Multiphase Computational Fluid Dynamics Research Articles

Enhancing CO2 capture efficiency: Computational fluid dynamics investigation of gas-liquid vortex reactor configurations for process intensification

This study employs non-thermal Computational Fluid Dynamics (CFD) simulations to explore the efficacy of a gas–liquid vortex reactor (GLVR) for intensifying CO2 capture. The investigation concentrates on the multiphase flow and mass transfer behavior in diverse GLVR experimental units. Employing a multiphase Euler-Euler CFD model integrated with a Population Balance Model (CFD-PBM), a mass transfer model, and reaction kinetics, allows us to accurately simulate the reactive absorption of CO2 into aqueous Monoethanolamine (MEA). Experiments are conducted using a 30 wt% MEA solution for CO2 absorption, serving the purpose of model validation. This comprehensive approach enables a simulation of complex dynamics within the GLVR, emphasizing bubble breakage, coalescence, and reactive mass transfer processes. Examining bubble size distribution, pressure drop, CO2 absorption efficiency, and energy input systematically across various reactor geometries and operational conditions, our findings demonstrate that an optimized GLVR configuration significantly enhances CO2 absorption compared to the original design. Furthermore, the optimized GLVR outperforms state-of-the-art process intensification equipment in terms of CO2 absorption rate per unit reactor volume and energy efficiency.

Numerical Simulation of Pipeline Scour and Sedimentation around Submerged Pipelines with an Open-Source Multiphase-CFD Model

This paper presents a comprehensive study on pipeline scour and sedimentation phenomena using an open-source multiphase Computational Fluid Dynamics (CFD) model. The research focuses on understanding the complex interactions between fluid flow, sediment transport, and scour formation around submerged pipelines. The proposed analysis aims to enhance the understanding of scour development and sedimentation deposition, which is crucial for the design, operation, and maintenance of various engineering structures, including offshore pipelines and underwater infrastructure. The results show that the model exhibits the ability to compute sediment transport without depending on traditional assumptions related to bed-load and suspended-load layers. The simulation results affirm the model's proficiency in replicating the underlying mechanisms accountable for the onset of these processes, notably seepage flow and piping. Furthermore, this model can successfully depict the vortex phenomenon, which promotes the accumulation of sediment around the pipe. This phenomenon arises from the contrast in pressure between the centre of the vortex and the pressure exerted on the sediment beneath it.

Capturing mesoscale structures in computational fluid dynamics simulations of gas‐solid flows

AbstractMultiphase reactors' performance depends on the mesoscale structures formed due to multiphase hydrodynamics. Examples of mesoscale structures include gas bubbles in a fluidized bed and particle clusters in a riser. Experimental investigation of these mesoscale structures is challenging and expensive. To this end, computational fluid dynamics (CFD) simulations are extensively employed; however, post‐processing CFD data to capture mesoscale structures is challenging. This article develops a density‐based spatial clustering of applications with noise (DBSCAN)‐based methodology to capture and characterize mesoscale structures from multiphase CFD simulation data. DBSCAN is an unsupervised machine‐learning algorithm, which requires the value of two hyperparameters. A simple technique to calculate these hyperparameters is provided and the performance of DBSCAN is assessed on CFD‐DEM simulations of bubbling fluidized beds and particle clustering. We demonstrate the computational complexity of DBSCAN to be , lower than the existing techniques, by testing its scalability on highly resolved grids (up to 100 million grid points).

Comparative Study of Droplet Diameter Distribution: Insights from Experimental Imaging and Computational Fluid Dynamics Simulations

The interfacial area between two phases plays a crucial role in the mass transfer rate of gas–liquid processes such as absorption. In this context, the droplet size distribution within the flow field of a droplet-based absorber significantly affects the surface area, thereby influencing the absorption efficiency. This study focuses on developing a computational fluid dynamics (CFD) model to predict the size and distribution of water droplets free-falling in a transparent square tube. This model serves as a digital twin of our experimental setup, enabling a comparative analysis of experimental and computational results. For the accurate measurement of droplet size and distribution, specialized experimental equipment was developed, and a high-speed camera along with Fiji software was used for the capturing and processing of droplet images. At the point of injection and at two different heights, the sizes and distributions of falling droplets were measured using this setup. The interaction between the liquid water droplets and the gas phase within the square tube was modeled using the Eulerian–Lagrangian (E-L) framework in the STAR-CCM+ software. The E-L multiphase CFD model yielded approximations with errors ranging from 11 to 27% for various average mean diameters, including d10, d20, d30, and d32, of the liquid droplets at two distinct heights (200 mm and 400 mm) for both nozzle plates. This comprehensive approach provides valuable insights into the dynamics of droplet-based absorption processes.

