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We report the finding of four changing look (CL) Active Galactic Nuclei (AGN). We selected these sources due to their potential as interesting targets when considering their relatively large optical flux variations and related mid-infrared flux variations. To identify their CL feature, we use archival spectra from the Sloan Digital Sky Survey (SDSS) taken at least 8 yr ago as well as spectra taken recently from the Transient Name Server (TNS) and with the 2.4-m LiJiang telescope (LJT). We study the sources' spectral changes by fitting and determining the Hα and Hβ components and verify their CL behaviour. When comparing the TNS and/or LJT spectra to the SDSS ones, all four sources showed the appearance of a broad or a stronger broad Hα component and a relatively weak broad Hβ component. As two of the four sources are established to have a brighter-and-bluer feature in the photometric data, during the time periods in which the TNS and LJT spectra were taken, this feature likely accompanied the turn-on of the broad components. Thus, we suggest that this brighter-and-bluer feature can be used as a criterion for efficiently finding CL sources among previously spectroscopically classified type 2 AGN, such as from among the sources provided by the SDSS. [ABSTRACT FROM AUTHOR]

Establishing a clean, low-carbon, and efficient energy system is paramount for the sustainable development of industries and human society. Multiphase flows are encountered extensively in various energy applications, including transportation, conversion, and utilization of fossil, renewable, hydrogen, and nuclear energies. These flows encompass a wide range of phenomena, such as fluid flow, heat and mass transfer, combustion, and chemical reactions. However, multiphase flows are highly intricate due to the coexistence of multiple phases, states, and components, as well as the interactions among them that occur across diverse spatiotemporal scales. Consequently, both academia and industry face significant challenges in comprehending and harnessing multiphase flows. Thus, establishing connections between basic research and industrial applications in the field of multiphase flows is fundamental and indispensable for advancements in energy science and technologies. [ABSTRACT FROM AUTHOR]

The effect of fluid turbulence models on the coarse-grid simulation for the mesoscale gas-solid flow system is not as clear as that for gas-liquid/single flows. In this study, the effect of different turbulence models on predictions of riser-only, turbulent and bubbling flow hydrodynamics is quantified. Then the selected turbulence models are examined by coarse-grid simulations in a full-loop circulating fluidized bed (CFB) with a proposed hybrid drag model which integrates two SGMs and Hulin-Gidaspow model. Results show that the standard k -epsilon and k -omega models fail to capture a correct fluidization pattern in riser. Meanwhile, the RNG and realizable k -epsilon models and SST k -omega model enable satisfactory predictions which are highly comparable to discrete model predictions and experiments over different flow regimes. However, the realizable k -epsilon model produces more pronounced flow fluctuations causing computational instability. Using superior turbulence closures, full-loop simulations with the proposed hybrid model can predict desirable hydrodynamics. Unlabelled Image • A hybrid drag model is proposed for feasible coarse-grid full-loop CFB simulations. • Applicability of different turbulence models over various fluidization regimes. • Validated against the discrete particle model and experiments. • The RNG k -epsilon and SST k -omega are optimal for gas-solid flows. [ABSTRACT FROM AUTHOR]

We introduce the concepts of 'multi-level-nozzle' and 'continuous oscillatory tapered' fluidized beds to enhance contact efficiency and promote mixing between the gas and particle phases for a pilot-scale turbulent fluidized bed. Before delving into these concepts, we comprehensively assess the mesoscale drag correction model's parameter sensitivity, ensuring its applicability in lab-scale and pilot-scale turbulent fluidized beds, as well as pilot-scale risers. Following this evaluation, we design multiple cases to systematically investigate the influence of injection nozzle numbers, heights, and angles on the hydrodynamic mechanisms, specifically focusing on the degree of particle clustering and intermittency. Furthermore, we explore the effect of reactor shapes in terms of tapered ratios and sub-tapered bed numbers to intensify contact efficiency of two phases. By implementing these conceptual designs, we effectively enhance the intermittent extent of particles by over 30% and achieve higher oscillation frequencies with relatively low instability, leading to intensification of flow quality. [Display omitted] • Comprehensive assessment of parameter sensitivity in the mesoscale drag correction model. • Using the optimum mesoscale model to design injection modes and reactor shapes. • Proposing concepts of 'multi-level-nozzle' and 'continuous oscillatory tapered' fluidized beds. • Enhancing the extent of particle intermittent by over 30% and improving flow quality. [ABSTRACT FROM AUTHOR]

