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Cross-flow and dead-end microfiltration of oily-water emulsions Part II. Mechanisms and modelling of flux decline

机译:油水乳状液的错流和死端微滤,第二部分。通量下降的机理和建模

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The focus of this paper is on the mechanisms and modelling of flux decline. Three distinct forms of modelling flux decline of cross flow filtration at constant transmembrane pressure (△P) were examined. The best fit to the data sets examined was obtained with the model developed previously by Field [9,l0]. The general equation is (dJ/dt) = -k_j(J-L~*)j~(2-n) where n depends upon the fouling mechanism and J~* is the steady-state flux. This approach to the analysis of flux data has the ability to identify the dominant mechanism, which has been shown to depend upon the membrane used and the operating conditions. In order not to give undue emphasis to early or late times, the data were fitted in both flux and resistance form simultaneously. The dominant fouling mechanism was found to be either incomplete pore blocking (n = l ) or 'cake' filtration (n = 0). Trends in the model parameters are also discussed in relation to operating conditions such as mode of filtration, cross-flow velocity and transmembrane pressure. For dead--end filtration, the initial rate of flux decline was found to be proportional to △P~3, as suggested by theory. The model of Wu et al. [ll] was shown to have limited predictive performance and discarded as being empirical. The model of Koltuniewicz [12] was shown to have limited application and unrealistic performance in this filtration application. The two most significant practical observations on the oily-water data are (l) the initial rate of fouling is significantly lower for cross-flow velocities of 0.8 ms~-l or greater and (2) a △P of l bar can lead to excessive fouling. With regard to microfiltration modelling generally, further comparison between the three models with other data sets is recommended.
机译:本文的重点是通量下降的机理和建模。考察了在恒定跨膜压力(△P)下错流过滤的三种不同形式的模型通量下降。使用Field [9,10]先前开发的模型可以获得与所检查数据集的最佳拟合。一般公式为(dJ / dt)= -k_j(J-L〜*)j〜(2-n),其中n取决于结垢机理,J〜*是稳态通量。这种分析通量数据的方法具有识别主要机理的能力,该机理已显示取决于所用的膜和操作条件。为了避免过早或过早地强调数据,将数据同时以磁通和电阻形式拟合。发现主要的结垢机制是不完全的孔堵塞(n = 1)或“滤饼”过滤(n = 0)。还讨论了与操作条件有关的模型参数趋势,例如过滤模式,错流速度和跨膜压力。对于死端过滤,理论上发现通量下降的初始速率与△P〜3成正比。吴等人的模型。 [11]被证明具有有限的预测性能,并作为经验被丢弃。 Koltuniewicz [12]的模型在这种过滤应用中显示出有限的应用和不切实际的性能。关于油水数据的两个最重要的实际观察结果是:(l)横流速度为0.8 ms〜-l或更高时,初始结垢率明显较低;(2)l bar的△P可能导致过多的污垢。一般而言,关于微滤模型,建议进一步比较这三个模型与其他数据集。

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