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Caliskan, Utkan

University of British Columbia

This research focuses on developing and validating a numerical model for dense particulate flow systems that consist of solid, liquid, and gas phases. The objective is to achieve a comprehensive understanding of the interplay between these phases, enhancing the accuracy and predictability of the model in simulating complex multiphase dynamics. The initial phase involves exploring the Multiphase Particle In Cell (MP-PIC) method, specifically for gas-solid systems like fluidized beds, and validating the model against NETL's SSCP-I fluidized bed data. The evaluation of liquid-gas-solid systems begins with the CFD-DEM-VOF model, known for its accuracy in particle dynamics and similar fluid coupling strategy to MP-PIC. This model is rigorously tested across various scenarios, predominantly in bulk particle water entry applications. Following this, similar validation procedures are applied to the MP-PIC-VOF model. A key advancement in these phases is the development of a tailored trilinear interpolation technique for unstructured hexahedral meshes, first implemented in the CFD-DEM-VOF model to enhance fluid-particle interaction accuracy. This technique is then successfully integrated into the MP-PIC-VOF model, that is also used in inter-particle stress gradient calculation. The consistent results across both models and their alignment with experimental data demonstrate the model development's effectiveness in simulating dense particle-laden free-surface flows. The research ultimately explores the challenges posed by flows with varied particle sizes and two distinct densities, termed polydisperse bi-density particle-laden free-surface flows. Such flows, especially with parts designed for particle retention (i.e. riffles), present unique challenges. To grasp these dynamics, both experimental studies and numerical simulations were employed, with a focus on particle segregation based on size and density. Gravitational and fluid-induced forces play roles in these segregations, particularly within riffles that tend to retain denser particles more effectively. The study integrates the latest development in MP-PIC, incorporating the Blended Acceleration Model (BAM) to improve predictions related to particle segregation. The model's applicability has been rigorously tested through comparisons with experimental data obtained from multiple different scenarious, especially observing interactions of denser and lighter particles in riffle settings. The validation study demonstrates reliable prediction of material retention, distribution profiles, and rejection patterns for both denser and lighter particles.

Text

2024-06-28

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/88532

Mining Engineering

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/