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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Pseudo-viscous modeling of transport in dense granular flows for thermal energy storage applications

Dense, granular flows were examined to effectively capture and model bulk viscous properties in thin packed beds. A modified Couette cell with particle image velocimetry was used to experimentally determine pseudo-viscosity properties of four particulate media with varying morphologies: (1) iron oxide-coated SiO 2 particles, (2) CARBOBEAD CP30-60 particles, (3) CARBOBEAD CP40-100 particles, and (4) Al 2 O 3 beads. The pseudo-viscosity functions were fitted using a power law to correlate the measured shear stress as a function of measured shear rate. The pseudo-viscous functions were used as inputs to computation fluid dynamics models for a single-phase viscous fluid to predict granular flow profiles. Steady-state free surface velocity profiles at angular velocities <7 rad/s predicted by the model were in good agreement with the experimental particle image velocimetry measurements, resulting in Pearson correlation coefficients of 0.97 for iron-oxide coated SiO 2 particles and 0.95 for CP30-60 particles. As a result, this alternative approach to measuring pseudo-viscous properties under shearing and modeling bulk transport behavior of granular flow using computation fluid dynamics model offered significant reduction in computational load compared to discrete element methods.

14 SOLAR ENERGY↗
DOE OSTI2025

An adaptive, data-driven multiscale approach for dense granular flows

The accuracy of coarse-grained continuum models of dense granular flows is limited by the lack of high-fidelity closure models for granular rheology. One approach to addressing this issue, referred to as the hierarchical multiscale method, is to use a high-fidelity fine-grained model to compute the closure terms needed by the coarse-grained model. The difficulty with this approach is that the overall model can become computationally intractable due to the high computational cost of the high-fidelity model. In this work, we describe a multiscale modeling approach for dense granular flows that utilizes neural networks trained using high-fidelity discrete element method (DEM) simulations to approximate the constitutive granular rheology for a continuum incompressible flow model. Our approach leverages an ensemble of neural networks to estimate predictive uncertainty that allows us to determine whether the rheology at a given point is accurately represented by the neural network model. Additional DEM simulations are only performed when needed, minimizing the number of additional DEM simulations required when updating the rheology. This adaptive coupling significantly reduces the overall computational cost of the approach while controlling the error. In addition, the neural networks are customized to learn regularized rheological behavior to ensure well-posedness of the continuum solution. We first validate the approach using two-dimensional steady-state and decelerating inclined flows. We then demonstrate the efficiency of our approach by modeling three-dimensional sub-aerial granular column collapse for varying initial column aspect ratios, where our multiscale method compares well with the computationally expensive computational fluid dynamics (CFD)-DEM simulation.

Dense granular flows↗
DOE OSTI2025

Dense granular flows with MFIX-Exa

This report extends the linear spring dashpot collision model the discrete element method available in MFIX-Exa to include static a static tangential friction force. Additionally, two rolling friction models frequently used in the literature are also implemented. The governing equations are provided with an emphasis on the new terms. The new model is validated by comparison to existing experimental data of single particle oblique collisions. The model is then tested on three dense granular flow problems: the formation of static piles, the discharge from a flat-bottom hopper and the self-induced granular Rayleigh-Taylor instability.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Heat transfer coefficients of moving particle beds from flow-dependent thermal conductivity and near-wall resistance

Accurate determination of heat transfer coefficients for flowing packed particle beds is essential to the design of particle heat exchangers and other thermal and thermochemical equipment. While such dense granular flows mostly fall into the well-known plug-flow regime, the discrete nature of granular materials alters the thermal transport processes in both the near-wall and bulk regions of flowing particle beds from their stationary counterparts. As a result, heat transfer correlations based on the stationary particle bed thermal conductivity could be inadequate for flowing particles in a heat exchanger. Most earlier works have achieved a reasonable agreement with experiments by treating granular heat transfer media as a plug-flow continuum with a near-wall thermal resistance in series. However, the thermal conductivity values of the continuum were often obtained from measurements on stationary beds owing to the difficulty of flowing bed measurements. In this work, it was found that the properties of a stationary bed are highly sensitive to the method of particle packing and there is a decrease in the particle bed thermal conductivity and increase in the near-wall thermal resistance, measured as an effective air gap thickness, on the onset of particle flow. These variations in thermal conductivity of stationary and flowing particle beds can lead to errors in heat transfer coefficient calculations. Therefore, the heat transfer coefficients for granular flows were calculated using experimentally determined flowing particle bed thermal conductivity and near-wall air gap for ceramic particles – CARBO CP 40/100 (mean diameter = 275 µm), HSP 40/70 (404 µm) and HSP 16/30 (956 µm); at velocities of 5–15 mm·s –1 ; and temperatures of 300–650 °C. The thermal conductivity and air gap values for CP 40/100 and HSP 40/70 were further used to calculate heat transfer coefficients across different particle bed temperatures and velocities for different parallel-plate heat exchanger dimensions. Furthermore, these calculations, which show good agreement with measured HTC values reported in literature, can be used as a guide for heat exchanger designs. Graphical abstract

14 SOLAR ENERGY↗