arXiv subjects

Soniya Kumawat

Publications and source records attributed to Soniya Kumawat.

6 recordsLinked to original sources

arXiv2026

Intercoupling of Segregation and Rheology in Spatially Developing Granular Chute Flows

We investigate the flow and segregation of binary granular mixtures with density differences down a long chute using a continuum framework that couples a particle-force-based segregation model with an inertial-number-based local rheology. The steady-state momentum and convection-diffusion-segregation equations are solved simultaneously, explicitly accounting for the two-way coupling between segregation and flow. Predicted concentration and velocity fields at different streamwise locations are validated against representative DEM simulations. The validated model is then used to examine the influence of density ratio, mixture composition, and chute inclination on segregation over a wide range of conditions. The chute length required to achieve fully developed segregation is quantified and compared with the development length for monodisperse granular flow. At low density ratios and/or low inclinations, segregation develops over much longer distances than the velocity field. In contrast, at higher inclinations and larger density contrasts, the two length scales become comparable, demonstrating that neglecting flow development can significantly underestimate segregation evolution.

cond-mat.soft↗

arXiv2026

Particle Force-Based Continuum Model for Multicomponent Size Segregating Mixtures

We investigate size difference driven segregation in dense granular flows of multicomponent mixtures down a periodic chute using continuum model and Discrete Element Method (DEM) simulations. A previously developed particle force-based segregation model for binary mixtures is systematically extended to mixtures comprising three or more particle species differing in size. The generalized model accounts for inter-species interactions by computing the net force on each component in the presence of all others, without relying on empirical percolation velocity. This segregation model is coupled with a mixture rheology model and incorporated into the species transport and momentum balance equations to develop a continuum model that predicts the spatial and temporal evolution of species concentration and velocity fields. The continuum model predictions are found to be in agreement with DEM simulation data for ternary and quaternary mixtures over a wide range of mixture compositions and chute inclinations at moderate size ratios for well-mixed and small-near-base configurations. For larger size ratios, the one dimensional model predictions capture the qualitative segregation trend while showing relatively larger quantitative differences from DEM data. For an initial configuration, having large particles near base and small particles near the free surface, a Rayleigh-Taylor like instability at early times is observed. Due to the presence of this instability, two dimensional evolution of the species concentration fields is present for initial part of the flow. Predictions of such features requires the extension of the one dimensional continuum model to two dimensions.

cond-mat.soft↗

arXiv2025

Transient segregation of bi-disperse granular mixtures in a periodic chute flow

Transient size segregation of a bi-disperse granular mixture flowing over a periodic chute is studied using the Discrete Element Method and continuum simulations. A recently developed particle force-based size segregation model is used to predict the time-dependent flow properties of binary mixtures starting from rest. A two-way coupled continuum model that solves the momentum balance and convection-diffusion equations by incorporating the mixture segregation model along with the generalized inertial number-based rheological model is developed for predicting the evolution of segregation. The predicted concentration profiles and other flow properties of the mixture are found to be in good agreement with the DEM data for a variety of compositions. The evolution of the centre of mass of the two species with time is also very well captured for different initial configurations and size ratios using the particle force-based segregation model.

cond-mat.soft↗

arXiv2025

Transient size segregation of binary granular mixtures

Transient size segregation of a bi-disperse granular mixture flowing over a periodic chute is studied using DEM simulations and theory. A recently developed particle force-based size segregation model has been shown to successfully predict the steady state behavior of binary granular mixtures [1]. This promising model is used to predict the time-dependent segregation of different size binary mixtures in this work. A one dimensional continuum model is developed to solve the convection-diffusion equation by incorporating a mixture segregation model along with rheological model. The inter-coupling of segregation with rheology is accounted to predict evolution of species concentration. We also investigate the effect of different initial configurations (Large near base (LNB), Small near base (SNB) and well-mixed) on the transient evolution of the flow and segregation. The particle force-based segregation model is able to predict the evolution of the concentration profile for all three initial configurations for smallest size ratio of 1.25. Significant deviations, however, are observable for larger size ratios, suggesting the need to account for the evolution of the velocity field in the model.

cond-mat.soft↗

arXiv2024

Transient segregation of different density granular mixtures

We study time-dependent density segregation of granular mixtures flowing over an inclined plane. Discrete Element Method (DEM) simulations in a periodic box are performed for granular mixtures of same size and different density particles flowing under the influence of gravity. In addition, a continuum model is developed to solve the momentum balance equations along with species transport equation by accounting for the inter-coupling of segregation and rheology. The particle force-based density segregation theory has been used along with the $μ-I$ rheology to predict evolution of flow properties with time for binary and multicomponent mixtures. The effect of particle arrangements on the transient evolution of flow properties for three different initial configurations is investigated using both continuum and DEM simulations. Continuum predictions for various flow properties of interest such as species concentration, velocity, pressure, and shear stress at different time instants are compared with DEM simulations. The results from the discrete and continuum models are found to be in good agreement with each other for well-mixed and heavy-near-base initial configurations. However, the continuum model is unable to predict the flow evolution for the light-near-base initial configuration. DEM simulations reveal the presence of an instability driven, quick segregation for this configuration which is not predicted by the one dimensional model and requires generalization to three dimensions.

cond-mat.soft↗

arXiv2023

Comparison of empirical and particle force-based density segregation models

The empirical and particle force-based models of granular segregation due to density differences among the species are compared in this work. Dependency of the empirical segregation parameters on the initial configuration, the observation time duration, inclination angle, and mixture composition are discussed in detail. The parameters obtained from empirical models are used to predict the steady-state concentration profiles for different density ratios and compositions. In addition, we utilize the predictions from the particle force-based segregation model and compare them with the predictions of the empirical segregation models. Our results show that the linear empirical segregation model predictions agree well with the simulation results for mixtures rich in light species where as quadratic empirical segregation model works better for mixtures rich in heavy species. Particle force-based segregation model, on the other hand, seems to be in very good agreement with the DEM simulation data across all mixture compositions.

cond-mat.soft↗