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At least 37 records · Page 2

Integrated modeling methodology for ash agglomeration in poly-disperse fluidized beds using particle population framework

This article discusses a unique agglomeration modeling methodology developed based on binary collisions to combine the effects of heterogeneity in ash chemistry and granular physics. A simple population balance is defined to find changes in the particle size distribution (PSD) of a fluidized bed. Thermodynamic equilibrium calculations and a computational fluid dynamics (CFD) code, are used to obtain hydrodynamic parameters. A method to calculate and use a distribution of collision frequencies in fluidized beds, corresponding to a poly-disperse particle size distribution, was developed in order to incorporate the particle level heterogeneities. A distribution of collision frequencies obtained for poly-dispersed particles showed a three orders of magnitude higher collision frequency amongst the smaller particles than the coarser ones, at the initiation of agglomeration. Ash agglomeration occurred when the slag amount (binder) was less than 10 wt% at temperatures <850 °C for Pittsburgh No. 8 coal.

42 ENGINEERING↗

Thermal Modeling and Simulation of the Packed-bed Thermal Energy Storage Combined with INL Thermal Energy Distribution System

Dynamic Energy Transport and Integration Lab (DETAIL) at Idaho National Laboratory is to support experimental demonstration and validation research on Nuclear-Renewable Hybrid Energy System [1]. The Thermal Energy Distribution System (TEDS) is a thermal-hydraulic flow loop in DETAIL with its own dedicated control system to support the integration of co-located multiple experimental systems, where a packed-bed thermal energy storage (TES) is installed as a thermal buffer and storage unit. Among various TES options, the packed-bed TES is adopted in TEDS because it offers a low-cost single-tank thermal storage option compared to the traditional two-tank TES. However, since the TES tank is filled with granular fillers having different thermophysical properties from those of TES tank wall, there is a potential thermo-mechanical issue to be carefully addressed like thermal ratcheting which may pose a significant design concern for the packed-bed TES tank. Thermal ratcheting is a thermomechanical process caused by the repeated rearrangement of granular filler inside a TES tank during continuous thermal cycling operation of the packed-bed TES system. If the thermally induced stress exceeds the yield strength of a TES tank wall, catastrophic consequences may happen like rupture of the TES tank. Thus, it is important to understand the phenomenon to ensure the robust operation of the packed-bed TES tank. Given that thermal ratcheting is caused by complex interaction of thermal transport in the porous bed and solid mechanics, the accurate prediction of transient thermal behavior of the packed-bed TES tank, which is the focus of this paper, is critical to the reliable thermal ratcheting analysis. This paper discusses the numerical modeling, simulation, and validation studies that are ongoing at INL to investigate the transient thermal behavior of the packed-bed TES. Of particular concern is the transient thermal process occurring in the packed-bed TES unit that is operated in conjunction with the INL TEDS. The main goal of this research is three-fold: (i) provide preliminary insights into the transient thermal behavior of the TEDS TES tank, (ii) support the thermal measurement and validation plan for TEDS experiment, and (iii) provide transient thermal boundary conditions to support the reliable thermal ratcheting analysis of the TEDS TES tank. For the transient thermal modeling and analysis, a CFD model was developed, and the validity of the modeling approach was examined via comparing the numerical simulation results with the experimental data obtained from various design characteristics of packed-bed TES tanks. Then, the present modeling method was applied for the transient thermal analysis of the TEDS TES tank, and the results are discussed along with the potential improvement of data acquisition strategy for the future TEDS experiments for more precise validation study.

25 ENERGY STORAGE↗

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↗

Continuum Correlations from CFD-DEM Modeling of Conduction Heat Transfer in Granular Flows

Heat transfer between a surface and flowing particles is analyzed to improve the accuracy of continuum models for wall-to-bed heat transfer in a fluidized bed. Discrete element modeling (DEM) is used to model a fluidized bed heat exchanger where heat enters the system through a heated wall. The DEM heat transfer predictions are validated against published experimental work (Brewster et al., 2024) with less than 15% error. In previous work by Morris et al. (2015), a continuum model was developed using data from high-fidelity DEM simulations of chute flows. In the current study, the continuum model is extended and validated for fluidized beds. The sensitivity of the continuum heat transfer model parameters, which was not quantified in previous studies, is also investigated. It is observed that for a given particle with specific properties, e.g. the particle size, roughness, and conduction lens radius, the continuum correlation developed for heat transfer from a heated boundary to the particle bed depends mainly on the solid fraction or porosity of the particle bed for a given fluid. The new continuum heat transfer model is then validated over a wide range of superficial velocities via comparisons to both discrete element and experimental data. It is shown that this correlation is valid for a large range of particle flow conditions from chute flows to fluidized beds with less than 10% error as compared to DEM predictions.

