Stability of highly soluble ferrocyanides at neutral pH for energy-dense flow batteries
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25 ENERGY STORAGE↗
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Modular dimerization of organic radicals for stable and dense flow battery catholyte
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Energy & Fuels↗
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↗
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↗
Viscometric flow of dense granular materials under controlled pressure and shear stress
This study examines the flow of dense granular materials under external shear stress and pressure using discrete element method simulations. In this method, the material is allowed to strain along all periodic directions and adapt its solid volume fraction in response to an imbalance between the internal state of stress and the external applied stress. By systematically varying the external shear stress and pressure, the steady rheological response is simulated for: (1) rate-independent quasi-static flow; and (2) rate-dependent inertial flow. The simulated flow is viscometric with non-negligible first and second normal stress differences. While both normal stress differences are negative in inertial flows, the first normal stress difference switches from negative to slightly positive, and second normal stress difference tends to zero in quasi-static flows. The first normal stress difference emerges from a lack of coaxiality between a second-rank contact fabric tensor and strain rate tensor in the flow plane, while the second normal stress difference is linked to an excess of contacts in the shear plane compared with the vorticity direction. A general rheological model of second order (in terms of strain rate tensor) is proposed to describe the two types of flow, and the model is calibrated for various values of interparticle friction from simulations on nearly monodisperse spheres. The model incorporates normal stress differences in both regimes of flow and provides a complete viscometric description of steady dense granular flows.
42 ENGINEERING↗
Measurement of flow properties coupled to experimental and numerical analyses of dense, granular flows for solar thermal energy storage
Granular flows of sintered bauxite proppants were researched along an inclined plane for solar thermal energy storage applications. Granular flow properties needed to drive numeric granular models were measured for improved numerical model predictions for Carbobead CP 50/140, 40/100, and 30/60 particles. Particle shape and size distributions were determined by coupling optical microscopy to an in-house image processing algorithm. The impulse excitation technique was used to measure elastic and shear moduli, and compute Poisson’s ratio. The coefficient of static sliding friction was measured using the slip-stick method, and the static rolling friction was determined from measured shear on particles positioned between two hot-pressed plates. The coefficient of restitution was measured by dropping particles on a surface and determining the kinetic energy before and after impact with the surface using high resolution particle tracking velocimetry. Particle size did not significantly impact the coefficients of restitution and static rolling friction, however, particle shape distribution resulted in a large variation in measurements. An inclined flow experiment was performed to characterize granular flows of Carbobead CP 30/60 particles using particle image velocimetry. Numerical models of the experiment using discrete element method were generated with the measured mechanical properties as inputs for comparison with experimental results. A constant directional torque rolling friction model best predicted bulk granular flow behavior. Furthermore, good agreement between the model and experiment was achieved at ambient, steady state conditions, with average velocity differences <10%.
14 SOLAR ENERGY↗
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↗
Modeling Dense Particle Flow in Multistage and Obstructed Flow Receivers Using High Fidelity Simulations
Particles are a leading contender for next-generation, concentrating solar power technologies, and the design of the particle receiver is critical to minimize the levelized cost of electricity. Falling particle receivers (FPRs) are a viable receiver concept, but many new designs feature complex particle obstructions that include dense discrete phase flows. This creates additional challenges for modeling as particle-to-particle interactions (i.e., collisions) and particle drag become more complex. To improve upon existing modeling strategies, a CFD-DEM simulation capability was created by coupling two independent codes: Sierra/Fuego and LAMMPS. A suitable receiver model was then defined using a traditional continuum-based model for the air and a granular model for the particle curtain. A sensitivity study was executed using this model to determine the relevance of different granular model inputs on important quantities of interest in obstructed flow FPRs: the particle velocity and curtain opacity. The study showed that the granular model inputs had little effect on the particle velocity magnitude and curtain opacity after an obstruction.