• A bed expansion ratio correlation is proposed based on extensive numerical simulations. • Effect of various numerically derived drag models on gas-solid flow dynamics is quantitatively assessed. • Simulation results agree with experimental data reasonably well. • The corrected correlation improves the prediction by the empirical equation. For designing and operating fluidized bed reactors, bed expansion ratio is one of the most important parameters. In this research, a bubbling fluidized bed is simulated using three-dimensional Eulerian-Eulerian method that is incorporated with kinetic theory of granular flow (KTGF) to calculate the pressure drop, gas volume fraction (GVF) and bed expansion ratio. Grid optimization is firstly conducted to achieve suitable solution for further simulations. Subsequently, different numerically derived drag models are employed to investigate the effect of these models on gas-solid flow dynamics. Afterwards, the fluidized bed is simulated at different gas superficial velocities employing two different drag models respectively. Simulation results have been comprehensively validated against experimental data. Finally, an expression for bed expansion ratio has been formulated and compared with the empirical correlation. The proposed correlation holds reasonably well with various experimental values. This work provides a scalable way to aid in designing and operating process reactors. [ABSTRACT FROM AUTHOR]

In this work, a three-dimensional coarse-grid two-fluid model (TFM) simulation by varying granular properties like granular viscosity, frictional viscosity, and solids pressure has been performed. Simulated predictions were subsequently compared with experimental results in the case of Geldart A or B particles. Laminar flow behavior is also studied and coarse-grid simulation predictions were less realistic for laminar flow. This flow regime which although consumes less computational resources falls short for large-scale riser scale up. Flow regime in our simulation was fast fluidization and simulation predicts with minimum error near riser inlet. More specifically, granular viscosity, frictional viscosity and solids pressure for Type A particles predict with minimum error especially near riser inlet at a lower height. For Type B particles, these three solid properties correspond closely with experimental results near inlet at a lower height whereas, at a higher height, turbulence increases and simulation results deviate from experimental studies. Image 1 • A sub-grid drag model has been used. • Coarse-grid two-fluid simulation has been performed. • Laminar and turbulent flow behavior has been compared. • Granular property effect on flow behavior has been systematically assessed. [ABSTRACT FROM AUTHOR]

• A Nusselt correlation for gas-particle transfer in packed bed and fluidized bed. • Particle-resolved data points (ε = [0.35, 1], Re p = [0, 550]) from open sources. • To validate the Nusselt correlation. • The correlation integrated with a macroscopic CFD reactor model. Particle-resolved (PR) high-fidelity simulations, e.g., direct numerical simulation (DNS), have emerged as a powerful tool to precisely capture the full details of complex fluid-particle heat and mass transfer behaviors. The captured information can be used to constitute closures for unresolved conservation equations. However, such simulations are commonly performed under a specific variety of operating conditions. To broaden the range of closure model applicability, this fundamental study develops an enhanced correlation for the gas-particle transport rate in terms of Nusselt (Sherwood) number via collecting data points (ε = [0.35, 1], Re p = [0, 550]) from open sources. The collected data are predicted with a mean relative error of 9.3%. The extended correlation is then systematically validated by comparison with experimental data and PR-DNS results. Finally, the correlation is applied to integrate with a macroscopic computational fluid dynamics (CFD) reactor model. Validation results reveal an enhanced improvement in mass and heat transfer predictions. Moreover, the overall thermal and reactive behaviors computed from the coupled reactor model achieve reasonably good accordance with PR-DNS predictions over various process conditions. The developed correlation is hopeful to improve the accuracy of coarse-grained simulation of interphase heat and mass transfer accompanied by heterogeneously catalyzed chemical reaction. [ABSTRACT FROM AUTHOR]