14 SOLAR ENERGY↗

Multimaterial powder bed patterning for additive manufacturing method

The present disclosure relates to an additive manufacturing system. In one embodiment the system makes use of a reservoir for holding a granular material feedstock. A nozzle is in communication with the reservoir for releasing the granular material feedstock in a controlled fashion from the reservoir to form at least one layer of a part. An excitation source is included for applying a signal which induces a controlled release of the granular material feedstock from the nozzle as needed, to pattern the granular material feedstock as necessary to form a layer of the part.

Dudukovic, Nikola↗

Thermal Ratcheting Analysis of TEDS Packed-bed Thermocline Energy Storage Tank - Modeling Methodology and Data Validation

This report investigates numerical modeling methods for thermal ratcheting analysis of packed-bed thermal energy storage (TES) tank and discusses the validation results via comparison with experimental data. The experimental data obtained from various design characteristics of packed-bed thermocline tanks, including the Thermal Energy Distribution System (TEDS) TES tank at Idaho National Laboratory (INL), were used to validate thermal and mechanical models developed in this study to evaluate the thermal ratcheting potential. The thermal model was shown to predict the transient thermal propagation through the packed-bed thermocline tanks generally well. However, a larger discrepancy was observed during the comparison with the data from TEDS, presumably due to the uncertainty of boundary conditions given from the experiment. Based on the comparative study between the thermal model predictions and experimental data of various packed-bed thermocline tanks, potential improvements were suggested for the future TEDS experiments for more precise validation study. For mechanical (thermally induced stress) analysis, two different modeling approaches were tested to evaluate hoop stress applied to the packed-bed TES tank wall, which is a major cause of thermal ratcheting process: (i) infinite rigidity model and (ii) Drucker-Prager (DP) model. The ‘model (i)’ is a conservative method with infinite rigidity assumption of granular filler inside a TES tank, whereas the ‘model (ii)’ is a method that takes into account more realistic processes such as thermal expansion of filler and tank wall as well as inter-particle interactions during the cyclic operation of a packed-bed TES tank. The validity of each modeling method was examined by comparing the numerical simulation with the experimental data obtained from the packed-bed TES tank for Solar One pilot plant. Then, the effects of various model parameters were discussed to evaluate the thermal ratcheting potential of the TEDS TES tank. The preliminary thermal ratcheting analysis implies that the TEDS TES tank will hold its structural integrity during the normal operation cycles.

25 ENERGY STORAGE↗

An Open-Source Framework for the Computational Analysis and Design of Autothermal Chemical Processes

The main project object was to develop software tools for simulating non-equilibrium autothermal processes, improving the prospects for identifying and designing such systems. The project demonstrates the use of these tools to simulate autothermal pyrolysis, a process recently developed at the pilot-plant scale at Iowa State University. In such process, instead of externally heating a reactor to pro-vide the enthalpy of pyrolysis, sufficient oxygen in the form of air is introduced into the reactor to support partial oxidation of reactants and products with the exothermic energy released supporting endothermic pyrolysis reactions. A fluidized bed is used to assure good mixing of biomass and oxidant and provide an isothermal reaction environment. The amount of oxygen required depends upon the kind of biomass being pyrolyzed and parasitic heat losses from the reactor. For example, for woody biomass pyrolyzed under conditions that simulate adiabatic operation, equivalence ratios can be as low as 0.06, compared to 0.20 or higher for autothermal gasifiers. By removing the heat transfer bottleneck of conventional pyrolysis, operation in autothermal mode allowed a significant increase in reactor throughput process, approaching five times the throughput of the conventionally operated pyrolyzer. Different simulation strategies were considered and developed: a zero-dimensional chemistry model was used to verify the applicability of kinetic schemes to predict biomass fast pyrolysis in autothermal conditions. Conventional chemical reactor models such as the plug flow reactor and the partially stirred reactor were used to investigate the role of mixing in the fluidized bed pyrolyzer and to establish the impact of mixing time on the gas-phase reactions. A comprehensive multiphase computational fluid dynamics (mCFD) framework, including polydisperse granular phase modeling and detailed chemical kinetics was formulated and used to model the experimental setup for autothermal biomass fast pyrolysis at ISU. Multiphase CFD was also used to investigate the role of biomass feed positioning on the mixing of biomass in the pyrolizer. Finally, a reduced order model (ROM), suitable to be implemented in process simulators was obtained. Both the mCFD and the ROM were validated against experiments.