Mills, Brantley↗
Shear rate dependency on flowing granular biomass material
The commercialization of bioenergy has been significantly limited by various material handling issues due to the poor flowability of granular biomass materials. A good understanding of flow physics and robust constitutive models to predict flow behavior across multiple regimes are essential to address these issues. In this study, we investigated the multi-regime flow behavior of loblolly pine chips, a widely used bioenergy feedstock, through comprehensive inclined plane flow experiments and simulations. A quasi-static hypoplastic model and a cross-regime Drucker-Prager-µ(I) model were calibrated and validated against the physical experiments to investigate the quasi-static and dense flow behavior. The results show that for granular biomass, 1) plane flow (iso-thickness along the plane) exists within a smaller range of inclination while heap flow (varying thickness along the plane) exists within a broader range of inclination, as compared with conventional granular materials (e.g., glass beads); 2) the scaling law of granular biomass flowing on an inclined plane (Froude Number versus dimensionless thickness) forms a bi-linear trend with the turning point governed by the quasi-static and dense flow regimes; 3) the multi-regime DP-µ(I) model can capture the flow behavior in both regimes well at the cost of extra calibration. In conclusion, these findings advance the scientific understanding of the multi-regime flow behavior of granular biomass materials and shed light on formulating novel constitutive models to assist granular biomass handling in the bioenergy industry.
09 BIOMASS FUELS↗
Multielectron Organic Redoxmers for Energy-Dense Redox Flow Batteries
Redox flow battery is a highly promising stationary energy storage method but the limited energy density and high chemical cost are among the main barriers for commercialization. Multi-electron organic redoxmers represent a family of structurally tailorable candidates that can achieve multiplied energy density with decreased materials consumption, potentially resulting in a viable solution to address these challenges. In this work, the recent development of organic molecules with reversible multi-redox activities in both aqueous and nonaqueous electrolytes is reviewed. The major focus is on the fundamental correlation between the chemical structures and the functional properties of reported multi-electron organic molecules. Valuable insights are offered on rational structural design strategies for improving the relevant physico- and electro-chemical properties. Finally, the current challenges are discussed to suggest future research needs along the avenue of using the multi-electron approach to achieve energy-dense, stable, cost-effective redox flow batteries.
25 ENERGY STORAGE↗
A scale-wise analysis of intermittent momentum transport in dense canopy flows
We investigate the intermittent dynamics of momentum transport and its underlying time scales in the near-wall region of the neutrally stratified atmospheric boundary layer in the presence of a vegetation canopy. This is achieved through an empirical analysis of the persistence time scales (periods between successive zero-crossings) of momentum flux events, and their connection to the ejection–sweep cycle. Using high-frequency measurements from the GoAmazon campaign, spanning multiple heights within and above a dense canopy, the analysis suggests that, when the persistence time scales ( $t_p$ ) of momentum flux events from four different quadrants are separately normalized by $\varGamma _{w}$ (integral time scale of the vertical velocity), their distributions $P(t_p/\varGamma _{w})$ remain height-invariant. This result points to a persistent memory imposed by canopy-induced coherent structures, and to their role as an efficient momentum-transporting mechanism between the canopy airspace and the region immediately above. Moreover, $P(t_p/\varGamma _{w})$ exhibits a power-law scaling at times $t_{p}<\varGamma _{w}$ , with an exponential tail appearing for $t_{p} \geq \varGamma _{w}$ . By separating the flux events based on $t_p$ , we discover that around 80 % of the momentum is transported through the long-lived events ( $t_{p} \geq \varGamma _{w}$ ) at heights immediately above the canopy, while the short-lived ones ( $t_{p} < \varGamma _{w}$ ) only contribute marginally ( $\approx 20\,\%$ ). To explain the role of instantaneous flux amplitudes in momentum transport, we compare the measurements with newly developed surrogate data and establish that the range of time scales involved with amplitude variations in the fluxes tends to increase as one transitions from within to above the canopy.