• A material-property-dependent sub-grid drag modification is developed. • The newly constituted correction model is verified by highly-resolved simulation results. • Results reveal an essential dependence of sub-grid drag correction on material properties. • Hydrodynamic validation predictions achieve good accordance with various experiments. Developing, verifying and validating sub-grid methods is of crucial significance for enabling accurate coarse-grained two-fluid modeling of rapid gas-fluidized flows. However, very few studies in the literature so far have been focused on how the sub-grid modification depends on material properties. As an extension of previous sub-grid efforts, this fundamental investigation attempts to derive a material-property-dependent drag modification based on generated data from an initially homogeneous state of periodic gas-particle suspensions. The newly constituted model is then verified by highly-resolved two-fluid simulation results. We further validate the accuracy of model predictions via systematic assessments to experimental results that encompass a wide variety of material properties in five three-dimensional large-scale circulating fluidized bed (CFB) risers. Besides, we introduce a deviation index (DI) to quantify the predictive capability of the extended model. Computational results demonstrate an essential dependence of drag correction on material properties as an additional factor. Hydrodynamic validation predictions achieve satisfactory accordance with experiments. The current model is potential to serve as a more general tool for efficiently reducing the number of pilot-scale tests and effectively designing and controlling industrial process devices. [ABSTRACT FROM AUTHOR]

Highlights • A comprehensive validation study of the developed model to its predictability is conducted. • The computed results accord with the experimental data well over various flow regimes. • The computation efficiency via the developed sub-grid model can be significantly improved. • To capture the macroscopic flow features reasonably, an additional wall correction is not needed for the developed model. Abstract Development and validation of sub-grid models are of pivotal importance for coarse-grid two-fluid modeling of gas-particle fluidization. In prior study (Zhu et al., 2018, Chem. Eng. Sci. 192, 759–773), we developed an effective three-marker sub-grid drag model to consider the local heterogeneity in gas-particle flows. In this study, we perform a comprehensive 3D hydrodynamic validation analysis of the developed model to its predictability. Specifically, the validation covers more flow situations with respect to rapid, turbulent and bubbling fluidization. Besides, we introduce a simplified wall correction factor for assessing how the bounding walls impact on flow hydrodynamics. Computational results accord well with the experimental data over various flow regimes. The developed model can adequately capture the macroscopic flow properties without an additional wall modification. Compared with the fine-grid two-fluid modeling using the uniform drag model for a lab-scale riser, approximately 44 times speedup in computational time is achieved via the developed model. A much more significant reduction in computational time can be consequently expected for industrial-scale reactors. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • An effective three-marker drag model is developed for considering the meso-scale effect on the hydrodynamic predictions. • The effect of uniform drag inputs on the derived three-marker drag correlation is quantified. • A comprehensive comparison between several typical sub-grid models and present work is implemented. • Coarse-grid validation reveals that the developed model can significantly improve hydrodynamic predictions. Abstract The effect of meso-scale structures on hydrodynamic predictions is not considered in the classically uniform drag models when the coarse grid is used. To address this issue, this study tries to develop an effective three-marker drag correlation via straightforward sub-grid modeling, which accounts for a parabolic spatial concentration distribution within a computational grid. The reliability and accuracy of the developed model is then assessed in detail. How the uniform drag inputs affect the derived sub-grid correction is quantified for the first time. Besides, a comprehensive comparison between several typical sub-grid models and present work is implemented. Results reveal a systematic dependence of our drag modification on the concentration gradient as an additional marker. Coarse-grid hydrodynamic validation shows that the developed model yields a fairly improved agreement with experiments under various operating conditions in a 3D turbulent fluidized bed. Furthermore, results demonstrate that the present model using different uniform drag inputs still can exhibit satisfactory performance. The developed model is able to resolve the heterogeneous flow behavior both cheaply and adequately, which is potentially applied for industrial reactor design and optimization. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • The proposed model is validated using the experimental and empirical data. • Three typical spatial distributions of pore diameter and porosity are investigated and evaluated comprehensively. • A decreasing pore diameter and porosity toward the particle core is the optimal distribution. • A comprehensive sensitivity analysis is performed. Abstract This modeling study investigates the influence of spatially distributed pore size and porosity on diffusional and reactive features inside the methanol-to-olefin (MTO) porous catalyst particle. The model developed in this study integrates mass, momentum and heat balance equations, spatial pore size and porosity distribution models, multicomponent diffusion and lumped kinetic models. The proposed model was first validated by using the experimental and empirical data. The simulation results demonstrated that the pore diameter and porosity that decrease toward the particle core is the optimal distribution for the MTO catalyst particle. Subsequent parametric sensitivity analysis indicated that the temperature plays the most significant role in the effectiveness factor. The smaller pore diameter favors the larger ratio of the ethylene to the propylene. Comparing with the traditional trial-and-error methods, the proposed model is simple but effective, which is valuable for the design and optimization of porous catalyst particles. [ABSTRACT FROM AUTHOR]