09 BIOMASS FUELS↗

A Forward Feedback Control Scheme for a Solar Thermochemical Moving Bed Counter-Current Flow Reactor

Abstract Pelletized thermochemical energy storage media has a potential for long-duration energy storage. Production of solid-state energy storage media can be done within a cavity chemical reactor that captures concentrated solar radiation from a solar thermal field. The temperature stability of a solar reactor is directly influenced by the solar flux intercepted. This paper presents a low-order physical model to simulate the dynamic response of temperature inside a tubular plug-flow reactor prototype. Solid granular particles are fed to the reactor from the top whereas a counter-current flowing gas enters the reactor from the bottom. An in-house code was developed to model transient heat transfer of the reactor wall, gas, and moving particles. The model was preliminarily validated with packed beds for different temperature ranges and two gas flowrates. Dynamic response of the reactor temperature is simulated for different input power and gas/particle flowrates. The results show that the system response can be controlled efficiently by utilizing input power (solar flux) as a control parameter. A conventional proportional integral (PI) controller is designed to control the temperature inside the reactor and to maintain it during the solar flux intermittency. The controller parameters are tuned using the Ziegler–Nichols method to ensure optimal system response. The results show that the feedback control model is successful in tracking different reference reactor temperatures within a reasonable settling time of 30 min and eliminated overshoot. This study can be extended to include a hybrid reactor with a multi-input, multi-output variable system.

Energy & Fuels↗

Particle Size gradients in Modeled Vibrated beds of continuously sized powders

Ensuring powder mixture homogeneity is paramount for modern powder processing techniques. A promising recent development in the field of powder processing, resonant acoustic mixing (RAM), proposes to use low-frequency vertical vibration to deliver well-mixed powders without relying on mechanical agitators. However, an undesirable outcome of vibrations applied to granular materials comprised of non-uniform particle sizes is the tendency towards size segregation. In this work, we experimentally ex

Renfroe, Steven Emad [Sandia National Laboratories↗

Perovskite Sorbent Oxygen Separation Modeling with MFiX

This document chronicles the development and implementation of computational kinetic rate models that capture absorption and desorption characteristics of the National Energy Technology Laboratory (NETL) developed perovskite, Sr 1-x Ca x FeO 3-δ . Two paths to create accurate kinetic rates were followed: (1) an isothermal rate approach where thermogravimetric (TGA) data are recast as oxygen capacities through a pseudo-second order Lagergren equation (He et al., 2009); and (2) a more traditional Arrhenius approach where experimental data are fit with a power law model to derive associate activation energies (Bulfin et al., 2020a). For reference, the mathematics and associate experimental strategies that support these derivations are included in this report. In addition, computational fluid dynamics (CFD) models were developed to utilize both kinetic rate formulations and applied to simulate oxygen uptake and release in small scale scenarios. The program Multiphase Flow with interphase eXchanges (MFiX) was used to create: (1) discrete element method (DEM) simulations of a single tube of granular perovskite experiencing isothermal O 2 -absorption; and desorption and (2) two-fluid-model (TFM) non-isothermal simulations of perovskite O 2 -absorption and desorption tubes that share a wall. Conjugate heat transfer between steel walled tubes and the perovskite bed were managed with user-defined functions. As the project moves to simulating larger scale devices that will require more robust conjugate heat transfer methods, developed kinetic rates and associate methodologies have been recast for use in the ANSYS Fluent CFD program.

36 MATERIALS SCIENCE↗

In‐operando thermal transport characterization of moving particle bed heat exchanger

