Fluidized Bed Model Research Articles

Reduced-Order Modeling of Indirect Fluidized-Bed Particle Receivers with Axial Dispersion

Oxide particles present a heat transfer and thermal energy storage (TES) media for next-generation concentrating solar power (CSP) plants where the high-temperature particle TES can provide dispatchable solar power [1]. Transferring heat to flowing particles can be a challenge and bubbling fluidization is a promising method for increased heat transfer between the oxide particles and confining walls. Using experimentally calibrated correlations for particle-wall heat transfer coefficients [2], this study explores in a quasi-1D model of a narrow-channel counterflow fluidized bed how the high heat transfer coefficients from bubbling fluidization enable cavity-based indirect particle receivers. Particle-wall heat transfer coefficients exceeding 800 W m-2 K-1 support angled solar fluxes > 200 kW m-2 from high normal fluxes > 1200 kW m-2 with wall temperatures < 900 oC. Parametric studies identify how gas flows, solar fluxes, and receiver heights impact receiver solar efficiency for a CSP plant. These modeling studies provide a basis for the development of an indirect narrow-channel fluidized particle receiver that has the potential to operate at normal solar fluxes over 1000 kW m-2 and solar efficiencies above 85%.

Design and evaluation of a geothermal power plant integrated with Mg(OH)₂/MgO thermochemical energy storage system: A dynamic simulation for assessing flexibility in power generation, energy, and economics

This study proposes a Carnot battery system that integrates MgO/Mg(OH)2-thermochemical energy storage (TCES) in a fluidized bed reactor (FBR) with Kalina cycle of a geothermal power plant. In the charge mode, surplus electricity from variable renewable energy is converted into heat and stored through the dehydration of Mg(OH)2. In the discharge mode, the hydration of MgO occurs in the FBR, and the reaction heat is converted into electricity through the Kalina cycle. Dynamic simulations of the charge and discharge modes were conducted using a non-steady state fluidized bed model. Results show the energy storage efficiency and capital cost were 76.4% and 68 USD/MJth for the base case, respectively. Round-trip efficiency and levelized cost of storage were 8.62% and 0.291–0.769 USD/kWhe, respectively, when the charging electricity cost was 0–0.042 USD/kWhe. A cost-competitive Carnot battery system using MgO/Mg(OH)2-TCES with high energy storage density and an easy-to-operate FBR has been developed.

A multiscale interphase heat transfer model for fluidized beds based on the steady-state EMMS approach

Fluidized beds are characterized by heterogeneous structures, which significantly influence the interphase drag and heat transfer. To account for the effects of sub-grid structures on heat transfer in coarse-grid simulations, this study proposes a multiscale heat transfer model based on the steady-state energy-minimization multi-scale (EMMS) approach. This model introduces four structure-dependent internal energy balance equations into the steady-state EMMS model. The heat source and sink terms are included in the internal energy balance equation to maintain a steady-state condition for heat transfer. Solving the model yields the functions of both multiscale drag and heat transfer coefficients. These functions are integrated into coarse-grid simulations under the two-fluid model framework. The simulation results are fairly consistent with the experimental data in terms of both flow and temperature fields, with flow regimes covering bubbling fluidization, fast fluidization and dilute transport.

Data driven reduced modeling for fluidized bed with immersed tubes based on PCA and Bi-LSTM neural networks

The fast and accurate reduced-order modeling of fluidized beds is a challenging task in the field of fluid dynamics, owing to their high dimensionality and nonlinear dynamic behavior. In this study, a nonintrusive reduced order modeling method, the reduced order model based on principal component analysis and bidirectional long short-term memory networks (PBLSTM ROM), was developed to capture complex spatio-temporal dynamics of fluidized beds. By combining principal component analysis and Bidirectional long- short-term memory networks, the PBLSTM ROM effectively extracted dynamic evolution information without any prior knowledge of governing equations, enabling reduced-order modeling of unsteady flow fields. The PBLSTM ROM was validated using the solid volume fraction and gas velocity flow fields of a fluidized bed with immersed tubes, showing superior performance over both the PLSTM and PANN ROMs in accurately capturing temporal changes in the fluidization fields, especially in the region near immersed tubes where severe fluctuations appear. Moreover, the PBLSTM ROM improved the simulation speed by five orders of magnitude compared to traditional computational fluid dynamics simulations. These findings suggest that the PBLSTM ROM presents a promising approach for analyzing the complex fluid flows in engineering practice.

