电渗析脱盐率预测模型研究
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摘要
电渗析法是以离子交换膜为分离介质,在直流电场的作用下,以电位差为推动力,能够有效去除水体中的无机盐。本文介绍了应用于实验室规模电渗析装置的实验数据、模糊模型(FL)、数学模型(MM )。目的是用来预测电渗析的脱盐率(SP ),脱盐率为浓度、温度、流速和电压的函数。
首先,主要是以离子在直流电场作用下发生电迁移传质为基础,根据电化学基本方程和电渗析的膜孔径传质平衡建立含盐废水脱盐率数学模型。实验考察电压、流量、温度以及进料浓度对电渗析装置的影响。应用实验脱盐率值计算出数学模型参数α值。利用回归程序,推导出数学模型参数α与进料浓度、电压、温度和流量的关系式,进而计算出数学模型参数α的理论值。从而计算出脱盐率的理论值。
针对数学模型在预测中存在的不足,以及影响电渗析工艺脱盐效果因素的复杂性等特点,应用Sugeno模糊逻辑推导机理建立NaCl溶液离子脱盐率模糊模型用于电渗析中,借助Matlab软件中的ANFIS功能进行训练测试,应用ANFIS中的混合学习方法确定隶属度函数,估算高斯隶属函数的参数c和σ以及结果函数,通过与实验数据及数学模型进行比较,对模型的预测能力进行验证分析,结果模糊模型的预测值和实验值之间有很好的吻合性,平均相对误差(MSRE)小于0.01。实验表明该模型具有较强的预测能力和实用性,ANFIS较适合用来建立电渗析中的参数间映射关系模型,数学模型的主要优点是通过两个与脱盐率有关的参数α、β表现出来的,其中α和电渗析的操作条件有关,β和电渗析的水力尺寸有关。这样数学模型可以按比例扩大应用范围。然而,根据数学模型的MSRE(大约为0.0397),数学模型不可能像模糊模型一样很好的预测实验数据。
Ion-exchange membrane is the crital medium of electrodialysis technology, under the directly electric field, with the potential difference as the driving force, effectively removed inorganic salts ionize in water solution. This paper presents experimental data, a fuzzy logic (FL) model, a mathematical model (MM) for a laboratory scale electrodialysis (ED) cell. The aim was to predict Removal rate as a function of concentration, temperature, ?ow rate and voltage.
At first, according to the property that ion electromigration happens on the external electric field, using an electrodialysis(ED) channel mass balance and fundamental electrochemical equations, a mathematical modeling was applied to model sepration from brine waste using ED. Experiments were conducted to investigate the effect of voltages, flow rates, temperature and feed concentrations on ED cell performance and the model parameter was calculated using sepration in the dilute compartment. Using experimental data, the equation was fitted forαas a function of voltage, flow rate, temperature and feed concentrations. Using multiple regression procedure, the model gives the values of sepration in the dilute compartment for various voltages, flow rates, temerature and feed concentrations.
Regarding to the existing MM for predicting, and analyzing the factors that affecting ED process demineralization, a Sugeno type FL inference system was applied to model NaCl ions separation using ED, training and testing was accomplished with the aid of MATLAB software, ANFIS methodology whit hybrid learning method was applied to identify membership function, estimate the parameters c andσof the applied two-parametric Gaussian membership function and the consequent functions. Compared with experimental data and MM, predictive power of a model was tested and analysed, FL modeling results showed that there is an excellent agreement between the experimental data and the predicted values, with mean squared relative error (MSRE) of less than 0.01. Expeiments show the model pccupies preferable predication performance and practicability, ANFIS is very well suited for the parameters mapping modeling of electrodialysis, Then, the results of a previously developed MM were presented. The MM related SP to hydrodynamic dimension of the ED cell and operation conditions via two distinct parametersαandβ. This ability favored the MM for scale-up applications. However, based on MSRE of the MM (about 0.0397), it could not obviously predict the experimental data as well as FL.
