Although great progress has been made in modeling the gas fluidization of Geldart B and D particles and dilute gas−solid flow by standard Eulerian approach, researchers have shown that, because of ...the limitation of computational resources and the formation of subgrid-scale (SGS) heterogeneous structures, Eulerian model with a suitable SGS model for constitutive law is necessary to simulate the hydrodynamics of large-scale gas-fluidized beds containing Geldart A particles. In this article, a state-of-the-art review of Eulerian modeling of Geldart A particles in gas-fluidized beds is presented. The available methods for establishing SGS models are classified into six categories, that is, empirical correlation method, scaling factor method, structure-based method, modified Syamlal and O’Brien drag correlation method, EMMS-model-based method, and correlative multiscale method. The basic ideas of those methods, as well as their advantages and disadvantages, are reviewed. Finally, directions for future research are indicated.
Gas-solid fluidization technology has been commercialized in many industrial applications since its implementation in the fluid catalytic cracking process in the early 1940s, however, the ...understanding of the complex hydrodynamics of gas-solid flow inside fluidized beds is still far from satisfactory due to its dynamic and multiscale nature, especially, the critical role played by mesoscale structures. In recent decades, computational fluid dynamics (CFD) has become an important toolkit in understanding the physics of complex gas-solid flow and then for the scale-up, optimization and design of gas-solid fluidized bed reactors. This article presented a pedagogical and comprehensive review to the Navier-Stokes order continuum theory for CFD simulation of the hydrodynamics of gas-solid fluidization, without taking the effects of heat and mass transfer as well as chemical reactions into consideration. A concise introduction to the methods for multiscale CFD simulation of gas-solid fluidization was firstly provided, which include direct numerical simulation, (coarse-grained) discrete particle method, kinetic method, continuum method and mesoscale-structure-based multiscale method. The underlying postulates of homogeneous continuum theory that assume the structure inside each computational cell is (nearly) homogeneous were then examined, followed by an overview of the constitutive relationships available in literature, including the particle phase stress models, the interphase drag models and the models for particle-wall interactions. The importance of mesoscale structures that take the form of gas bubbles and/or particle clusters and streamers in the quantification of the hydrodynamics of gas-solid flows was then addressed, and the explicit resolution (or highly resolved) method and implicit modeling method for quantifying the effects of mesoscale structures in continuum modeling of gas-solid fluidization were highlighted. Coarse grid simulation of large scale fluidized beds with proper mesoscale, sub-grid scale or turbulent models for constitutive relationships were then reviewed, focusing on the filtered method, turbulence modelling and heterogeneity-based method where the energy-minimization multi-scale (EMMS) based method is a representative. Finally, the scope for the further research areas is described.
The Energy Minimization Multi-Scale (EMMS) drag model, using Sauter mean particle diameter to represent real particle size distribution, has proven to be effective in improving the accuracy of ...continuum modeling of gas–solid flow. Nevertheless, mixing and segregation characteristics in circulating fluidized bed (CFB) risers are very important in many situations, which necessitates the explicit consideration of the effects of particle size distribution on the bed hydrodynamics. To this end, an attempt is made to extend the EMMS drag model to binary gas–solid system, where four input parameters that can be obtained from computational fluid dynamics (CFD) simulation, including two slip velocities between gas and each particle phase and two particle concentrations of each phase, are used to solve the proposed EMMS drag model. Heterogeneous indexes, which are used to modify the drag correlation obtained from homogeneous fluidization, are then predicted and fed into multifluid model (MFM) to predict the dynamical behavior of mixing and segregation of binary gas–solid flow in a CFB riser. The effects of different drag force models, kinetic theories and particle–particle drag force models are also systematically evaluated. It was shown that (i) MFM with the proposed EMMS drag model and the kinetic theory developed by Chao et al. (Chemical Engineering Science 2011, 66: 3605–3616) is able to correctly predict the mixing and segregation pattern in the studied riser, while MFM with homogenous drag forces and the simplified kinetic theory available in commercial software FLUENT completely fails; and (ii) with or without particle–particle drag force has a substantial influence upon the particle behavior.
•An EMMS drag model is developed for binary gas–solid flow.•The effect of kinetic theory and particle–particle drag model are evaluated.•Segregation characteristics are studied using multifluid model.