The project aimed to develop modulated photothermal radiometry (MPR) for conducting in-operando measurements of thermal transport in moving particle bed heat exchangers (MPBE) located at Sandia National Laboratory (SNL). The plan was to initially conduct lab-scale measurements on a 1-meter-long particle channel at UCSD, followed by in- operando measurements at SNL on a 20 kWth MPBE prototype built for this project, and if time permitting, potential final deployment on SNL’s 1 MWth G3P3 MPBE. The first two goals were successfully achieved but due to changes with commissioning timeline of the G3P3 MPBE, in-operando measurements on the G3P3 MPBE could not be conducted. The measurement campaigns have resulted in some promising results and the MPR tool has been handed over to trained SNL personnel for future use. MPR measurements on UCSD’s 1-meter-long particle channel showed a peculiar length dependence of the particle bed thermal conductivity and near-wall thermal resistance. The bed thermal conductivity increased, and the near-wall thermal resistance decreased, with increasing distance from the channel inlet, both eventually reaching a plateau. This was found to be due to hydrostatic pressure screening by the channel walls, known as the “Janssen effect”, and is the first experimental study on its role in granular heat transfer. A 20 kWth small-scale MPBE prototype, the first of its kind with 3 mm particle channels and 2 mm sCO2 plates, was designed and manufactured by Vacuum Process Engineering (VPE) for this project. This MPBE prototype was installed in SNL’s HEX test stand and the MPR tool was integrated into the test stand for in-operando measurements. Several modifications have been made to the MPR setup for facile installation and easy operation at SNL. Measurements with Carbo HSP40/70 particles were conducted with various particle and sCO2 temperatures and flow rates. Further, apart from regular MPBE operation, fault scenarios such as plate warping, particle stagnation, and choking were also detected and MPR showed excellent sensitivity to the detection of such conditions. Through the course of this project, MPR has evolved from a sensitive laboratory technique to a rugged industrial tool with various applications in high temperature measurements and diagnostics.

14 SOLAR ENERGY↗

Corona splashing triggered by a loose monolayer of particles

In nature, high-speed raindrops often impact and spread on particulate surfaces (e.g., soil, plant leaves with spores or pollen). We study the dynamics of droplet impact on a loosely packed monolayer of particles by combining experimental and mathematical approaches. We find that the presence of mobile particles lowers the critical impact velocity at which the droplet exhibits corona splashing, as the particle area fraction is systematically increased. We rationalize this experimental observation by considering the jamming of frictional particles at the spreading rim. Elucidating the splashing transition of the drop on a particulate bed can lead to a better understanding of soil loss and erosion from falling raindrops

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Data From Experiments on Bubbling Fluidization of Zeolite in a Rectangular Bubbling Fluidized Bed

Fluidization experiments were conducted in a lab-scale rectangular bubbling fluidized bed with the objective of generating a high-quality dataset for model validation and artificial intelligence/machine learning (AI/ML) training. Zeolite was chosen as the bed material, and the fluidizing medium was air as supplied by a compressor. Three different flow rates at the inlet were chosen such that the particles were fluidized but not elutriated from the system. The test matrix involved randomization and replicates to provide uncertainty estimates as well as four different batches of zeolite as the bed material. The quantities of interest obtained from this study were statistics of differential pressures, interface heights, and particle velocities. Considering all the components of the elaborate test plan, the results obtained were consistent and reproducible. Characterization tests were performed to estimate particle properties including size, density, coefficient of friction, coefficient of restitution, and minimum fluidization velocity. In addition, the angle of repose from granular discharge experiments has been reported to account for rolling friction, though its effect on the overall process is expected to be negligible.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An index to characterize gas‐solid and solid‐solid mixing from average volume fraction fields

Abstract A mixing index based on solid volume fraction fields is developed for gas‐solid flows. Conventional mixing indices are based on particle realizations of granular mixing and are applicable to experimental data or discrete element method simulations. However, these indices cannot be used as‐is for multifluid models, and an index for characterizing mixing in gas‐solid flows from continuous fields is needed. The performance of the new mixing index is tested in two applications. The first is a 3D simulation of the mixing of biomass and sand in a fluidized bed reactor, and the second is a 2D simulation of binary particle segregation in a fluidized bed. The simulations are performed using OpenFOAM®. The mixing index is used to quantify gas‐solid mixing using solid volume fractions and solid‐solid mixing using solid fractions. The formulation of conventional mixing indices is extended to be used with solid volume fractions fields, and methods for performance improvement are presented.

09 BIOMASS FUELS↗

An investigation into the effects of cyclic strain rate on the high cycle and very high cycle fatigue behaviors of wrought and additively manufactured Inconel 718