Vibration energy transfer in a forced oscillation fluidized bed

Fluidized bed technology plays a vital role in petroleum, chemical, and coal separation. To improve fluidization stability, airflow is periodically introduced to form a pulsed gas–solid fluidized bed. The vibrating airflow drives the particles with vibration energy transfer and dissipation in the pulsed fluidized bed. The fluidization quality will be greatly improved when the pulsation frequency is equal to the natural frequency. The understanding of the mechanism governing vibration energy transfer and dissipation enables further adjustment of parameters to effectively control the fluidized bed, thereby optimizing its operational state. In this work, the response mechanism of the fluidized bed to resonance effect is described, and its vibration energy transfer and dissipation mechanism is investigated. Furthermore, an evaluation index for energy dissipation rate is proposed. Additionally, based on the theory of spring oscillators, an enhanced natural frequency model for bubble-free fluidized beds is established in this study, incorporating particle properties and bed height as key factors. The predicted error is effectively controlled within 15%, demonstrating excellent agreement with existing literature and research findings.

An experimental and kinetic modeling study of CO2 hydrogenation to CO over Cu-Al catalyst utilizing MFB-TGA-MS

Carbon capture, utilization, and storage (CCUS) are essential technologies for realizing carbon neutrality in the context of fossil fuel decarbonization. Integrated carbon capture and utilization, in conjunction with the reverse water gas shift reaction (ICCU-RWGS), presents a promising strategy for the in-situ conversion of CO2. This approach mitigates the energy penalties associated with CO2 capture and eliminates the additional costs associated with storage and transportation. In this study, we employed a Cu-Al composite catalyst, prepared using the impregnation method, for ICCU-RWGS, with a specific focus on CO2 hydrogenation. The kinetics of hydrogenation for the Cu-Al catalyst were comprehensively investigated using micro-fluidized bed thermogravimetric analysis coupled with mass spectrometry (MFB-TGA-MS). The results indicate that, when subjected to experimental conditions involving 800 °C, 20 vol.% CO2, 30 vol.% H2, and a sample mass of 1 g, the comprehensive evaluation reveals a CO2 conversion rate of 43.67 %. This conversion is accompanied by 100 % CO selectivity and a reaction rate of 0.10 mmol·g−1·s−1, respectively. Furthermore, we calculated the kinetic parameters for the CO2 hydrogenation by analyzing the MFB-TGA-MS data, utilizing the simplified K-L model for fluidized beds. The results indicated an activation energy of 55.8 kJ∙mol−1. These findings highlight the effectiveness of ICCU-RWGS methodologies, especially concerning CO2 hydrogenation, and present a compelling case for their further commercialization.

The effect of baffles on the hydrodynamics of a gas-solid fluidized bed studied using real-time magnetic resonance imaging

Understanding and predicting the hydrodynamics of gas bubbles and particle-laden phase in fluidized beds is essential for the successful design and efficient operation of this type of reactor. In this work, we used real-time magnetic resonance imaging (MRI) to investigate the effect of three commonly-used baffle geometries on gas bubble behavior and particle motion in a fluidized bed model with an inner diameter of 190 mm. MRI time series of the local particle density and velocity were acquired and used to study the size, number, and shape of gas bubbles as well as the motion of the particle phase. The superficial gas velocity was varied between 1 and 2 Umf. We found that baffles decreased the average equivalent bubble diameter with a simultaneous increase in the total number of bubbles. Moreover, baffles promoted bubble splitting and the formation of air cushions below the baffles and decreased the average particle velocity and acceleration in the bed. For two of the three baffle types investigated, the spatial variation of the particle velocity became larger compared to the bed without internal.

