The protection factor and pressure drop coefficient of single layers of active carbon particles in chemical, biological, radiological, and nuclear (CBRN) protective garments have been computed from computational fluid dynamics simulations of airflow and mass transport. Based on the results from the simulations, a closed-form analytical model has been proposed for the protection factor and the pressure drop coefficient as a function of layer porosity, particle diameter, and cross airflow velocity. This model has been validated against experimental data in literature. It can be used to find an optimal compromise between high protection factor and low pressure drop coefficient. Maximum protection factors are achieved when small carbon particles are employed in a layer with high packing density, at the expense of a high pressure drop coefficient. For a given required protection factor, the lowest pressure drop coefficient is found for layers combining a high porosity and small particle diameter.
In chemical, biological, radiological, and nuclear protective clothing, a layer of activated carbon material in between two textile layers provides protection against hazardous gases. A cylinder in cross flow, sheathed by such material, is generally used to experimentally test the garment properties. This is, however, complicated and predictive models are needed. We present a computational fluid dynamics model for the initial phase in which the carbon filter material is not yet saturated. The textiles are modeled as chemically inactive porous layers, the carbon filter particles have been resolved explicitly. The model has been validated against experimental data. We demonstrate that (1) computational fluid dynamics simulations can be used for the efficient design and optimization of protective garments, and (2) the addition of a highly porous active carbon layer highly increases the chemical protection capabilities, while having relatively little negative impact on the thermal comfort of protective garments.
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