• The cohesive gas–solid flows coupled with a polymerization reaction are simulated. • The effect of cohesion on hydrodynamic and thermal behaviors is quantified. • The formation of hot spots in the agglomerates is detailed analyzed. • How the cohesion model parameters affect the particle agglomeration is revealed. The cohesive particles are commonly encountered in high temperature polymerization fluidized bed reactors. However, detailed studies on the effect of cohesiveness on the hydrodynamics, heat transfer, and reaction characteristics in such reactors have been rarely reported. In this work, a CFD-DEM approach coupled with solid bridge force model and polymerization reaction kinetics model is established to simulate the reactive gas–solid flows with cohesive particles. The results demonstrate that cohesive particle agglomeration significantly increases the inhomogeneity of concentration and velocity fields, and hinders particle circulation. The hindered particle circulation further results in pronounced temperature inhomogeneity. Moreover, the local hot spots are readily formed in the agglomerates, which expand and deteriorate rapidly if not controlled promptly. Besides, how the cohesion model parameters, namely contact time and maximum cohesive force limitation, affect the onset temperature and the severity of particle agglomeration is revealed. The established model extends the particle-scale study of cohesive gas–solid flows to reactive systems. [ABSTRACT FROM AUTHOR]

Multiscale mixing phenomena in stirred-tank polymerization reactors are mainly caused by stir agitation, which performs a key function in macroscopic and microscopic flow fields. Both macroscopic and microscopic flow fields interact with each other and significantly affect the microstructure and product distribution of the resultant polymers. In this work, a computational fluid dynamics model combining the moment method used in the polymerization engineering field is implemented and validated using open data. Multiscale properties are characterized in terms of macroscopic mixing fields and the polymer microscopic structure of the atom transfer radical copolymerization system of methyl methacrylate and 2-(trimethylsilyl) ethyl methacrylate. Agitation in a 3D stirred tank is also thoroughly studied by using the multiple reference frame approach, and the effects of several important para­meters, such as impeller speed, impeller types, and feeding position, on the macroscopic and microscopic flow fields are investigated on the basis of the validated model. Interdependent relationships among agitation, multiscale flow fields, and polymerization are described clearly. The results highlight the function of stirring and provide useful guidelines for the scale-up of stirred-tank polymerization reactors. [ABSTRACT FROM AUTHOR]

Gas-particle flows can be well described by highly resolved simulations (HRS). Limited by the daunting computational cost, HRS at scale remains infeasible. Many methods are proposed to strike tradeoffs between accuracy and computational cost. Here, we design a machine learning (ML) based alternate mode to accelerate HRS without sacrificing accuracy. Spatiotemporal samples (~1.3 × 106) generated from two-fluid model-based HRS of gas-particle flows are trained for developing artificial neural network (ANN) and long short-term memory (LSTM) models. Simple time-series predictions consisting of repeated ANN iterations can accurately predict the flow field in ~10−3 s. Hybrid accelerations combining CFD and the offline trained ML in time scale can approximate to the time-series highly resolved flow fields within 1% error, saving 40% computing time. This work may contribute to a new transformative paradigm that how scientific computing can leverage ML to improve gas-particle simulations without new device requirements. [Display omitted] • Gas-particle flow fields are well predicted via ANN and LSTM. • Simple ML can accurately predict the flow field in ~10−3 s. • Highly resolved simulations are accelerated by combining CFD & ML within 1% error, saving 40% computing time. • Accelerated simulation is deployed on the CPU devices supporting multi-core parallel computation. [ABSTRACT FROM AUTHOR]

The molecular properties of polymers are greatly influenced by operation parameters during polymerization in reactors. Since operation parameter distributions in reactors also result in molecular property distributions, polymerization bridges the gap between molecular properties and operation parameters. The combination of the computational fluid dynamics technology with the method of moments to form a uniquely coupled model was used to describe multiscale mixing fields in the reactor. The coupled model was validated by open experimental data, and the effects of polymerization kinetics on macroscopic and microscopic fields were investigated numerically. Also, the coupled model was applied to numerically predict the impacts of some key operation conditions on the main macroscopic flow field parameters and polymer molecular properties. [ABSTRACT FROM AUTHOR]

