Abstract

We investigate heat conduction rates through the contact network of sheared granular materials that consist of particles with a density much larger than that of the ambient fluid. The tool ParScale, a finite difference solver for intra-particle transport processes, is coupled to the discrete element method solver LIGGGHTS to carry out the simulations. Heat transfer to the surrounding fluid is considered via a fixed heat transfer coefficient. We identify a combination of Biot and Peclet number as the key non-dimensional influence parameter to describe the non-dimensional heat flux through the particle bed and provide an analytical solution to calculate mean particle temperature profiles. Simulations over a wide range of particle volume fractions, Biot and Peclet numbers are then performed in order to develop a continuum model for the heat flux. We show that for Biot numbers below 10^{-3} our results agree with a simple model based on a uniform particle temperature. However, for Biot numbers above a certain threshold, the conductive heat flux decreases substantially depending on the flow situation, and temperature gradients within the particle should be considered in order to correctly predict the heat transfer rate to the surrounding fluid.

Highlights

  • 14 Page 2 of 23Convection Conductive Drift value Normal direction Tangential direction Transferred Direction

  • The reliable prediction of local temperatures in reactors for, e.g., CO2 absorption, or biomass combustion is a research field of high interest

  • Since we focus on particle volume fractions with φp ≥ 0.50, all three flow regimes known from granular rheology can be identified: (i) an interial regime characterized by a quadratic increase of the conductive flux with the shear rate, (ii) a quasi-static regime where fluxes are independent of the shear rate, and (iii) an intermediate regime that is only relevant for very soft particles

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Summary

14 Page 2 of 23

Convection Conductive Drift value Normal direction Tangential direction Transferred Direction. Initial state Average value Bottom Critical value Characteristic value Contact points in system Cylinder Drift value Effective value Fluid Particle index Inertial int p QS top s vol x, y, z

Introduction
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Simulation method
Particle flow model
Transport within a particle
Governing equations
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Thermal fluxes
Dimensional analysis
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Effect of heat conduction within the particle
Analytical solution for heat conduction in a cooled particle bed
14 Page 10 of 23
Small Biot number limit
High Biot number limit
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Simple shear flow
Effect of particle stiffness on conductive fluxes
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Effect of the Peclet number and shear rate on convective fluxes
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Impact of the Biot number on conductive fluxes
Effect of the Peclet number on conductive flux at several Biot numbers
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Regimes of conductive heat transport
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Conclusions
Findings
Compliance with ethical standards
Full Text
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