Filter Media for Protective Face Masks

Design, modelling, simulation and optimization with GeoDict 2022

In answering the global demand for safe personal protective equipment and the need for faster development and optimization of face masks, we demonstrate here how GeoDict software is applied to design, model, simulate, analyze and optimize the filter media to improve the filter characteristics of face masks.

The filtration characteristics of a filter depend mainly on its filter media. These macroscopic properties of the filter may be modified and improved by analyzing, understanding, and then optimizing the nano and/or microstructure of the filter media. Beside flow simulation at micro scale, Geodict is able to precisely simulate the flow through nano-fibrous media considering correctly the slip length.

What is the result of the simulations?

The end result is the identification of the best digital designs of filter media with the highest filtration efficiency and lowest pressure drop as well as the most economic design by saving in material.

What does this mean for you?

This unique digital workflow with GeoDict represents an efficient, sustainable and state-of-the-art methodology for digital R&D material design for porous media, explicitly shown here for a filter medium as an example.

Authors and application specialists

Dr.-Ing. Mehdi Azimian

Senior Business Manager
for Filtration

Dr. Philipp Eichheimer

Application Engineer &
Business Manager for Filtration

Approach to the Study

1. Image processing of the CT scans

In this case study, a 2-layer filter medium of an existing well-known surgical face mask was scanned by nano-CT with a resolution of 400 nm. The ImportGeo-Vol module of GeoDict was then used to import, process, and segment the scanned images.

2. Image analysis of the grayscale images

In the next step, the FiberFind module was used to analyze the gray-scale images and obtain relevant information about the fibers. With this information, the sample could be evaluated in regard to its geometrical characteristics such as fiber diameter, fiber orientation and curliness.

3. Simulation and Validation

Next, the filtration lifetime of the filter medium was simulated using the FilterDict module. The simulation results were compared and validated with the laboratory experiments performed by Berger et al. from Heilbronn University of Applied Sciences.

4. Optimization of the filter medium

For optimization of the filter medium, we focused on improving the fine layer of the filter medium. The reason is that the main filtration task and most of the pressure loss occurs in this specific layer. During this step, a large number of 3D digital prototypes were modeled and then simulated with GeoDict.

Such an extensive parameter study during this optimization is possible and expedient through the automation capabilities of the GeoDict software with Python scripts (GeoPy).

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The Conclusion from the Case Study

These reliable quantitative simulations are the way to a time and cost saving approach for the development of new filter materials and filters with superior lifetime and performance. Development phases can be significantly accelerated thanks to shortened development times. The innovations can be developed much more easily by obtaining digitally unique insights and rich information about material prototypes and their properties, even before manufacturing them.

GeoDict is being applied routinely by our customers for the design and improvement of their products. They benefit from a significant reduction in development time and cost to obtain improved materials for filtration applications.

Simulating with GeoDict not only saves time and money, but also empowers the development of tomorrow's innovations today in a sustainable and efficient way.

Service

Simulations in filtration

An overview of GeoDict solutions for diverse filtration applications.

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Acknowledgement

We thank our partners at Heilbronn University of Applied Sciences, Prof. Niessner and her team, for their excellent collaboration and for providing the experimental data.