In this work, a three-dimensional (3-D) filtered two-fluid model (TFM) was developed to describe the gas–solid flow behavior in a large-scale methanol-to-olefins (MTO) fluidized bed reactor (FBR). The cold-model flow behaviors were characterized successfully via the filtered TFM with a coarse grid. A coarse-grid sensitivity test was first carried out, and the filtered model was testified using predictions from classical models and the experimental data. Moreover, four drag models have been incorporated into the TFM for evaluating the effectiveness of these models at the same coarse-grid condition. Subsequently, the effects of some important model parameters including solid stresses, wall corrections and filter size on the flow behaviors were also investigated numerically. Finally, the filtered model was applied to predict the effects of the operating gas velocity, distributor shape and solid particle size. The results suggested the effectiveness of the sub-grid models for simulating large-scale MTO FBRs at coarse-grid conditions. This study further confirmed that the filtered drag coefficient correlation plays a significant role in capturing flow behaviors and the filter size is nearly independent on the grid size when the filter size is larger than or equal to twice the grid size. The simulation results by coarse-grid also show that the catalyst particles are easier to be fluidized with the increase of the operating gas velocity. It is also found that a triangle-shaped distributor strengthens the mixing behaviors and weakens the clustering of the near-wall regions. Additionally, our study indicates that the clustering phenomena near the wall regions are more obvious with the decrease of the catalyst particle size. [ABSTRACT FROM AUTHOR]

Smart polymeric surfaces with switchable oil/water wettability are ideal candidates for oil/water separation, which still suffer from significant restrictions in practical separation applications. Appropriate fabrication method should be explored to devise and mass produce smart polymeric membranes. Herein, we prepared two smart membranes through solution-casting method and electrospinning technology, respectively, based on temperature-responsive copolymer poly(methyl methacrylate)-block-poly(N-isopropylacrylamide) (PMMA- b -PNIPAAm). According to the thermo-responsive component PNIPAAm, both membranes exhibited temperature-modulable oil/water wettability. Electrospun fibrous membrane owned an extended transition range of oil/water wettability compared to polymer solution-casting membrane because of its 3D network porous structure of the random entangled fibers. The as-prepared membranes realized gravity-driven oil/water separation with efficiency higher than 98% through regulating temperature. Solution-casting membrane exhibited a water flux of about 6200 L h −1 m −2 and an oil flux of about 1550 L h −1 m −2 . By contrast, characteristics of the high porosity and the large surface-to-volume ratio made the electrospun fibrous membrane achieve higher fluxes of about 9400 L h −1 m −2 for water and about 4200 L h −1 for oil. Electrospinning is a powerful and cost-effective method to construct smart membrane with excellent wetting property and separation performance. [ABSTRACT FROM AUTHOR]

• Applicability of different mesoscale drags for predicting hydrodynamics over all flow regimes. • Applying the optimal drag model to design bed internals and quantify bed size effects. • The proposed nature-inspired snowflake-type internal significantly improves fluidization quality. • Proposing a preliminary correlation to quantify the bed size-dependent effect. This work systematically investigates the applicability of our recently developed three mesoscale drag models for predictions of hydrodynamics over extensive flow regimes ranging from bubbling, turbulent, rapid to full-loop fluidization. Subsequently, we try to apply the suitable mesoscale model for designing bed internals and quantifying bed size effects in a dense turbulent fluidized bed reactor. It is found that the optimized nature-inspired snowflake-type internal scheme contributes to breaking up the bubbles effectively and thereby weakening the degree of the particle clustering near the wall significantly. This phenomenon can enhance the uniform solid hold-up distribution (A ∼25% reduction of its nonuniformity) and improve the fluidization quality. Moreover, the bed size evidently affects the gas–solid fluidization characteristics and we thereby propose a preliminary correlation to quantify this size-dependent effect. This work may contribute to facilitating the CFD design practice of multiphase reactors from an art to science. [ABSTRACT FROM AUTHOR]

