Fibrous depth filters are frequently used for the purification of gas streams with low dust loadings, as well as processes where a high initial filtration efficiency is required (e.g., clean rooms for aseptic production). One tool suitable for supporting the development of optimized filter media is the use of numerical simulations. The drawback of this technique is the high computational resources required. In this work, a new and fast approach based on a one-dimensional model was applied. Structural characteristics (e.g., porosity distribution and fiber diameter) of two different filter media were successfully determined using a novel X-ray microscope. These characteristics were incorporated in the filtration model, and their influence on the calculations was evaluated. It was found that the porosity distribution does have an impact on local (microscopic) deposition rates, but only a minor influence on the macroscopic filtration efficiency (around 3%). Benefits of the model are the application of measured structural data and the low computational expense. Compared to experimental data (VDI 3926 / ISO 11057), the prediction of the filtration efficiency can be improved by incorporating the structural data in the model.
Depth filtration is a widespread technique for the separation of airborne particles. The evolution of the pressure difference within this process is determined to a significant extent by the filter structure. Simulations are an important tool for optimizing the filter structure, allowing the development of filter materials having high filtration efficiencies and low pressure differences. Because of the large number of physical phenomena and the complex structure of filter materials, simulations of the filtration kinetics are, however, challenging. In this context, one-dimensional models are advantageous for the calculation of the filtration kinetics of depth filters, due to their low computation requirements. In this work, an approach for combining a one-dimensional model with microstructural data of filter materials is presented. This enables more realistic modeling of the filtration process. Calculations were performed on a macroscopic as well as microscopic level and compared to experimental data. With the suggested approach, the influence of a measured microstructure on the results was examined and predictability was improved. Especially for small research departments and for the development of optimized filter materials adapted to specific separation tasks, this approach provides a valuable tool.
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