Steady shearing flows of deformable, inelastic spheres
1Department of Civil and Environmental Engineering, Politecnico di Milano, 20133 Milano, Italy. diego.berzi@polimi.it.
Soft Matter
|May 16, 2015
Summary
This study extends kinetic theory for granular flows, incorporating particle interaction duration to model stresses beyond critical volume fractions. The new model accurately predicts stress components in various flow conditions, aligning with simulations and experiments.
Area of Science:
- Physics
- Mechanical Engineering
- Materials Science
Background:
- Granular flow models based on kinetic theory face challenges at high volume fractions.
- A critical volume fraction exists where rate-independent stress contributions emerge.
- Understanding stress evolution in dense granular media is crucial for engineering applications.
Purpose of the Study:
- To extend kinetic theory models for granular flows beyond the critical volume fraction.
- To incorporate particle interaction duration into stress calculations.
- To accurately predict stress components in both homogeneous and inhomogeneous granular flows.
Main Methods:
- Extended kinetic theory models for granular flows.
- Incorporated a measure of particle interaction duration before and after critical volume fraction.
- Developed a simple expression for collision duration to ensure smooth transitions between flow regimes.
- Applied the theory to steady, homogeneous, and inhomogeneous shearing flows.
Main Results:
- Stress components at low volume fractions are influenced by elastic collisions.
- At high volume fractions, stress includes static contributions from elasticity and dynamic contributions from force chain breakage.
- The extended model provides predictions in good agreement with numerical simulations for homogeneous flows.
- The theory successfully reproduces features of inhomogeneous flows observed in simulations and experiments.
Conclusions:
- The extended kinetic theory provides a unified framework for granular flow stress.
- The model captures the transition in stress behavior at critical volume fractions.
- This approach offers improved predictive capabilities for dense granular flows in diverse applications.
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