应用溶解扩散模型预测钴的渗透行为

摘要/Abstract

摘要：

摘要：应用溶解扩散模型预测反渗透去除放射性废水溶液中钴的渗透行为.研究了低浓度钴离子的渗透行为，结合溶解扩散模型和物料平衡，推导出渗透分离的方程.首先通过拟合较高浓度钴离子渗透的实验数据，求得模型的相关参数，然后针对较低浓度钴离子的渗透实验数据，与模型预测数据进行对比.结果显示，实验数据与模拟数据相对误差不超过15%，该溶解扩散模型可以很好地预测较低钴离子浓度下的渗透行为.

关键词: , 反渗透, 钴离子, 溶解扩散模型

Abstract:

Abstract： The solution-diffusion model was used to predict the behavior of reverse osmosis membrane,when used for the removal of cobalt from radioactive wastewater.System mass balances together with solutiondiffusionmass transfer models were used to simulate the separation process of low concentrations of cobalt.Model equation constants were obtained when the cobalt concentration was high, and the experimental data were then compared with simulated data when the cobalt concentration was low. The results show that the relative error between experimental data and simulated data does not exceed 15%. Good agreement between the experimental and the predicted cobalt concentrations suggests that the solutiondiffusion model can be used to well predict osmotic concentration even when the concentration of cobalt is low.
Key words：

Key words: reverse osmosis, cobalt ions, solution-diffusion model

中图分类号:

TL 941.19

乐志东，蒯琳萍. 应用溶解扩散模型预测钴的渗透行为[J]. 上海交通大学学报（自然版）, 2014, 48(11): 1650-1654.

YUE Zhidong，KUAI Linping. Application of SolutionDiffusion Model in Removal of Cobalt Ions by Reverse Osmosis[J]. Journal of Shanghai Jiaotong University, 2014, 48(11): 1650-1654.

参考文献

［1］ZakrzewskaTrznadel G. Advances in membrane technologies for the treatment of liquid radioactive waste［J］. Desalination，2013，321(1)：119130.

［2］Ambashta R D, Sillanp M E T. Membrane purification in radioactive waste management: a short review［J］. Journal of Environmental Radioactivity，2012，105(1)：7684.

［3］孙东辉,韦葵子,杨沐.GB 9133—1995放射性废物分类［S］. 1995.

［4］Chmielewski A G, Harasimowicz M. Influence of gamma and electron irradiation on transport properties of nanofiltration and hyperfiltration membranes［J］. NukleonikaOriginal Edition，1997，42(1)：857862.

［5］Lin S H, Huang C U, Cheng M J. Optimization of multistage phenol adsorption by organobentonites: Theoretical developments and experimental verification［J］. Environmental Technology，2002，23(6)： 609622.

［6］Yaroshchuk A, MartínezLladó X, Llenas L, et al. Solutiondiffusionfilm model for the description of pressuredriven transmembrane transfer of electrolyte mixtures: One dominant salt and trace ions［J］. Journal of Membrane Science，2011，368(1)：192201.

［7］Hidalgo A M, León G, Gómez M, et al. Application of the solutiondiffusion model for the removal of atrazine using a nanofiltration membrane［J］. Desalination and Water Treatment，2013，51(1012)：22442252.

［8］Hung P V X, Cho S H, Moon S H. Prediction of boron transport through seawater reverse osmosis membranes using solutiondiffusion model［J］. Desalination，2009，247(1)：3344.

［9］Kesting R E. The four tiers of structure in integrally skinned phase inversion membranes and their relevance to the various separation regimes［J］. Journal of Applied Polymer Science, 1990, 41(1112)：27392752.