Enhancing Efficiency in Alkaline Electrolysis Cells: Optimizing Flow Channels through Multiphase Computational Fluid Dynamics Modeling

The efficient operation of alkaline water electrolysis cells hinges upon understanding and optimizing gas–liquid flow dynamics. Achieving uniform flow patterns is crucial to minimize stagnant regions, prevent gas bubble accumulation, and establish optimal conditions for electrochemical reactions. This study employed a comprehensive, three-dimensional computational fluid dynamics Euler–Euler multiphase model, based on a geometric representation of an alkaline electrolytic cell. The electrochemical model, responsible for producing hydrogen and oxygen at the cathode and anode during water electrolysis, is integrated into the flow model by introducing mass source terms within the user-defined function. The membrane positioned between the flow channels employs a porous medium model to selectively permit specific components to pass through while restricting others. To validate the accuracy of the model, comparisons were made with measured data available in the literature. We obtained an optimization design method for the channel structure; the three-inlet model demonstrated improved speed and temperature uniformity, with a 22% reduction in the hydrogen concentration at the outlet compared to the single-inlet model. This resulted in the optimization of gas emission efficiency. As the radius of the spherical convex structure increased, the influence of the spherical convex structure on the electrolyte intensified, resulting in enhanced flow uniformity within the flow field. This study may help provide recommendations for designing and optimizing flow channels to enhance the efficiency of alkaline water electrolysis cells.

Unsupervised machine learning of virus dispersion indoors

This paper concerns analyses of virus droplet dynamics resulting from coughing events within a confined environment using, as an example, a typical cruiser's cabin. It is of paramount importance to be able to comprehend and predict droplet dispersion patterns within enclosed spaces under varying conditions. Numerical simulations are expensive and difficult to perform in real-time situations. Unsupervised machine learning methods are proposed to study droplet dispersion patterns. Data from multi-phase computational fluid dynamics simulations of coughing events at different flow rates are utilized with an unsupervised learning algorithm to identify prevailing trends based on the distance traveled by the droplets and their sizes. The algorithm determines optimal clustering by introducing novel metrics such as the Clustering Dominance Index and Uncertainty. Our analysis revealed the existence of three distinct stages for droplet dispersion during a coughing event, irrespective of the underlying flow rates. An initial stage where all droplets disperse homogeneously, an intermediate stage where larger droplets overtake the smaller ones, and a final stage where the smaller droplets overtake the larger ones. This is the first time computational fluid dynamics is coupled with unsupervised learning to study particles' dispersion and understand their dynamic behavior.

NUMERICAL ANALYSIS OF A TURBULENT PLUNGING WATER JET

In the present study, we employed multiphase computational fluid dynamics analysis to investigate the mechanisms of air entrainment by plunging liquid jets. The ANSY-CFX commercial software program, which is based on finite-element analysis, was used in the numerical simulations. The effects of the exit velocity of the jet on the velocity distribution in the pool, bubble depth, and volumetric fraction of air were the extracted results of the simulations. In this article, we conducted verification analyses to compare the results obtained from our numerical runs to the results of a previously published experimental study. Good agreement was achieved between the numerical simulations and the experimental study.

The effects of ventilation conditions on mitigating airborne virus transmission

The effects of ventilation strategies on mitigating airborne virus transmission in a generic indoor space representative of a lobby area or information desk found in a hotel, company, or cruise ship are presented. Multiphase computational fluid dynamics simulations are employed in conjunction with evaporation modeling. Four different ventilation flow rates are examined based on the most updated post-COVID-19 pandemic standards from health organizations and recent findings from research studies. Three air changes per hour provide the best option for minimizing droplet spreading at reasonable energy efficiency. Thus, a higher ventilation rate is not the best solution to avoid spreading airborne diseases. Simultaneous coughing of all occupants revealed that contagious droplets could be trapped in regions of low airflow and on furniture, significantly prolonging their evaporation time. Multiphase flow simulations can help define ventilation standards to reduce droplet spreading and mitigate virus transmission while maintaining adequate ventilation with lower energy consumption. The present work significantly impacts how heat, air-conditioning, and ventilation systems are designed and implemented.

Realistic fuel spray modeling for gasoline direct injection engine applications

Fuel spray modeling plays a critical role during modern gasoline direct injection (GDI) engine development due to fuel injection’s dominant impact on engine performance and emissions as well as the complex physical processes involved. In engineering three-dimensional (3D) computational fluid dynamics (CFD) simulations, the liquid-phase fuel atomization, evaporation, and mixing are usually modeled with the discrete droplet model (DDM) adopting a Lagrangian approach for multiphase CFD simulations. To this end, general practices heavily depend on the reduced order characterization of the injector nozzle flow. However, such simplified injector modeling may lead to insufficient representations of the complex spray dynamics. To tackle this problem, this study proposes a novel workflow to numerically evaluate GDI sub-cooled and flash-boiling sprays under engine-relevant conditions using a side-mounted GDI injector together with real gasoline fuel properties. The workflow introduces a one-way coupling (OWC) method leveraging high-fidelity nozzle flow simulations to provide realistic boundary conditions to the Lagrangian injector model. The proposed workflow was first verified in a constant volume chamber (CVC) environment and then implemented in a practical GDI engine setup to study spray morphology, fuel-air mixing, and wall-wetting propensity. In addition, detailed comparison was performed between the OWC method and the conventional rate of injection (ROI) routine. Quantitative analysis of spray characteristics was conducted to highlight possible source of discrepancies of the conventional ROI method.

