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Predicting the Hydraulic Conductivity of Metallic Iron Filters: Modeling Gone Astray

机译:预测金属铁过滤器的水力传导率:模拟失误模型

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Since its introduction about 25 years ago, metallic iron (Fe 0 ) has shown its potential as the key component of reactive filtration systems for contaminant removal in polluted waters. Technical applications of such systems can be enhanced by numerical simulation of a filter design to improve, e.g., the service time or the minimum permeability of a prospected system to warrant the required output water quality. This communication discusses the relevant input quantities into such a simulation model, illustrates the possible simplifications and identifies the lack of relevant thermodynamic and kinetic data. As a result, necessary steps are outlined that may improve the numerical simulation and, consequently, the technical design of Fe 0 filters. Following a general overview on the key reactions in a Fe 0 system, the importance of iron corrosion kinetics is illustrated. Iron corrosion kinetics, expressed as a rate constant k iron , determines both the removal rate of contaminants and the average permeability loss of the filter system. While the relevance of a reasonable estimate of k iron is thus obvious, information is scarce. As a conclusion, systematic experiments for the determination of k iron values are suggested to improve the database of this key input parameter to Fe 0 filters.
机译:自大约25年前问世以来,金属铁(Fe 0)已显示出其作为反应过滤系统中用于去除污水中污染物的关键成分的潜力。这种系统的技术应用可以通过过滤器设计的数值模拟来改进,以改善例如使用寿命或预期系统的最小渗透率,以保证所需的出水水质。该交流讨论了在这种仿真模型中的相关输入量,说明了可能的简化方式,并确定了缺少相关的热力学和动力学数据。结果,概述了必要的步骤,这些步骤可以改善数值模拟,从而改善Fe 0滤波器的技术设计。在对Fe 0系统中关键反应的一般概述之后,说明了铁腐蚀动力学的重要性。铁腐蚀动力学,用速率常数k iron表示,既决定了污染物的去除率,又决定了过滤系统的平均渗透率损失。因此,显然可以合理地估计出k铁的相关性,但缺乏信息。总之,建议进行系统的实验以确定k个铁含量,以改善该关键输入参数到Fe 0过滤器的数据库。

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