Mechanics↗
Numerical analyses of high temperature dense, granular flows coupled to high temperature flow property measurements for solar thermal energy storage
High temperature particle flow properties necessary to predict granular flow behavior for solar thermal energy storage applications were measured and calculated for Carbobead CP 30/60 up to 800 °C. Here, the measured properties included elastic and shear moduli, particle-particle coefficients of static sliding and rolling friction, and particle-particle coefficients of restitution. Poisson’s ratio was calculated with elastic and shear moduli. The flow properties were used as inputs for a numerical model using the discrete element method to examine granular flows along an inclined plane at high temperature. The flow behavior was strongly influenced by the coefficients of static friction, which impacted the particle residence time, shear effects from the side walls, and particle flow mass flux. An 8.7%, 15.6%, and 8.5% increase and 37.9% decrease in steady state mass flow rate was observed for 200 °C, 400 °C, 600 °C, and 800 °C, respectively, when compared to room temperature simulations. A 52%, 59%, and 33% decrease in the time to reach steady state was observed for 200 °C, 400 °C, and 600 °C, respectively, while a 53% increase in time was observed for 800 °C. A significant delay in the flow development at 800 °C was observed due to significantly higher frictional forces.
14 SOLAR ENERGY↗
The Development of a Generalized Riser Flow Regime Map Based Upon Higher Moment and Chaotic Statistics Using Electrical Capacitance Volume Tomography (ECVT)
Dynamic analyses have been applied to the temporal signals from an Electro Capacitance Volume Tomography instrument located near mid-height on the riser of an industrial-scale cold-flow circulating fluidized bed to characterize gas-solids flow behavior in the riser. Twelve capacitance electrodes surround the cylindrical riser over a height of 1.3 m. The instrument used a neural network deconvolution algorithm to determine the spatially resolved solids fraction recorded at 52 Hz. Experiments were carried out over a range of gas and solids flows in the transport regime using a Geldart Group B bed material, high density polyethylene with mean particle size of 880 μm. The radial solids distribution was found to vary from one-time step to the next between profiles typical of laminar and turbulent flow. The duration of time spent in each of these flow profiles depended upon the operating regime – dilute, core-annular, or fast fluidized bed. The chaotic structure of the temporal data was characterized using the three conventional approaches: the first 4 moments from the distribution of signal in time, system memory parameters from the autocorrelation function and the Hurst exponent, and analysis of the correlationentropy and correlation dimension of the attractor. These signal analysis techniques were used to clearly distinguish differences between different transport operating regimes. Specifically, it was experimentally observed that a riser transitions from core annular flow profile to dilute and dense regimes via increasing the frequency of short term transients to either dilute or dense flow profiles, respectively. A regime map was generated based upon these dynamics using solids flux and gas velocity axes. Fast fluidized, core annular, and dilute each exhibited different degree of dynamic characteristics typical of fluid dominated or particle compromising behavior. It should be noted that the magnitude for the different statistics was in the same range regardless of the regime, it was the radial profile for the statistic that changed and subsequently identified that there was a change in the regime. Finally, a reduced regime map was developed consisting of plotting the gas velocity normalized by the upper transport velocity versus the solids flux normalized by the saturation carrying capacity. The use of this reduced plot allowed the data from widely different conditions to be plotted and compared on the same<p>graph. Note that in many instances, some of the statistics identified the operating point as being in one regime while others indicated that it was in another indicating a transition region between dilute or core annular regimes and between the core annular and fast fluidization regimes. This now provides a tool that can be used to optimize process performance, identify changes in operating states, or replicate process dynamics during process scaling or changing operating parameters. </p>
Breault, Ronald↗
Coupled Experimental and High-Temperature Discrete-Element Method Modeling Studies of Aluminosilicate Particle Handling in Concentrated Solar Power Environments