Numerical simulation of granular silicon growth and silicon fines formation process in polysilicon fluidized bed

Operating conditions strongly affect the yield and quality of polysilicon in a polysilicon fluidized bed. In this study, a new model of polysilicon fluidized bed was established using the Euler–Euler model coupled with population balance model (PBM), which was combined with fluid flow, heat, and mass transfer models, while considering the scavenging effect of silicon fines. The effects of different operating conditions on the deposition and formation rates of silicon fines were investigated. Results show that the model can correctly describe the particle growth process in the fluidized bed of polysilicon. The silicon fines and the interphase velocity difference show “N”- and “M”-shaped distributions along the axial direction, respectively. The particle temperature and concentration near the wall are higher than those in the central region. The decomposition of silane in the bottom region of the bed is dominated by heterogeneous deposition. The scavenging of silicon fines occurs in the dilute-phase region. The effects of operating conditions, i.e. inlet gas temperature, silane composition, and gas velocity, on the reactor performance were also explored comprehensively. Increasing the inlet gas composition and velocity enhances the formation rates of solid silicon and fines. Increasing the inlet gas temperature promotes the growth of solid silicon and inhibits the formation of silicon fines. High fluidization ratio, low inlet silane concentration, and high inlet gas temperature enhance the selectivity of silicon growth.

Update and extension of the mesoscale model for fast fluidization: Toward type C choking, high-density fast-bed, and flow-regime map

As a supplementary paper for “Mesoscale analysis on clusters in conjunction with fast fluidized bed modeling” published recently, this article aims to update and further extend the model toward type C choking, high-density fast-bed (HDFF), and flow-regime map. Starting from an argument on mesoscale shear-layer formation, a more mechanistic expression for the energy recovery coefficient of in-cloud circulation was derived; and the effective velocity factor for gas flow in the dilute phase was also modified, with which the type C choking for Geldart Group B particles was correctly predicted. Two different mechanisms for “type C choking”, actually the transition at the upper limit of solids flux for traditional fast fluidization in the low velocity region, were identified, i.e. Choking C(I), defined by Gsmax at dMs+/dβ=dMs−/dβ; and Choking C(O), characterized by the cluster diameter reaching Dcl=dp. A rough estimation method for Choking C(I) or C(O) was obtained, thereby. Following the general strategy of extrapolation from its onset, the detailed procedures for modeling of the incipient stage of HDFF, and the classical case, were derived and demonstrated, respectively. The method to predict the upper limit of Gs for HDFF was also obtained, making the flow regime map for fast fluidization fully complete. Simple two parameter criteria, i.e. uf−ut/Dt0.29 and Gs/ρsuf−ut, for sketchy scale-up of fast-beds with the same gas-particle properties were proposed. From those, acceptable flow regime maps for enlarged risers were successfully estimated. Finally, the transition from dilute-transport to fast-bed was revisited, and the reasons for reduction of the solids-wall friction factor, from its direct regression result to the value used in the model, were discussed along with further outlook.

Numerical and Experimental Investigation of Fluidized Bed Hydrodynamics at Elevated Temperatures

Fluidized bed gasifiers operate at elevated temperatures, and experimental measurements for the hydrodynamic parameters at high temperatures are difficult and time consuming, making computational fluid dynamics simulation useful for such investigation. In this study, Opensource computational fluid dynamics code, OpenFOAM, was used to investigate temperature effect on the fluidized bed hydrodynamics on a 3D fluidized bed model using Eulerian-Eulerian approach. Silica sand of particle sizes of 500, 335 and 233 m was used as the bed materials under temperatures between 25 and 400 °C. To validate the simulation model, a laboratory scale fluidized bed unit was used to conduct experiments for the same range of temperature and sand particle sizes. The results revealed that the temperature of the bed materials greatly affect fluidized bed hydrodynamics. The minimum fluidization velocity increased with the sand particle diameter but decreased with the temperature. On the other hand, the bed porosity at the minimum fluidization point increased marginally with both the temperature and the particle size of the bed materials. Further analysis showed that the expanded bed height increased with the temperature for a specific superficial velocity while the bubbles grew in size with both the air flow rates and the temperature. The numerical model results were compared with the experimental results based on minimum fluidization velocity, bed porosity and pressure drop at the minimum fluidization point. The hydrodynamic results of the numerical model were in good agreement with the experimental results.

