城市——天津市的地表水源为主要研究对象，对其给水处理工艺及技术开展了较为系统的研究。主要研究成果和结论如下：采用Kmeans聚类分析方法对天津市滦河水源和黄河水源水质进行水质分期，把滦河水源划分为3个水质期（低温低浊期、常温常浊期、高温高藻期），黄河水源共划分为2个水质期（低污染期和高污染期）；并给出了各个水质期的日期界线、水质界线，以及主要的区分指标，为水厂处理工艺的优化调度提供依据。通过烧杯搅拌试验，确定了适合天津高藻水源的混凝沉淀单元最优运行控制参数：混合转速n=200转／min或Gt=11280～12000；一级反应转速n₁=80转／min；二级反应转速n₂=40转／min；投药量m=8mg／L，沉淀时间t=20min。考虑经济因素，因子重要性排序为：m＞G₂＞G＞t＞G₁。滤池级配优化的中试试验结果表明：煤砂双层滤池2中下部滤层的截污能力较大，水头增长速度较慢（3.5cm／h）；考虑出水水质和产水能力，煤砂双层滤池2为适合天津水源的较优级配。针对斜管沉淀池的布水不均匀性问题，首次提出了不均匀系数（k）的概念，并分析了不同结构参数对k的影响情况：当L／B大于4时，k急剧增加，且布水区的高度不宜小于1.3m。考虑水流对下滑絮团的影响，定性和定量分析了布水不均匀性对临界沉速u₀的影响：随着L／B的增加，u₀逐渐增大，当L／B大于6时（q=10m／h），下滑絮团所受的合力(F_合)下降为0；适宜的布水区高度h₁为1.2～1.6m。考虑絮体沉降，斜管管径越大，沉淀池平均临界沉速也越大，对絮凝效果的要求也就越高；从絮团下滑的角度考虑，不同表面负荷下存在斜管管径的最小要求：当q=15m／h时，min（d）=18mm；当q=30m／h时，min（d）=65mm。同时，一定管径下也对应有最大的表面负荷，当管径d=35mm时，最大表面负荷不能超过27m／h。针对划分的4个水质期（试验期间无滦河低温期），建立了各水质期内给水处理工艺的神经网络（ANN）模型，精确预测常规工艺和深度处理系统的处理效率和出水水质。常规工艺ANN模型的浊度相关系数均大于0.85，COD_Mn的相关系数均大于0.89；黄河高污染期需要增加深度处理单元来提高出水水质，且COD_Mn的相关系数基本大于0.80。ANN模型预测的相关系数均远大于临界相关系数(R_0.01)，说明了该模型的模拟精确性和预测稳定性。在原水水质变化的情况下根据所建立的ANN模型，利用遗传算法高效搜索功能确定了预设目标下（制水成本最低）的较优运行控制参数。结果表明，对于滦河高藻水源，优化参数结构下强化常规工艺出水COD_Mn≤3.0mg／L，出水浊度较非优化运行条件降低0.10～0.16NTU，制水成本降低0.017～0.049元／m³；混凝剂HPAC（High-efficiency Poly-Aluminium Chloride）效果好于FeCl₃，较优预氧化剂为PPC（高锰酸盐复合药剂）、KMnO₄或O₃。对于有机物较高的黄河高污染期，选择工艺为“混凝-气浮-过滤-O₃-BAC”，且FeCl₃效果略好于HPAC，PPC预氧化措施较为经济。利用所建立的层次分析模型，从经济、管理因素和技术指标等多方面，确定了适合天津水源条件的较优组合工艺，为水处理系统的调度提供依据。对于天津滦河水源和黄河水源的低污染期，较优的常规或强化常规工艺排序为：“混凝（HPAC）-絮凝-气浮-过滤”＞“PPC预氧化-混凝（HPAC）-絮凝-气浮-过滤”＞“PAC预处理-混凝（FeCl₃）-絮凝-气浮-过滤”。在黄河高污染期或原水水质进一步恶化时，较优的深度处理工艺排序为：“混凝（FeCl₃）-絮凝-气浮-过滤-GAC”＞“PPC预氧化-混凝（FeCl₃）-絮凝-气浮-过滤-GAC”＞“混凝（FeCl₃）-絮凝-气浮-过滤-O₃-BAC”。从进一步提高饮用水安全性考虑，需要增加深度处理单元，且较优的处理工艺为“混凝-絮凝-气浮-过滤-O₃-BAC”。目前，该研究的优选工艺：“预处理-混合絮凝-气浮-过滤（-消毒）”已经在示范工程中投入运行，其部分运行控制参数和结构变量为本研究成果。更多还原

【Abstract】 Along with more and more serious contamination of raw water and the advance of drinking water quality standards, the demand of treatment processes is becoming more and more stringent. And so, with the constraints of water quality, the integration and optimization of drinking water treatment processes is an important problem in water-supply field.It is necessary to select the optimal treatment process because of the change of raw water quality. Tianjin raw water could represent raw water characters of North-China. In this article, some studies have been finished based on Tianjin raw water, and the main results and conclusions are as follows.Clustering Analysis is introduced to divide Tianjin raw water into different periods for the first time. The results show that Luanhe raw water was divided into 3 periods（including low-temperature raw water, natural raw water, high algae raw water）, and Huanghe raw water into 2 periods（including mildly contaminated raw water and badly contaminated raw water）. At the same time, characters of each period （level） were analyzed and explained, which provide the theory basis of the optimization of water treatment processes.Based on laboratory-scale jar test, the optimal running parameters of coagulation-sediment units were obtained. The results include: rotation velocity of coagulation n=200rpm, or Gt=11280～12000; rotation velocity of the first and second flocculation units n₁=80rpm and n₂=40rpm; coagulant dose m=8mg/L, settling time t=20min. For economic consideration, the priority-order is m>G₂>G>t>G₁. From a pilot trial of filter bed grading, it is shown that the anthracite-sand filter has slower increase of head loss（3.5cm/h）, and it is the optimal filter bed grading of Tianjin raw water.Non-uniformity coefficient （k） of water distribution of Inclined-tube Settling Tank has been put forward and the influences of configuration parameters on k have been discussed