Mechanism-Based Upscaling of Particle Clogging in Porous Media: An Integrated Experimental and Numerical Approach

This thesis, Mechanism-Based Upscaling of Particle Clogging in Porous Media: An Integrated Experimental and Numerical Approach, investigates particle clogging in porous media using both experimental and modeling techniques. The goal is to develop a unified framework for observing clogging mechanisms at both the pore and sample scales, while enhancing the Pore Network Model (PNM) to improve clogging predictions. In Chapter 2, we introduced a custom-built microfluidic setup integrating Fluorescence Recovery After Photobleaching (FRAP) and pressure probing techniques to directly observe particle clogging dynamics. This setup allowed us to capture real-time particle movement, attachment, and clogging processes, while simultaneously measuring permeability changes. The findings revealed that hydrophobic particles exhibit higher attachment potentials, accelerating clogging and leading to pressure drops directly correlated with particle attachment. Chapter 3 explores the clogging behavior of bimodal particle mixtures in high-resolution microfluidic models mimicking paper coating structures. The study demonstrated that smaller particles cause greater permeability reduction by penetrating deeper into the porous network, while larger particles form filter cakes that enhance small particle retention. Notably, the wormholing phenomenon, where small particles bypass filter cakes, was observed and analyzed using FRAP techniques to track changes in flow paths and solute dispersion. Chapter 4 integrates particle clogging mechanisms into Pore Network Modeling (PNM) to simulate clogging dynamics in porous media. We established a deterministic criterion for throat clogging and updated conductance and connectivity rules to account for phenomena such as the decoupling of fluid and particle flux in clogged pores. The model effectively captured the exponential decline in permeability and flow alteration with particle accumulation, providing a robust framework for simulating clogging dynamics. In summary, this thesis provides a comprehensive understanding of particle clogging in porous media, offering novel experimental techniques and insights, as well as a refined PNM for simulating clogging behavior. The findings have implications for various applications, including filtration, well clogging, and inkjet printing, contributing to better clogging management and optimization strategies.