[1]	王聚团, 戚晓宁, 黄志明. 水下生产管汇测试技术及其改进研究[J]. 海洋工程装备与技术, 2022, 9(2): 43-49.
[2]	袁振钦, 邹科, 孙亚峰, 刘刚, 屈衍, 李居跃. 基于时域分析法的动态电缆疲劳分析[J]. 海洋工程装备与技术, 2022, 9(2): 50-55.
[3]	王娟, 杨明旺, 郑茂尧, 刘凌云, 赵立君. 高强钢在大型半潜式平台组块建造中的应用[J]. 海洋工程装备与技术, 2022, 9(1): 27-31.
[4]	陈欣, 赵晓磊, 王立坤, 肖德明, 张腾月. 深水大型吸力锚建造技术研究[J]. 海洋工程装备与技术, 2022, 9(1): 32-36.
[5]	尹彦坤, 易涤非. 半潜式生产平台船体结构关键节点工程临界评估[J]. 海洋工程装备与技术, 2022, 9(1): 52-57.
[6]	ZHANG Shengfa (张胜发), TANG Na (唐纳), SHEN Guofeng (沈国峰), WANG Han (王悍), QIAO Shan (乔杉). Universal Software Architecture of Magnetic Resonance-Guided Focused Ultrasound Surgery System and Experimental Study[J]. J Shanghai Jiaotong Univ Sci, 2021, 26(4): 471-481.
[7]	MA Qunsheng (马群圣), CEN Xingxing (岑星星), YUAN Junyi (袁骏毅), HOU Xumin (侯旭敏). Word Embedding Bootstrapped Deep Active Learning Method to Information Extraction on Chinese Electronic Medical Record[J]. J Shanghai Jiaotong Univ Sci, 2021, 26(4): 494-502.
[8]	安庆升, 孙立东, 武秋生. 碳纤维增强复合材料发射筒设计研究[J]. 空天防御, 2021, 4(2): 13-.
[9]	KONG Xiangqiang (孔祥强), MENG Xiangxi (孟祥熙), LI Jianbo (李见波), SHANG Yanping (尚燕平), CUI Fulin (崔福林) . Comparative Study on Two-Stage Absorption Refrigeration Systems with Different Working Pairs[J]. J Shanghai Jiaotong Univ Sci, 2021, 26(2): 155-162.
[10]	ZHUANG Weimin (庄蔚敏), WANG Pengyue (王鹏跃), AO Wenhong (熬文宏), CHEN Gang (陈刚) . Experiment and Simulation of Impact Response of Woven CFRP Laminates with Different Stacking Angles[J]. J Shanghai Jiaotong Univ Sci, 2021, 26(2): 218-230.
[11]	ZHOU Xuhui (周旭辉), ZHANG Wenguang (张文光), XIE Jie (谢颉). Effects of Micro-Milling and Laser Engraving on Processing Quality and Implantation Mechanics of PEG-Dexamethasone Coated Neural Probe[J]. J Shanghai Jiaotong Univ Sci, 2021, 26(1): 1-9.
[12]	HUANG Ningning (黄宁宁), MA Yixin (马艺馨), ZHANG Mingzhu (张明珠), GE Hao (葛浩), WU Huawei (吴华伟). Finite Element Modeling of Human Thorax Based on MRI Images for EIT Image Reconstruction[J]. J Shanghai Jiaotong Univ Sci, 2021, 26(1): 33-39.
[13]	WANG Xianjin, GAO Xu, YU Kuigang . Fixture Locating Modelling and Optimization Research of Aluminum Alloy Sidewall in a High-Speed Train Body[J]. J Shanghai Jiaotong Univ Sci, 2020, 25(6): 706-713.
[14]	QIAO Xing, MA Dan, YAO Xuliang, FENG Baolin. Stability and Numerical Analysis of a Standby System[J]. J Shanghai Jiaotong Univ Sci, 2020, 25(6): 769-778.
[15]	WU Jin, MIN Yu, YANG Xiaodie, MA Simin . Micro-Expression Recognition Algorithm Based on Information Entropy Feature[J]. Journal of Shanghai Jiao Tong University(Science), 2020, 25(5): 589-599.