Chemically inert, aluminosilicate based particles have been investigated as both a thermal transport and sensible energy storage medium for concentrated solar power facilities. These particles will experience a wide range of operating temperatures (300-1000 K) and handling conditions (dense to dilute falling particle curtains, dense granular flows, or dense structures), requiring specially-designed and optimized infrastructures. The relative influence of collisional and frictional interactions between particles varies based on temperature-dependent particulate properties and greatly impacts the bulk, granular flow behavior. These underlying physics are captured using discrete element method modeling tools. However, this modeling method is computationally expensive as each particle position and interaction is tracked during the simulation. These modeling methods are further complicated by introducing temperature-dependent particle properties, high-temperature radiative exchange, and directional irradiation sources experienced by granular flows in concentrated solar power environments. Coupled experimental and numerical studies of aluminosilicate particles in rotary kilns and dense particle curtains were performed for bulk temperatures up to 1073 K. The three particle types investigated included Carbobead HSP 30 /60, Carbobead CP 30/60, and Granusil 4030. Temperature, spatial, and velocity profile data were extracted from experimental runs using embedded K-type thermocouple probes and particle image velocimetry techniques. Experimental and numerical studies were compared using spatial temperature profiles, velocity fields, and shape profiles of the bulk, granular flows. Numerical models were developed using commercially available discrete element method modeling software, Aspherix®. Existing Aspherix® functionality was expanded by introducing coupled radiative exchange modeling tools. The laboratory-scale rotary kiln was developed to investigate the steady-state heat and mass transfer performance of aluminosilicate particles based on particle type, bulk handling temperature, and wall roughness. The rotational speed of the rotary kiln was varied to control the relative impact of collisional and frictional effects upon the granular flow behavior. Heat and mass transfer performance was categorized based on the Froude number and the observed flow regimes of slipping, rolling, cascading, and centrifuging. Coupled discrete element method modeling studies were used to evaluate the effects of temperature-dependent, particulate mechanical properties upon bulk flow behavior and upon the relative effects of radiative, advective, and/or conductive heat transfer. A high-temperature (< 1073 K) falling particle curtain was similarly fabricated to investigate the heat and mass transfer performance of aluminosilicate particles in particle handling situations dominated by inter-particle collisions. The impact of particle type, flow preheat temperatures (< 1073K), and bulk mass flow rates were investigated upon the particle curtain shape, temperature, and velocity profiles. Coupled discrete element method modeling studies were performed to evaluate the varying impact of temperature-dependent, particulate mechanical properties on the bulk flow behavior and the temperature profile of the particle curtain.
14 SOLAR ENERGY↗
Investigation of Best-Practices and Computationally Inexpensive Radiative Exchange Models for Discrete Element Method Modeling of Aluminosilicate Particles in Concentrating Solar Power Environments
Chemically inert, aluminosilicate based particles have been investigated as both a thermal transport and sensible energy storage medium for concentrating solar power facilities. These particles will experience a wide range of operating temperatures (300-1000 K) and handling conditions (dense to dilute falling particle curtains, dense granular flows, or dense structures), requiring specially-designed and optimized infrastructures. The relative influence of collisional and frictional interactions between particles varies based on temperature-dependent particulate properties and greatly impacts the bulk, granular flow behavior. These underlying physics are captured using discrete element method modeling tools. However, this modeling method is computationally expensive as each particle position and interaction is tracked during the simulation. These modeling methods are further complicated by introducing temperature-dependent particle properties, high-temperature radiative exchange, and directional irradiation sources experienced by granular flows in concentrating solar power environments. In this study, coupled experimental and numerical slump testing of aluminosilicate particles was performed and computationally efficient radiative exchange models were evaluated to establish best-practices for discrete element method models for concentrating solar power environments. The three particle types investigated included Carbobead HSP 30 /60, Carbobead CP 30/60, and Granusil 4030. Existing modeling limitations and computationally-efficient multi-modal heat transfer models were evaluated using Aspherix®, a commercial discrete element method software. High-temperature (< 1073 K) slump testing of aluminosilicate particles was performed to investigate the deviation between experimentally-observed and numerically-predicted angles of repose introduced by computation-time reduction practices including the relaxation of the particle elastic modulus and coarse-graining. Coarse-graining is used to use a single modeled particle that is representative