Modeling Phase Separation in Grain‐Fluid Mixture Flows by a Depth‐Averaged Approach With Dilatancy Effects

In this work, we propose a comprehensive two‐layer depth‐averaged model to study the dynamic behavior of grain‐fluid mixtures, which considers the granular dilatancy effects and the different frictional rheologies of grains in different states. Unlike single‐phase flows, not only the interaction between granular and fluid phases significantly influence the dynamics of mixtures, but also the phase separation, so that different flow regimes can occur. These include five different possible regimes: two‐layer regimes of (a) under‐saturated mixture and (b) over‐saturated mixture as well as single‐layer regimes of (c) saturated mixture, (d) pure grains and (e) pure fluid. Most depth‐averaged models in previous studies have considered only one of these flow regimes. The present model is an improved and integrated version of these depth‐averaged models. Taking into account that the pure grains and pure fluid in the upper layer, which occur in the regimes of the under‐saturated and over‐saturated grain‐fluid mixtures, respectively, exhibit different flow features than in the lower layer of the saturated mixture, we use a two‐phase two‐layer depth‐averaged model to describe these regimes. This proposed model is possibly the first to employ a two‐layer structure to describe all possible different flow regimes simultaneously. The proposed model is then solved numerically using a high‐resolution central‐upwind scheme and shows its ability to handle different flow regimes. To demonstrate the robustness of the numerical implementation and to evaluate the performance of the model, the numerical results are compared with several experiments reported in the literature, showing a certain qualitative agreement.

Publication Details

Journal
TUbilio (Technical University of Darmstadt)
Published
2025-01-01
DOI
https://doi.org/10.26083/tuprints-00029025
Primary Topic
Granular flow and fluidized beds
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Modeling Phase Separation in Grain‐Fluid Mixture Flows by a Depth‐Averaged Approach With Dilatancy Effects

TUbilio (Technical University of Darmstadt)
Granular flow and fluidized beds
article

Modeling Phase Separation in Grain‐Fluid Mixture Flows by a Depth‐Averaged Approach With Dilatancy Effects

article en

Abstract

In this work, we propose a comprehensive two‐layer depth‐averaged model to study the dynamic behavior of grain‐fluid mixtures, which considers the granular dilatancy effects and the different frictional rheologies of grains in different states. Unlike single‐phase flows, not only the interaction between granular and fluid phases significantly influence the dynamics of mixtures, but also the phase separation, so that different flow regimes can occur. These include five different possible regimes: two‐layer regimes of (a) under‐saturated mixture and (b) over‐saturated mixture as well as single‐layer regimes of (c) saturated mixture, (d) pure grains and (e) pure fluid. Most depth‐averaged models in previous studies have considered only one of these flow regimes. The present model is an improved and integrated version of these depth‐averaged models. Taking into account that the pure grains and pure fluid in the upper layer, which occur in the regimes of the under‐saturated and over‐saturated grain‐fluid mixtures, respectively, exhibit different flow features than in the lower layer of the saturated mixture, we use a two‐phase two‐layer depth‐averaged model to describe these regimes. This proposed model is possibly the first to employ a two‐layer structure to describe all possible different flow regimes simultaneously. The proposed model is then solved numerically using a high‐resolution central‐upwind scheme and shows its ability to handle different flow regimes. To demonstrate the robustness of the numerical implementation and to evaluate the performance of the model, the numerical results are compared with several experiments reported in the literature, showing a certain qualitative agreement.

TUbilio (Technical University of Darmstadt)
Openalex Percentile: Top 58%
Granular flow and fluidized beds
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.