[Display omitted] • Mesoscale drag and solids stress models are developed via a DL algorithm. • Validation reveals the importance of mesoscale solids stress. • Optimal conditions for anisotropic closure are obtained and validated. • The use of DL does not significantly increase the computational cost. This study develops filtered two-fluid model (fTFM) closures by coupling computational fluid dynamics (CFD) and deep learning algorithm (DL) for enabling coarse-grid simulations at reactor scales. Mesoscale drag, solids pressure and viscosity are modeled using an isotropic or anisotropic method. Subsequently, a priori analysis and a posteriori analysis of the present models along with other previously proposed closures are conducted. Comparison with the experimental data covering a broad range of operating conditions indicates that the mesoscale solids stress can be neglected in bubbling and turbulent fluidization regimes. However, the contribution of solids stress is clearly not insignificant at very low superficial gas velocities. Moreover, the drag model considering the anisotropy shows better prediction performance in the turbulent fluidization regime. In short, the present study develops and validates a DL-fTFM coupling algorithm applicable for gas-particle simulations. [ABSTRACT FROM AUTHOR]

The gas-solid fluidized bed is a complex multiscale system with diverse mesoscale structures such as bubbles and particle clusters. The Euler-Euler two-fluid model is one of the most popular methods in simulating this kind of system. However, when using coarse grids, the mesoscale structures involved can hardly be characterized. In this study, a new quasi-three-phase method was proposed to properly account for the mesoscale structures by using three phases (bubble phase/solid phase/emulsion phase) to represent the gas-solid fluidized bed, and comparative simulations were performed under different gas velocities. It was found that the simulation could reasonably predict the flow changes from bubbling fluidization to turbulent fluidization. The predicted gas velocity at the flow pattern transition is close to that calculated by the empirical equation concerning the bed pressure fluctuation, and the predicted solids fraction distribution fits well with the experimental data in the literature. [Display omitted] • Both bubbles and particle clusters are considered simultaneously. • Application of three-fluid model in gas-solid two-phase flow is feasible. • Three-fluid model reveals well the flow pattern transition of FBR. • The simulation using the classical drag model can match the experimental data. [ABSTRACT FROM AUTHOR]

[Display omitted] • 3D coarse-grid CFD for pilot-scale biomass pyrolysis VPU reactor. • Sub-grid models incorporated into CFD model for meso-scale structure. • Study of extensive types of different gas inlet, catalyst feed and outlet structures. • The effect of geometric configurations on RTD and temperature is complex. The effect of geometric configurations on flow hydrodynamics, heat transfer, and residence time distribution (RTD) in a pilot-scale biomass pyrolysis vapor phase upgrading (VPU) reactor is comprehensively studied by numerical simulations. More specifically, three types of carrier gas structure, three types of particle feed structure, and five types of outlet structure are included in the present study. The results demonstrate that the effect of geometric configurations on heat transfer and RTD is much more pronounced than that on flow hydrodynamics such as the axial particle distribution, probably due to the low particle inventory. In this case, it is necessary to verify the difference of the temperature field in the grid independence analysis in addition to flow dynamics. Furthermore, we find that the carrier gas inlet and particle feed have an important influence on the particle distribution at the bottom of the reactor and thus affect the back-mixing behavior at both the bottom and outlet. As a consequence, such back-mixing flows further affect the temperature field and RTD substantially. Moreover, reducing the abrupt structure contributes to the catalyst particles well-distributed at the bottom of the reactor. This can reduce the mean residence time and variance, thereby decreasing the particle and gas temperature in the reactor. This work has a potential to provide a feasible guideline for biomass pyrolysis VPU reactor design and optimization. [ABSTRACT FROM AUTHOR]

• Quantifying the effects of HDCs on filtered mesoscale predictions. • Significant differences between the Wen-Yu drag closure and the DNS based HDCs. • Wen-Yu drag applicable for filtered modeling of dilute flows while DNS-based HDCs applicable for moderate/dense flows. • The enhanced drag closure is demonstrated to be more generic. Filtered mesoscale model can be formulated from highly-resolved continuum or discrete simulations. The embedded microscopic homogeneous drag closure (HDC) is of key importance in determining the reliability and accuracy of such simulations. This work investigates the effects of sub-input HDCs on filtered mesoscale predictions using highly-resolved simulations. Quantitative comparisons directly reveal that there are significant differences between the commonly-practiced Wen-Yu drag closure and the direct numerical simulation (DNS) based HDCs, especially for moderate and dense gas-particle flows. Moreover, the HDCs from DNS of static particles agree well with the benchmark data from DNS of dynamic gas-particle flows at very low Reynolds numbers for ε s > 0.05 ~ 0.10 while Wen-Yu drag is more applicable for the remaining range. Regarding that DNS is commonly implemented over a specific range of operating conditions, an enhanced HDC via refitting more elaborate high-fidelity DNS data (ε s = [0.01, 0.65], Re s = [1, 1000]) from literature is proposed and analyzed. [ABSTRACT FROM AUTHOR]