Dimensioning Air Reactor and Fuel Reactor of a Pressurized CLC Plant to Be Coupled to a Gas Turbine: Part 2, the Fuel Reactor

Bioenergy with Carbon Capture and Storage (BECCS) technologies are fundamental to reach negative CO2 emissions by removing it from the atmosphere and storing it underground. A promising solution to implement BECCS is pressurized Chemical Looping Combustion (CLC), which involves coupling a pressurized CLC reactor system to a turboexpander. The typical configuration chosen is to have an air reactor and a fuel reactor based on coupled circulating fluidized beds. The fluidization regime in both reactors is preferred to be fast fluidization to enhance gas particle contact and solids circulation among reactors. To design the two reactors, Aspen Plus software was used, given that the new version has a module for fluidized bed modeling. At first, the oxygen carrier was designed ex novo, but given that it is a composite compound mainly made by nickel oxide freeze-granulated on alumina (Ni40Al-FG), the molecular structure has been inserted in Aspen Plus. Then, based on the power of the gas turbine, the power output per kg of evolving fluid (in this case, depleted air) is calculated using Aspen Plus. Once the nitrogen content in the depleted air is known, the total air at the inlet of the air reactor is calculated. The fuel reactor is modeled by inserting the reduction reactions for nickel-based oxygen carriers. The paper presents a useful methodology for developing pressurized Chemical Looping Combustors to be coupled to gas turbines for power generation. The provided data will be cross-validated with 0D-models and experimental results.

Numerical simulation of fluidized bed coating process considering particle abrasion

A coupled methodology was developed to model the fluidized bed coating process considering particle abrasion. Interactions of gas phase, particle phase and droplet phase were coupled with multiphase flow. Evaporation, coating and abrasion models were involved and verified by experimental data. The coupled method was evaluated by NaCl coating cases. Under the conditions of two experimental cases, quantitative proportion of the adhered precipitation abrased from the coated particle surface was obtained, which is attributed to frequent particle collisions. Another fluidized bed coating process, in-situ preparation of the Calcium-based supported sorbent for flue gas desulfurization, was simulated to validate the coupled model and investigate the effects of operating conditions on the net coating efficiency. When the nozzle was arranged near the dense phase zone, the conditions had little effect on the efficiency. Otherwise, higher efficiency can be achieved by increasing the bed inventory, droplet diameter, and droplet initial velocity. This research offers an efficient approach for modeling of fluidized bed coating process where particle abrasion is exigent, as well as providing guidelines for practical application of in-situ desulfurizer preparation.

Scalable multi-task Gaussian processes with neural embedding of coregionalization

Multi-task regression attempts to exploit the task similarity in order to achieve knowledge transfer across related tasks for improving the quality of prediction and alleviating the demand of big data. The application of Gaussian process (GP) in this scenario yields the non-parametric yet informative Bayesian multi-task regression paradigm. Multi-task GP (MTGP) provides not only the prediction mean but also the associated prediction variance to quantify uncertainty, thus gaining popularity in various scenarios. The linear model of coregionalization (LMC) is a well-known MTGP paradigm which exploits the dependency of tasks through linear combination of several independent and diverse GPs. The LMC however suffers from high model complexity and limited model capability when handling complicated multi-task cases. To this end, we develop the neural embedding of coregionalization that transforms the latent GPs into a high-dimensional latent space to induce rich yet diverse behaviors. Furthermore, we use advanced variational inference as well as sparse approximation to devise a tight and compact evidence lower bound (ELBO) for higher quality of scalable model inference. Extensive numerical experiments have been conducted to verify the higher prediction quality and better generalization of our model, named NSVLMC, on various real-world multi-task datasets and the cross-fluid modeling of unsteady fluidized bed.