Gas–solid flows have been numerically investigated by various multiphase models, none of which is suitable for all the problems encountered in industries. Different multiphase models have been chosen ...by different researchers to meet their specific requirements; therefore, it is highly desirable to have a comprehensive understanding of the merits and drawbacks of these models. In this study, three existing multiphase models, including a two-fluid model (TFM), a dense discrete particle model (DDPM) and a combined computational fluid dynamics and discrete element model (CFD-DEM) method, are compared by simulating the flow patterns of impinging particle jet in a channel. Depending on the solid concentration used, the particle jets can either merge into a single jet or cross through each other (particle trajectory crossing effect) when they are impinging. The TFM and the DDPM methods have the advantage of less computational demanding compared to the CFD-DEM method, with the cost of more uncertainties. Using the simulation results obtained from the CFD-DEM method as the benchmark data, it was shown that (i) the TFM fails to predict the well-known particle trajectory crossing effect in any cases as in previous studies (Desjardins et al., Journal of Computational Physics 2008, 227, 2514–2539) but can reproduce the merging cases reasonably well; (ii) the DDPM fails to predict the cases where the two particle jets are emerging due to the over-simplified treatment of particle–particle interactions, highlighting the requirement of a proper way to represent the realistic particle–particle interactions and the importance of volume exclusion effect (the particles cannot overlap) in dense gas–solid flows; and (iii) quantitative comparisons show there are major differences between the results predicted by the three models, highlighting the requirement of further improvement of DDPM and TFM.
TFM (a) can predict the merging gas–solid flow as in CFD-DEM (c), where DDPM (b) fails to predict it. The reason is that significant overlap between particles is allowed in DDPM which results in the unphysical phenomenon, as proved by significantly decreasing the value of Kn in CFD-DEM (d). Display omitted
•The TFM, DDPM and CFD-DEM methods are compared.•TFM fails to predict the particle trajectory crossing effect.•DDPM fails to predict the jets merging phenomenon.•Quantitative differences exist between TFM, DDPM and CFD-DEM.
•A new CFD-DEM-IBM method was proposed and validated.•CFD-DEM-IBM method was used to simulate gas-solid flow in complex geometries.•Cartisian grid method and immersed boundary method were used to ...treat complex geometries.
The use of CFD-DEM method to accurately simulate gas-solid flows in complex geometries is challenging, mainly due to the complexity related to the use of unstructured computational grids. In order to solve this problem, researchers have simulated gas-solid fluidized beds with complex geometries using CFD-DEM-IBM method with Cartesian grids. In present study the gas-solid flows in complex geometries were simulated using Cartesian grids following the basic idea of CFD-DEM-IBM method (De Jong et al., 2012), where the interactions between gas phase and complex geometries were firstly modelled using the immersed boundary method (IBM) implemented by Tuković and Jasak (2012) in OpenFOAM®. It was found that the computational efficiency is quite low. To improve the efficiency of the CFD-DEM-IBM solver, a new IBM method was then proposed by removing the neighboring immersed boundary cells from the interpolated extended stencil in the reconstruction of the velocity and pressure fields near the wall, and further proposing a new zero-gradient boundary condition to replace the original Neumann boundary condition for reconstructing the pressure field. Single-phase flow past a stationary cylinder, single-phase pipe flow, gas-solid flow in a cylindrical fluidized bed and fluidized bed with immersed tubes were simulated with four different IBM imposition methods to assess the accuracy and efficiency of sharp-interface CFD-DEM-IBM solver. It was shown that (i) the results of CFD-DEM-IBM simulations agree well with the reported experimental, analytical and/or numerical results available in literature; and (ii) the computational efficiency of newly proposed CFD-DEM-IBM solver is one or two order of magnitudes faster than that of the original IBM of Tuković and Jasak (2012) in OpenFOAM®, due to the fact that internal iterations are not needed anymore during the reconstruction of velocity and pressure fields.