as well. The results show that: k will increase sharply when L/B>4 and the height of water distribution area （h₁） should not be lower than 1.3m. The influences of k on sedimentation efficiency （Critical Settling Velocity, CSV） have also been studied. The results show that: CSV increases with L/B; under the conditions of q=10 and L/B≥6, the total force on the sliding flocs(F_total) is nearly equal to zero; the feasible height of water distribution area （h₁） is in range of 1.2～1.6m; the mean CSV increases with inclined tube diameter （d）, which need the enhancement of coagulation effect. For the down-sliding flocs, different surface load（q） will need different minimum diameters（d）. That is, q=15m/h, min（d）=18mm; q=30m/h, min（d）=65mm. Meanwhile, certain diameter will determine the corresponding maximal loads （q）. For example, when J=35mm, the maximal surface load should be 27m/h.According to the four periods of raw water quality（without Luanhe low temperature section during the experiment）, Artificial Neural Network （ANN） models of water treatment processes in each period have been set up to predict the effects and water quality of the conventional systems and advanced systems for process evaluation. For ANN models of conventional system, the correlation coefficient of turbidity is bigger than 0.85 and the coefficient of CODMn is bigger than 0.89. As Huanghe raw water is badly contaminated, advanced treatment is needed to improve the treated water quality, and the correlation coefficient of CODMn is bigger than 0.80. The simulated coefficients of ANN are much bigger than the critical coeffient (R_0.1), which indicates the simulation accuracy and prediction stability.Based on the changing raw water, Genetic Algorithms （GA） has been first combined with the ANN models to select the optimal running parameters of water treatment processes. The results show that, with high algae-laden raw water of Luanhe river, CODMn of treated water with optimal running parameters are not bigger than 3.0mg/L; comparing with non-optimal parameters, turbidity is reduced by 0.10～0.16NTU and cost of water product is reduced by 0.017～0.049Yuan/m³; HPAC （High-efficiency Poly-Aluminium Chloride） is the optimal coagulant and PPC, KMnO₄ or O₃ is the optimal pre-oxidant. With badly contaminated raw water of Huanghe river, the optimal process is "Coagulation-DAF-Filter-O₃-BAC"; FeCl₃ is better than HPAC and PPC is the optimal pre-oxidant.Based on the Analytical Hierarchy Process （AHP）, the optimal treatment processes are selected from the aspects of economy, management and technology. For Luanhe raw water and lightly contaminated Huanghe raw water, the order of optimal conventional treatment processes is: "Coagulation （HPAC） + Flocculation + DAF + Filter"> "Pre-oxidation （PPC） + Coagulation （HPAC） + Flocculation + DAF + Filter"> "Pre-adsorption （PAC） + Coagulation （FeCl₃） + Flocculation + DAF + Filter". With the badly contaminated Huanghe raw water or worse raw water quality, the order of optimal advanced treatment processes is: "Coagulation Flocculation + DAF + Filter + GAC"> "Pre-oxidation （PPC） + Coagulation （FeCl₃） + Flocculation + DAF + Filter + GAC"> "Coagulation （FeCl₃） + Flocculation + DAF + Filter + O3-BAC". For the enhancement of safe drinking water, it is necessary to select advanced treatment, and the optimal process is "Coagulation + Flocculation+ DAF + Filter + O₃-BAC".At present, the selected optimal treatment process, "Pre-oxidation +Coagulation +Flocculation +DAF +Filter + Disinfect", has been applied to a water plant in Tianjin. The running parameters and some configuration parameters are discussed in this article.更多还原