Mesoscale analysis on clusters in conjunction with fast fluidized bed modeling

As a subsequent paper for “type-A-choking-oriented unified model for fast fluidization dynamics”, the present work aims to provide more systematic mesoscale analyses on clusters. Starting from theoretical derivations on idealized flow patterns of gas and solids around a single falling cluster; the momentum consumption due to particle circulation in clouds and the modification of flows by the constraint of driving force available in the bed were addressed. Complete compensation of the pressure-drop driven percolated gas in clusters by the reversely-penetrating particles was used for the ultimate closure of the model. An important finding of the present work, different from most empirical correlations, but verified by Wei and Zhu's latest experimental data and others, is that the cluster diameter does not vary monotonically with the mean solids holdup of the bed, but has a maximum value in between. Demonstrative calculations show that it is easy for Group A particles to enter the flow regime of high-density fast-fluidization as the circulating solids flux increases continuously, while fast fluidization for Group B particles tends to be stopped at Type C choking in advance. Compared with Group A particles, the clusters for Group B particles are less dense, but the penetration velocities of particles are higher, resulting in much larger dimensionless diameters of clusters. Finally, issues of pseudo-2D fast-bed modeling were discussed, and modeling of fast-beds with uneven flow fields was outlook briefly.

Modelling DME production from synthetic gases with a fluidized bed reactor: A CFD approach

Dimethyl ether (DME) is one of the most sought-after automotive fuels. Catalyst is generally preferred in direct dime production from synthesis gas. 0In our study, Computational Fluid Dynamics is used for reactor modeling of DME production from syngas in a fluid bed model. It is aimed to determine the necessary conditions to ensure maximum gas-solid contact for the production of zeolite-catalyzed DME in a fluidized reactor, especially for the syngas produced by gasification method from domestic wastes. A distinctive feature of this approach is the physical optimisation simulation. The calculation of the bed density at which the catalyst active surface is provided at maximum contact has a very important place in determining the reactor operating conditions. In the study, firstly, the simulation model is compared with a real experimental fluidized bed model. In the subsequent optimization study, the conditions where the maximum solid-gas contact surface was achieved was sought. For this reason, the results obtained in the case of a bed density of 2200 kg/m3 showed that the pressure drop increased positively across the bed. This means that the reaction time is reduced. Therefore, the bed density value of 2200 kg/m3 (with a maximum volume fraction of 55%), is the ideal density value to ensure maximum gas-solid contact compared to 2300 (with a maximum volume fraction of 55,8%), 2400 (with a maximum volume fraction of 59,5%), 2500 (with a maximum volume fraction of 58,9%), and 2600 (with a maximum volume fraction of 57,2%) kg/m3.

MP-PIC simulation of the gas-solid full-loop flow characteristics in a dual fluidized bed and validation with experimental data

• Full-loop flow characteristics are investigated by MP-PIC simulation. • Four flow zones are identified in the BFB. • The BFB and the lower U valve are working together as a particle buffer region. • The start-up characteristics among different parts are investigated based on simulation. It is necessary to investigate and understand the gas-solid flow characteristics for the design and optimized operation for chemical looping combustion reactors and other chemical process which involves dual fluidized bed (DFB) system. In this research, computational fluid dynamics simulation was performed in a lab-scale cold three-dimensional full-loop dual fluidized bed model based on the Particel-In-Cell (MP-PIC) method to understand its gas-solid flow characteristics. The simulated results were analyzed and validated with the pressure and electrical capacitance tomography (ECT) measurements. It has been shown that Wen-Yu/Ergun drag model is feasible for the prediction of the gas-solid flow dynamics of this DFB system. The simulated particle volume fraction and ECT results have a good agreement. In the bubbling fluidized bed (BFB), four flow zones are identified based on the bubble and particle behaviors. In each zone, bubbles are mainly concentrated in the middle region. Moreover, the fluidizing air in the chute functions as a secondary air of the BFB to facilitate the particle movement. The BFB and the lower U valve are working as one component and function as a particle buffer region. Therefore, the balance of the whole system is determined by the time when the riser reaches steady state. The higher the air inlet velocity of the riser, the sooner the system reaches steady operation. In addition, the start-up characteristics among the riser, the BFB and U-valve are investigated based on the simulation results. The results indicated that there is a start-up time lag between the riser and bubbling fluidized bed when they each reach steady state.

