Speaker
Description
Capillary flow through porous media plays a crucial role in applications ranging from material science to biological systems. We are interested in quantifying the effect of hydrophobic defects in a heterogeneous wetting problem, which can for example occur in powder processing problems for food technologies [1]. In real-world applications such as the one mentioned before, the amount and spatial position of these defects is highly uncertain and quantifying their effect on the functionality, i.e. wettability and wetting dynamics of the composite is crucial in the design process for such applications.
Our model is a revision of the classical problem of liquid imbibition in a single pore, focusing on spatially varying wettability of the pore surface. For single pores consisting of two different hydrophilic materials, we recently found [2] that the order of materials matters for the wetting dynamics, leading to the shortest wetting times, when the liquid first completely passes the less wettable material, followed by the material with higher wettability. Extending these results to cases, where the less wettable material is even hydrophobic comes along with new, interesting questions.
Firstly, in contrary to considering two hydrophilic materials, the presence of hydrophobic defects can lead to a complete stoppage of the capillary rise under certain critical conditions.
Secondly, the complex dynamics of the dynamic contact angle as well as free surface oscillations make it harder to develop macroscopic ODE models for the overall wetting dynamics, which are available for the case with two hydrophilic materials, at least under some assumptions [2,3].
For this reason, we need to rely on direct numerical simulations (DNS) of the capillary rise problem. Quantifying the effect of hydrophobic defects of unknown size distribution, number and position leads to a multidimensional forward UQ problem, so, regarding the computational expense of DNS simulations, classical sampling methods such as Monte Carlo quickly reach their limits. To circumvent this issue, we construct Polynomial Chaos-based surrogate responses to our simulations, subsequently enabling to define critical parameters for the wetting process under uncertain conditions. This ultimately aims at obtaining robust process designs in the numerous wetting-based technologies.
[1] J. Kammerhofer et al. (2018), Powder Technology, 328, 367-74
[2] M. Fricke, L. Gossel, J. De Coninck (2024), Optimizing Capillary Flow: The Role of Material Distribution in Fluid Transport, to be published.
[3] M. Fricke et al. (2023), Physica D: Nonlinear Phenomena, 455, 133895
