Modeling of Delayed Desorption in Activated Carbon Filter Systems for Air Purification Applications.
Activated carbon filtration has proven to be a reliable method to clean indoor air. In such a system, air, contaminated with VOCs, is led through the filter where the contaminants are adsorbed onto the filter. However, for the long term stability of the air purification system, it is necessary that the filter is regenerated by releasing the adsorbed contaminants to be further degraded. This can be done by increasing the temperature of the system and thus promoting desorption of the contaminants.
This work showcases the use of COMSOL Multiphysics® to model the delayed desorption of volatile organic compounds (VOCs) on an activated carbon filter (ACF). The ACF is modeled as a porous domain. The air flow through the reactor is modeled with the free and porous media flow module. The air flow is then used as input to model the transport of VOCs through the reactor with the transport of diluted species in porous media interface. Appropriate kinetic rate expressions to account for adsorption and desorption are introduced as sink and source terms in the transport equations of the bulk and adsorbed species. Through experimental results, the adsorption and desorption constants will then be optimized with the optimization module.
To be able to account for the delayed desorption, the kinetic constants are made time dependent. In this way, the model will mimic the real system where desorption occurs because of an increased temperature over time. In the future, the model will be extended such that the kinetic constants are dependent only on temperature instead of time. By utilizing COMSOL Multiphysics®, deeper insights into the effect of temperature on the adsorption/desorption behavior of ACFs can be gained. Additionally the model can then be coupled to other air purification models to account for the full degradation of VOCs. And finally, through the results of the model, substantiated suggestions can be made to improve reactor performance and predict energy consumption in the future.
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