Additive Manufacturing (AM) has increasingly been used to fabricate parts in aerospace applications, which may require service lives beyond ten-million cycles due to the imposed high loading frequencies. Understanding the very high cycle fatigue (VHCF) behavior of these additive manufactured (AM) parts is an important step towards their design and qualification processes. This study focuses on the high cycle fatigue (HCF) and VHCF behaviors of both wrought and laser beam-powder bed fusion (LB-PBF) fabricated Inconel 718 in machined/polished surface condition, emphasizing on the influence of test frequency (i.e., cyclic strain rate). Uniaxial, fully-reversed force- and stress-controlled fatigue tests were conducted utilizing a servo-hydraulic and an ultrasonic test system operating at 5 Hz and 20 kHz, respectively, on wrought as well as LB-PBF vertically and diagonally built specimens. Fatigue cracks in the majority of the specimens were found to initiate from intra-granular slip bands near or at the surface, which gives rise to strong anisotropy in fatigue resistance in LB-PBF specimens due to the presence of columnar grains along the build directions. Longer fatigue lives were obtained at 20 kHz, which was ascribed to possibly lower-than-intended stresses applied in the ultrasonic tests. The corrected stress-life fatigue data at 20 kHz were found to converge to the one obtained from conventional testing at 5 Hz, implying no effect of cyclic strain rate on the fatigue behavior of Inconel 718 regardless of the fabrication process. The findings of this work confirm the use of ultrasonic fatigue testing to expedite generation of AM materials data to keep up with the current demand; however, the applied stress may need to be corrected.

36 MATERIALS SCIENCE↗

Critical analysis of velocimetry methods for particulate flows from synthetic data

Particle tracking methods that extract high-fidelity particle velocity data from high speed video of particle laden flows is a common experimental technique applied to chemical processes. These measurements are used to better understand the motion of particles and fluids in complex systems and create data against which computational models are validated. However, the methods, codes, and experimental setups all have limitations. It is imperative that practitioners verify the methods and their implementation as well as understand the limitations of experimental setups. This work focuses on quantifying the visible depth of field in a high particle concentration fluidized bed. Following a precedent set by the particle imaging velocimetry community, a particle velocity field is manufactured using a computational fluid dynamics and discrete element method simulation. Photo realistic high-speed videos are rendered based on the simulated data using the three-dimensional creation software Blender. Particle velocities are extracted from the synthetic high-speed videos using three variants of Particle Tracking Velocimetry and Optical Flow Velocimetry methodologies. Here, the tracked results are then compared to the known solution, quantifying the error associated with the assumed visible depth. The results indicate that at depth of one particle diameter, all three particle tracking codes give accurate measurements, largely within 5%. However, the error increases when the full bed video measurements are compared to the known solution at one particle diameter, i.e., mimicking a validation study. Finally, for some statistics the constant depth assumption only increases the error slightly, for others significantly.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Real-time tracking and analysis of gas bubble dynamics in laser powder bed fusion using in-situ X-ray characterization and machine learning

Porosity defects remain a significant challenge in the laser powder bed fusion (LPBF) process, adversely affecting the mechanical properties and reliability of additively manufactured components. Here, this study investigates the real-time formation and trajectory of gas bubbles during LPBF of Al6061 alloy using advanced in-situ X-ray characterization and machine learning. The unsupervised Gaussian mixture model and particle tracking algorithm developed are able to precisely track and quantify the properties of gas bubbles and keyhole pores. Our analysis identified five distinct types of gas bubble formation and movement patterns, emphasizing the diverse origins and behaviors of these defects. It enables precise quantification of trajectories, velocities, and morphological changes of gas bubbles, offering a granular view of the subsurface dynamics within the melt pool. Additionally, we explored keyhole-induced pore dynamics, revealing the critical role of keyhole oscillation and collapse for the formation of both large and small gas pores. It defines four different regions of gas bubble movement within the melt pool, providing a clearer understanding of how local fluid dynamics affect pore behavior. The results underscore the importance of integrating in-situ experimental observation and automated machine learning to develop a more robust predictive model for defect formation in LPBF.

In-situ X-ray imaging↗

An error-controlled adaptive time-stepping method for particle advancement in coupled CFD-DEM simulations

Coupled Computational-Fluid-Dynamics (CFD) and Discrete-Element-Method (DEM) models provide an accurate description of multiphase physical systems where a solid granular particle phase exists in an underlying gaseous continuous medium. The time integration of the granular phase in these simulations is typically handled using an explicit scheme with a constant time-step among all particles that is invariant in time to resolve inter-particle collisions. A locally third-order accurate adaptive time integration technique for particles that employs an embedded locally second-order scheme for error determination is presented in this work. The particle time-step size is dynamically adapted based on solution error, thus leading to significant savings in computational time. The efficacy of our scheme is quantified using four test cases of varying complexity (binary collision, homogeneous cooling system, fluidized bed and hopper discharge). The adaptive time-stepping method exhibits improved performance (~ 2–3 times in most of the cases studied) compared to three commonly used non-adaptive time-step methods (first-order Euler-explicit, second-order Adams-Bashforth and third-order Runge-Kutta schemes), while maintaining the same level of accuracy and parallel scalability.

42 ENGINEERING↗