• Review explores bubble dynamic behavior and mass transfer. • Mechanisms, modeling, and turbulence effects are discussed. • Identifies challenges and proposes avenues for further research. • The use of machine learning is suggested as a promising new approach. Bubbly flow is a prototypical two-phase flow problem. The dynamic behavior of bubbles within a reactor is intrinsically linked to their transport, distribution, and mass transfer, all of which directly influence reactor productivity. This review provides a comprehensive analysis of the kinetics of bubble behaviors and mechanisms of gas–liquid mass transfer. Our exposition delves deeply into the intricate dynamics of bubbles behaviors, the complex correlation between bubble behavior and mass transfer, and the modeling of both these phenomena. Specifically, we explore (1) the dynamic mechanisms that govern bubble dynamic behaviors, encompassing path instability, breakup, and coalescence, (2) the inherent correlation between bubble dynamic behavior and mass transfer, and (3) the modeling of bubble behavior and mass transfer processes. These sections also discuss the impact of global turbulence and local turbulence on the bubble dynamic behaviors and mass transfer. Finally, we conclude by summarizing the challenges inherent in the study of bubble dynamic behaviors and mass transfer, and propose avenues for further research. The advent of machine learning promises to infuse fresh vigor into traditional investigations of bubble dynamic behaviors and mass transfer. [ABSTRACT FROM AUTHOR]

[Display omitted] • Well-resolved CFD-DEM simulations of bidisperse gas-solid flows are performed. • Filtered models of fluid-particle drag and heat transfer corrections are developed. • The corrections are almost independent of filter size in this work. • The Sauter mean diameter is adopted to quantify the effect of bidispersity. • The effectiveness of the model is preliminarily validated in monodisperse systems. This work extends filtered models to investigate the influence of particle polydispersity on the filtered fluid-particle drag and heat transfer behaviors based on well-resolved computational fluid dynamics-discrete element model (CFD-DEM) simulations. By systematically filtering the CFD-DEM simulation data, it is found that the markers used for the monodisperse systems, (i.e., the filtered slip velocity and the gas phase pressure gradient for the drag correction; the filtered interphase temperature difference for the heat transfer correction) are indispensable in the bidisperse systems. Furthermore, the dependence of the filtered corrections on the particle size ratio and volume fraction ratio is identified. The increase in the proportion of small particles generally corresponds to the reduction of drag and interphase heat transfer corrections. The Sauter mean diameter is applicable to quantify the effect of particle bidispersity. Eventually filtered models of fluid-particle drag and heat transfer corrections for the bidisperse systems are developed. [ABSTRACT FROM AUTHOR]

Gas–liquid–solid fluidized bed reactors (FBRs) are of considerable importance as proved by their widespread use and popularity in various industrial processes, which results in extensive theoretical analyses, experimental investigations and computational fluid dynamics (CFD) studies in the past. Many reviews have been published concerning the theoretical and experimental works of three-phase FBRs while little effort is on the CFD approach of three-phase fluidization system. This review attempts to summarize and analyze CFD simulations for these three-phase fluidization systems from two aspects: the fundamentals and their applications, which are of paramount importance to the formulation of strategies for scale-up, design and control of three-phase FBRs. The fundamentals of CFD approach in the three-phase FBRs are focusing on various multi-scale models, such as pseudo two fluid model, three fluid model, two fluid model + discrete particle method (DPM), CFD + the front tracking (FT)/front capturing (FC) + DPM etc. and the coupling fundamental theories of interaction forces. With the emphasis on the hydrodynamics of individual phase at macroscopic or microscopic level, the applications of CFD approach for three-phase fluidization system are analyzed. This review also proposes that future emphasis and challenges of CFD simulation for three-phase FBRs are to present specific and appropriate closure laws for interphase momentum exchange, incorporate chemical reactions transport phenomena properties into numerical models, and develop measurement techniques and provide more experimental data for three-phase systems. [ABSTRACT FROM AUTHOR]