首先,主要是以离子在直流电场作用下发生电迁移传质为基础,根据电化学基本方程和电渗析的膜孔径传质平衡建立含盐废水脱盐率数学模型。实验考察电压、流量、温度以及进料浓度对电渗析装置的影响。应用实验脱盐率值计算出数学模型参数α值。利用回归程序,推导出数学模型参数α与进料浓度、电压、温度和流量的关系式,进而计算出数学模型参数α的理论值。从而计算出脱盐率的理论值。
针对数学模型在预测中存在的不足,以及影响电渗析工艺脱盐效果因素的复杂性等特点,应用Sugeno模糊逻辑推导机理建立NaCl溶液离子脱盐率模糊模型用于电渗析中,借助Matlab软件中的ANFIS功能进行训练测试,应用ANFIS中的混合学习方法确定隶属度函数,估算高斯隶属函数的参数c和σ以及结果函数,通过与实验数据及数学模型进行比较,对模型的预测能力进行验证分析,结果模糊模型的预测值和实验值之间有很好的吻合性,平均相对误差(MSRE)小于0.01。实验表明该模型具有较强的预测能力和实用性,ANFIS较适合用来建立电渗析中的参数间映射关系模型,数学模型的主要优点是通过两个与脱盐率有关的参数α、β表现出来的,其中α和电渗析的操作条件有关,β和电渗析的水力尺寸有关。这样数学模型可以按比例扩大应用范围。然而,根据数学模型的MSRE(大约为0.0397),数学模型不可能像模糊模型一样很好的预测实验数据。
Ion-exchange membrane is the crital medium of electrodialysis technology, under the directly electric field, with the potential difference as the driving force, effectively removed inorganic salts ionize in water solution. This paper presents experimental data, a fuzzy logic (FL) model, a mathematical model (MM) for a laboratory scale electrodialysis (ED) cell. The aim was to predict Removal rate as a function of concentration, temperature, ?ow rate and voltage.
At first, according to the property that ion electromigration happens on the external electric field, using an electrodialysis(ED) channel mass balance and fundamental electrochemical equations, a mathematical modeling was applied to model sepration from brine waste using ED. Experiments were conducted to investigate the effect of voltages, flow rates, temperature and feed concentrations on ED cell performance and the model parameter was calculated using sepration in the dilute compartment. Using experimental data, the equation was fitted forαas a function of voltage, flow rate, temperature and feed concentrations. Using multiple regression procedure, the model gives the values of sepration in the dilute compartment for various voltages, flow rates, temerature and feed concentrations.
Regarding to the existing MM for predicting, and analyzing the factors that affecting ED process demineralization, a Sugeno type FL inference system was applied to model NaCl ions separation using ED, training and testing was accomplished with the aid of MATLAB software, ANFIS methodology whit hybrid learning method was applied to identify membership function, estimate the parameters c andσof the applied two-parametric Gaussian membership function and the consequent functions. Compared with experimental data and MM, predictive power of a model was tested and analysed, FL modeling results showed that there is an excellent agreement between the experimental data and the predicted values, with mean squared relative error (MSRE) of less than 0.01. Expeiments show the model pccupies preferable predication performance and practicability, ANFIS is very well suited for the parameters mapping modeling of electrodialysis, Then, the results of a previously developed MM were presented. The MM related SP to hydrodynamic dimension of the ED cell and operation conditions via two distinct parametersαandβ. This ability favored the MM for scale-up applications. However, based on MSRE of the MM (about 0.0397), it could not obviously predict the experimental data as well as FL.
引文
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[2]李学梅,刘茉娥.发酵液中乳酸的电渗析法分离[J].高校化学工程学报,1998,12(3):231-235.
[3] P.B.Spoor etc. Continuous Deionization of a Dilute Nickel Solution[J].Chemical Engineering Journal, 2002, 85:127-135.
