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Research Articles

Scale transition: Pore network study of how pore structure affects the macroscopic parameters of the continuum model for drying

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Pages 948-967 | Received 31 Dec 2022, Accepted 17 Mar 2023, Published online: 31 Mar 2023
 

Abstract

The scale transition from discrete pore network model (PNM) simulations to one-equation continuum model (CM) of drying has been investigated in previous studies for uniformly structured porous media. This investigation is extended in the present work to porous media with widely different pore size distributions, as well as to those with spatially correlated networks of small and large pores. The key questions examined here are how and to what extent pore-structural features can be reflected in the local macroscopic parameters of the one-equation CM derived by traditional homogenization. For this purpose, three-dimensional model capillary structures with monomodal and bimodal pore size distributions are generated and drying simulations are conducted at the limit of viscous-capillary dominated regime. By leveraging volume-averaged data obtained from PNM simulations the one-equation CM is parameterized and thus its local parameters are expressed in dependence on the pore structure. The simulation results show that for the monomodal and bimodal pore structures the profiles of the moisture transport coefficients are complex and non-unique over the entire drying process. Moreover, the deviation of the water vapor partial pressure from the saturation vapor pressure in the presence of liquid water – which is referred to as non-local equilibrium effect – is less pronounced for the bimodal pore structure compared to the monomodal pore structures. Finally, comparisons are performed between the volume-averaged data obtained at different stages of drying by the discrete simulations with monomodal and bimodal pore structures and results of the continuum model of drying.

Disclosure of interest statement

The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper.

Additional information

Funding

Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project-ID 422037413 – TRR 287.

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