Modeling and experimental investigation on the fuel particle heat-up and devolatilization behavior in a fluidized bed

The proper understanding and description of fuel devolatilization behavior in a fluidized bed (FB) is important to the FB reactor design and modeling. Aiming at this issue, two different mathematical models, isothermal (0D) particle model and one-dimensional (1D) particle model, have been developed. The particle heat transfer is solved simultaneously using an iterative approach with the existing nitrogen containing chemical percolation devolatilization (CPD-NLG) model. Experiments in a special designed FB reactor were conducted to help validate both the temperature solver and modifications to the fast nitrogen release chemical kinetic parameters. The results show that when the bed temperature is higher or coal size become smaller, the final volatiles yield increases and the nitrogen remaining in char decreases. Under all conditions given in the present study, the final nitrogen content of char is always lower than that of parent coal. The yields of some volatile species are also affected by the coal size and bed temperature. In addition, simulation analysis reveals that the deviation between the results of these two models cannot be ignored if the particle size exceeds a specific value (transition size), namely, the large particle is improper to be described as isothermal during heat-up, while this transition size decreases with the increase of bed temperature. A selection principle of these two models is proposed for balancing the calculation precision and computational time. The particle model developed in this work makes it possible to carry out further FB reactor simulations with the devolatilization process more consistent with laboratory data.

Material specific drying kinetics in fluidized bed drying under mechanical vibration using the reaction engineering approach

The accurate modeling of vibrated fluidized bed dryers plays an important role in the design and optimization of industrial drying processes. Understanding the impact of vibration on the hydrodynamics of the bed, as well as the drying kinetics, is crucial for accurate modeling. The influence of vibration on the drying kinetics was investigated. It could be shown that vibration reduces the minimum fluidization velocity (umf) and thereby enables the operation of fluidized bed dryers at lower gas velocities. The reduction of umf is particularly pronounced at the resonance frequency of the bed material. However, once the powder was fully fluidized, no impact on the drying kinetics was observed.The Reaction Engineering Approach (REA) is one of the methods used to describe the drying kinetics with one material specific curve. In this work, it was shown that REA curves can be determined based on batch drying experiments in fluidized beds. Porous particles of Geldart groups A, B and D with particle sizes and densities similar to food products were investigated and their REA curves were experimentally determined. Comparison of the derived REA data with established material specific drying curves from literature shows high similarity. Hence, the REA data from fluidized bed experiments is suitable for the modeling and simulation of fluidized bed drying processes.

Development of data-driven filtered drag model for industrial-scale fluidized beds

Simulations of large-scale gas-particle flows using coarse meshes and the filtered two-fluid model approach depend critically on the constitutive model that accounts for the effects of sub-grid scale inhomogeneous structures. In an earlier study (Jiang et al., 2019), we had demonstrated that an artificial neural network (ANN) model for drag correction developed from a small-scale systems did well in both a priori and a posteriori tests. In the present study, we first demonstrate through a cascading analysis that the extrapolation of the ANN model to large grid sizes works satisfactorily, and then performed fine-grid simulations for 20 additional combinations of gas and particle properties straddling the Geldart A-B transition. We identified the Reynolds number as a suitable additional marker to combine the results from all the different cases, and developed a general ANN model for drag correction that can be used for a range of gas and particle characteristics.

Journal Vol – 15 No -7, July 2020 Journal > Journal > Journal Vol – 15 No -7, July 2020 > Page 6 PERFORMANCE AND EMISSION CHARACTERISTICS OF GASOLINE-ETHANOL BLENDS ON PFI-SI ENGINE Authors: D.Vinay Kumar ,G.Samhita Priyadarsini,V.Jagadeesh Babu,Y.Sai Varun Teja, DOI NO: https://doi.org/10.26782/jmcms.2020.07.00051 admin July 26, 2020 Abstract: Alcohol based fuels can be produced from renewable energy sources and

Journal Vol – 15 No -7, July 2020 Journal > Journal > Journal Vol – 15 No -7, July 2020 > Page 6 PERFORMANCE AND EMISSION CHARACTERISTICS OF GASOLINE-ETHANOL BLENDS ON PFI-SI ENGINE Authors: D.Vinay Kumar ,G.Samhita Priyadarsini,V.Jagadeesh Babu,Y.Sai Varun Teja, DOI NO: https://doi.org/10.26782/jmcms.2020.07.00051 admin July 26, 2020 Abstract: Alcohol based fuels can be produced from renewable energy sources and