[4] T.Sirivedhin, J.McCue and L.Dallbauman. Reclaiming Produced Water for Beneficial Use: Salt Removal by Electrodialysis[J].Journal of Membrane Science, 2004, 243:335-343.
[5] Jing Guolin, XingLijie, Liu Yang, et al. Development of a Four-grade and Four- segment Electrodialysis Set-up for Desalination of Polymer-flooding Produced Water [J].Desalination, 2010, 264(3), 214-219.
[6] Jing Guolin, Xing Lijie, Li Shulin.Study of mathematical model in electrodialysis of desalination[C].4th International Conference on Bioinformatics and Biomedical Engineering, iCBBE, 2010, Jun.18-20, Chengdu, China.
[7] Jing Guolin, XingLijie, Li Shulin, et al.Reclaiming polymer-flooding produced water for beneficial use: salt removal via electrodialysis[J].Desalination and Water Treatment, 25(2011)71–77.
[8]张维润.电渗析工程学[M].科学出版社,1995:1-92.
[9]张艳华,田景新,陆际林.电渗析在化工行业中应用展望[J].辽宁化工,1997,26(2)70-72.
[10]马成良.我国电渗析技术发展浅析[J].膜科学于技术,1998(4):58-60.
[11]华河生,吴光夏,张东华,等.电渗析技术的新进展[J].环境污染技术治理与设备,2001,6(3):44.
[12]李福勤,杨云龙.电渗析技术发展方向的思考[J].科技情报开发与经济,2001,11(4):56-57.
[13]冯敏.工业水处理技术[M].海洋出版社,1992:201-210.
[14] Chen Yulian, Zhang He, Zhou Guangjun. Technical Characterization of Furfural Wastewater Treatment by Electrodialysis [J]. Water Treatment, 1993, (8):347-367.
[15]黄万抚,罗凯,李新冬.电渗析技术应用研究进展[J].中国水资源综合利用,2003,11:15-19.
[16] Shubo Deng, Renbi Bai.Produced Water from Polymer Flooding Process in Crude Oil Extraction: Characterization and Treatment by a Novelcrossflow Oil-water Separator[J].Separation and Purification Technology, 2002,29:207-216.
[17] J.J.Baschuk, Xianguo Li. Modeling of Polymer Electrolyte Membrane Fuel Cells withVariable Degrees of Water Flooding[J].Journal of Power Sources, 2000, 86:181-196.
[18] V.A.Shaposhnik,N.N.Zubets, I.P.Strygina, et al. Depassivation of Ion-Exchange Membranes in Electrodialysis[J].Russian Journal of Applied Chemistry, 2001, 74(10):1653-1657.
[19] Endre Nagy, Péter Hadik . Analysis of mass transfer in hollow-fiber membranes[J].Desalination, 2002, 145:147–152.
[20]王方.电去离子过程的反应叠加的实用模型[J].清华大学学报,1998,38(7):107-110.
[21] Emma Anna Carolina Emanuelsson, Andrew Guy Livingston.Study of Membrane Attached Biofilm Performance with Nitrateas Electron Acceptor[J].Desalination, 2002, 149:211–215.
[22] Millipore Corporation.Depletion Compartment for Deionization Apparatus and Methods. US Patent 4804451.
[23]王芳.混床离子交换树脂的电再生[J].工业水处理,1997,2:1-3.
[24]杨洪渊.用填充床电渗析直接处理废水同时制取纯水[J].水处理技术,1985,5: 53-56.
[25]徐新,林载祁.填充床电渗析制备纯水的研究[J].水处理技术,1996,6:336-341.
[26]沈立英.无极水全自动控制电渗析器.中国实用新型专利:ZL90222927.
[27]江维达.无隔板电渗析器[J].水处理技术,1994,20(5):314-317.
[28]鲁学仁.国家海洋局杭州水处理中心膜技术进展概况[J].水处理技术,1999,1:1-7.
[29] Liu K J, Lee H L. Bipolar Membranes[P].US Patent 4584246.
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