Gas–solid two-phase flow in CFB risers is characterized by the clustering of solid particles producing dynamical multi-scale structures, and how to quantify such heterogeneity is a critical yet ...unsolved issue. Recently, incorporating the energy minimization multi-scale (EMMS) model with Eulerian approach has obtained encouraging results for simulating the hydrodynamics in CFB risers. However, owing to the cluster diameter correlation used, the present model is still limited to the simulation of Geldart A particles. In this study, a stochastic geometry approach named doubly stochastic Poisson processes is used to analyze the fluctuation characteristics of solid concentration in CFB risers, which provides a mean to define the solid concentration inside clusters. The predicted results are validated by experimental data available in literature, and a revised cluster diameter correlation is then proposed for EMMS model previously developed for cocurrent-up gas–solid flow. Following our previous studies, the EMMS model thus improved is incorporated into an Eulerian–Eulerian description of gas–solid flow as a sub-grid scale model for inter-phase drag force, with which the hydrodynamics of both Geldart A and Geldart B particles in CFB risers are simulated. It is shown that the experimentally found S-shaped axial voidage profiles and the choking phenomenon can be well predicted. The computed one-dimensional slip velocities decrease toward the top of the risers and increase with decreasing cross-sectional averaged voidages. The experimentally found dependence of the root mean square of the solid concentration on its mean value at a given position is also well predicted.
Current research on personal protective equipment (PPE) detection has mainly focused on hard hats, overlooking the detection of reflective clothing. Therefore, this study aims to address this ...research gap comprehensively. We achieve this by creating a novel dataset using semi-automatic labeling techniques and enhancing the YOLOv5 model. The dataset consists of four categories, assessing the presence of hard hats and reflective clothing. Additionally, we introduce an attention mechanism and an improved loss function to tackle challenges related to detecting reflective clothing and overlapping detection frames. Through extensive multi-model comparison experiments, our improved model, AL-YOLOv5, outperforms the baseline model with remarkable advancements of 0.9 AP in the data-limited category and 0.4 mAP overall. Notably, our improved model shows substantial progress in detecting reflective clothing, significantly reducing false detections, and improving overlapping bounding frames. In conclusion, this study contributes to PPE detection accuracy through a novel dataset and an improved model.
•Unified EMMS-based constitutive relation was proposed.•A EMMS-based particle stress model was proposed.•The effect of mesoscale structure was considered in the constitutive relation.•The predicted ...granular temperature, pressure and viscosity are agreed with experimental data.
Energy minimization multi-scale (EMMS) drag model has been demonstrated to be very successful in quantifying the effect of mesoscale structure on the effective interphase drag force of heterogeneous gas-solid flow in circulating fluidized bed (CFB) risers, however, a corresponding model for the effective particle phase stress is not yet available. To this end, an EMMS drag model was extended to predict the granular temperature of particles inside the dilute phase and the dense phase as well as the granular temperature of clusters. A model for the effective particle phase stress was then developed based on the concept of multiscale analysis in EMMS model. It was shown that the experimentally measured granular temperature, granular pressure and granular viscosity as a function of mean solid concentration can be predicted reasonably well. The agreement demonstrates its effectiveness in the quantification of the effect of mesoscale structure on the particle phase stress, thus establishing a unified EMMS-based model for the constitutive law of heterogeneous gas-solid flow in CFB risers.
High-resolution Eulerian simulation has recently emerged as an effective approach for studying the mechanics of heterogeneous gas–solid flow. In this study, it is used to study the characteristics of ...RMS of solid volume fraction fluctuation and particle clustering structures in a CFB riser. It was shown that the experimentally founded RMS of solid volume fraction fluctuation variation with local mean solid volume fraction can be well predicted and the experimentally measured particle clustering characteristics, including the solid volume fraction inside cluster, cluster time fraction, cluster frequency, cluster existence time, vertical and horizontal cluster velocity and vertical cluster size, can be qualitatively predicted by high-resolution Eulerian simulation.
Addressing the challenges of intelligent decision support within traditional management approaches, this study presents a novel conceptual framework for enhancing sustainability in construction ...behavioral safety management. By integrating Bayesian network (BN) modeling and ontology, our framework enables robust decision-making and fosters knowledge sharing. Key to our approach is the encoding and storage of BN-modeled properties within the ontology, facilitating a formal representation of behavioral safety knowledge. Leveraging SWRL rules for reasoning and judgment, our study effectively elucidates causal relationships and interactions within the behavioral safety system. Rigorous verification, including consistency checks and task evaluations, ensures the reliability and validity of our ontology. Ultimately, our framework facilitates seamless communication and retrieval of traditional construction behavioral safety knowledge, underpinning sustainability efforts through the integrated BN model and ontology storage and sharing mechanism.
