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| 1 | 亚硫酸亚铁铵沉淀法去除高浓度氨氮的反应特性及工艺研究显示文摘首次报道了采用亚硫酸亚铁铵沉淀法去除高浓度氨氮废水。系统地研究了该方法的反应过程特性、产物纯度及溶解度特征,同时研究了影响氨氮脱除效率的工艺参数(反应初始pH、药剂量、反应温度)。结果表明:亚硫酸亚铁铵法去除氨氮的反应过程呈两阶段变化,在pH为6,加药量n(NH_(4)^(+))∶n(Fe^(2+))∶n(SO_(3)^(2-))为0.5∶1∶1,反应温度为25℃时,可实现氨氮浓度为14000 mg/L的模拟废水的去除88.04%氨氮,并以高纯度的亚硫酸亚铁铵结晶回收。另外,该反应能在氧气气氛下发生,且不能影响反应效率。 | 杨本涛 杨燿华 刘彦廷 陈跃辉 贺颖捷 叶恒棣 | 2023 | 水处理技术2023，49，8： | 0 |
| 2 | Asynchronous Fuzzy Cognitive Networks Modeling and Control for Goethite Iron Precipitation Process显示文摘Goethite iron precipitation process is a key step in direct leaching process of zinc,whose aim is to remove ferrous ions from zinc sulphate solution.The process consists of several cascade reactors,and each of them contains complex chemical reactions featured by strong nonlinearity and large time delay.Therefore,it is hard to build up an accurate mathematical model to describe the dynamic changes in the process.In this paper,by studying the mechanism of these reactions and combining historical data and expert experience,the modeling method called asynchronous fuzzy cognitive networks(AFCN)is proposed to solve the various time delay problem.Moreover,the corresponding AFCN model for goethite iron precipitation process is established.To control the process according to fuzzy rules,the nonlinear Hebbian learning algorithm(NHL)terminal constraints is firstly adopted for weights learning.Then the model parameters of equilibrium intervals corresponding to different operating conditions can be calculated.Finally,the matrix meeting the expected value and the weight value of steady states is stored into fuzzy rules as prior knowledge.The simulation shows that the AFCN model for goethite iron precipitation process could precisely describe the dynamic changes in the system,and verifies the superiority of control method based on fuzzy rules. | CHEN Ning PENG Junjie GUI Weihua ZHOU Jiaqi DAI Jiayang | 2020 | Journal of Systems Science & Complexity2020，33，5： | 0 |
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