of a collection of smaller particles, decreasing the computational cost at the expense of geometric accuracy. Additionally, relaxation of the elastic modulus is used to reduce computational time at the expense of an increased, modeled particle overlap. Prior studies have determined that aluminosilicate particles retain a high elastic modulus at high temperatures (< 1073 K), requiring small simulation timesteps to ensure resolved contact forces resemble appropriate solid mechanics. A parametric study was performed to evaluate the influence of computation time improvements on the deviation between experimental and modeled angle of repose across high temperatures < 1073 K. Additionally, numerical case studies were performed on candidate particle systems at varying porosities and temperatures. These studies were performed to investigate the influence of computationally-efficient radiative-exchange modeling methods coupled to Aspherix® on modeled accuracy and computation time. The recently-developed distance-based approximation was evaluated in estimating radiative exchange between particles and participating surfaces located in close proximity. The distance based approximation was developed to use tabulated estimates of the radiative distribution factor between individual particles and surfaces in close proximity (< 40 particle radii). These methods were expanded to the aluminosilicate particles of interest, including the influence of particle size distributions. To capture radiative exchange between particles and surfaces not in close proximity (> 40 particle radii) and to capture the absorption of directional irradiation from concentrating solar resources, a volumetrically-averaged radiative distribution factor was calculated between the modeled granular flow and surfaces using Monte Carlo ray-tracing for participating media. Volume-averaged absorption and scattering coefficients were predicted using a volumetric discretization of the modeled domain with monodisperse approximations based on geometric optics and experimentally-determined scattering phase functions for aluminosilicate particles.
14 SOLAR ENERGY↗
Development and Validation of Dense Discrete Phase Flow Models for Concentrating Solar Power Particle Receivers
This report summarizes a recent project aimed at developing and validating the necessary tools to enable more accurate modeling of denser and more complex particle flows in next-generation particle receivers used in concentrating solar power towers. A newly developed CFD/DEM simulation capability was created by coupling existing the modeling and simulation tools Sierra and LAMMPS. This new capability permitted the inclusion of additional physics for particle drag and particle collisions to model
14 SOLAR ENERGY↗
Turbulent-like flows in quasi two-dimensional dense suspensions of motile colloids
Dense bacterial suspensions exhibit turbulent-like flows at low Reynolds numbers, driven by the activity of the microswimmers. In this study, we develop a model system to examine these dynamics using motile colloids that mimic bacterial locomotion. The colloids are powered by the Quincke instability, which causes them to spontaneously roll in a random-walk pattern when exposed to a square-wave electric field. We experimentally investigate the flow dynamics in dense suspensions of these Quincke random walkers under quasi two-dimensional conditions, where the particle size is comparable to the gap between the electrodes. The results suggest a scaling regime in the energy spectrum ∼k −4 at high wavenumbers, observed consistently across activity levels and particle concentrations. We observe that velocity time correlations decay within a single period of the square-wave field, yet an anti-correlation appears between successive field applications, indicative of a dynamic structural memory of the ensemble.
Luo, Rui [Northwestern Univ., Evanston, IL (United↗
Experimental characterization of extreme temperature granular flows for solar thermal energy transport and storage
High-temperature, dense granular flows along an inclined plane were considered for solar thermal energy transport and storage with sintered bauxite particles. A series of experiments was performed for particle inlet temperatures of ~ 200, 400, 600, and 800 °C to understand the mechanisms of granular flows at extreme temperatures. Mass flow rates were measured using a load cell and free-surface velocities were measured and computed using particle image velocimetry. Surface temperatures were measured using infrared cameras. A significant decrease in steady-state particle mass flow rate was observed with increasing temperature due to changing flow properties. A decrease in bulk particle free-surface velocities was observed at higher temperatures. Free-surface velocity measurement error between experiments were within 20% of the average. The particle surface temperatures decreased from inlet to outlet with larger gradients at higher temperatures observed due to increasing convection and radiative heat losses. Here, a decrease in temperature was observed along the side walls due to a decrease in particle velocities.
14 SOLAR ENERGY↗