Effect of static magnetic field on the molten pool dynamics during laser powder bed fusion of Inconel 718 superalloy

Recent researches show that a static magnetic field (SMF) has an impact on the molten pool dynamics and microstructure of laser powder bed fusion (L-PBF). This work is intended to the multiple effect of SMF on the molten pool dynamics during L-PBF of Inconel 718 superalloy. A three-dimensional (3D) multiphase computational fluid dynamics (CFD) model at the powder-bed scale was established by coupling the electromagnetic braking and Seebeck effect in a static vertically-distributed magnetic field. Results show that the magnetic damping force (MDF) of the order of 104 N/m3∼105 N/m3 within the whole molten pool suppresses the Marangoni convection. The thermoelectric magnetic force (TEMF) of the order of 106 N/m3∼107 N/m3 rotates in the mushy zone and further enhances the melt flow of the whole molten pool. The SMF will not transform the flow pattern and temperature distribution in the molten pool. SMFs of 0.1 T and 0.3 T will suppress the melt flow, while that of 0.5 T will enhance the melt flow. The width of molten pool first decreases and then increases when the magnetic flux density (MFD) increases from 0 T to 0.5 T. In addition, applying a SMF of 0.3 T can effectively inhibit pore defect and spatters. This work can provide insight into the control of molten pool by introducing a SMF during L-PBF.

The First Unified and Transient Modeling Platform to Build a Digital Twin of Blast Furnaces Based on the Extended Discrete Element Method

The current research addresses a unified and integrated Euler–Lagrange simulation platform based on the extended discrete element method that advances significantly the digital twin technology applied to blast furnaces. It includes a particulate phase characterized by its dynamic and thermodynamic state that is coupled to multiphase computational fluid dynamics (CFD) by heat, mass, and momentum transfer. Thus, the framework deals with transient and reacting 3D granular and multiphase flows. The latter includes all relevant processes taking place in a blast furnace: formation of a reducing agent, e.g., carbon monoxide, reduction of iron‐bearing material, and softening and melting with the subsequent transfer into the corresponding phase of the multiphase CFD solver and thus, identifying unambiguously the cohesive zone. Validation is carried out on different length scales from a particle level to the global dimensions of a blast furnace and shows a good agreement between predictions and experimental data. Applying fast and innovative algorithms allows for moderate computational times, i.e., 1000 s real‐time takes ≈2.3 d on an Intel(R) Xenon(R) Silver 4114 CPU @ 2.2 GHz processor with 40 cores and the entire domain divides into eight partitions.

Thermo-fluid dynamics and morphology evolution of nickel-based superalloy in a multilayer laser directed energy deposition process

The complex thermo-fluid dynamics of the molten pool determine the dimension accuracy and mechanical properties of laser directed energy deposition (L-DED) components. In this work, a three-dimensional (3D) multiphase computational fluid dynamics (CFD) model based on the Volume of Fluid (VOF) method was proposed to establish the relationship between the thermo-fluid dynamics and the molten pool morphology evolution of René N5 nickel-based superalloy in L-DED. The single-track and ten-layer deposition processes under unidirectional and bidirectional scanning strategies were studied. Results show that the predicted deposition morphology and dimensions are in good agreement with the experimental samples. The heat accumulation in the multilayer deposition process increases the size of the molten pool, thereby increasing the width of the deposit. Different from the single-layer deposition driven by the Marangoni force, gravity is the key factor in the multilayer deposition process without the side support. The hump structure at the starting position under unidirectional scanning is attributed to the backward flow of the melt of the molten pool, while the decline structure at the end position is enhanced by the forward flow of the melt. At the starting position of each layer under bidirectional scanning, the expansion of the molten pool resulted from the heat accumulation and mass addition increases the width of the two ends and compensates for the deposition height. This work can provide a theoretical basis for understanding the uneven morphology characteristics and the dimensional accuracy control in L-DED.

Influence of impeller clearance, impeller size and baffles on copper sorption on zeolite NaX: Do the size and position really matter?

Even though optimal mixing parameters may significantly influence the sorption process and its costs, the influence of hydrodynamics on sorption in a batch reactor hasn't yet been adequately studied. In this study, the hydrodynamic conditions produced by pitched blade turbine (PBT) impellers of various diameters and positions in baffled and unbaffled reactors were investigated. The objective was to investigate their influence on the just suspended impeller speed (NJS), power consumption per zeolite mass and the sorption process at the same temperature, initial copper solution concentration, and zeolite particle size in all the experiments conducted. The results show that NJS generally decreases as impeller diameter increases and is lower in the reactor without baffles. A transient multiphase computational fluid dynamics model was developed to provide valuable insight into the complex flow kinetics and it was found that the further the impeller is from the bottom of the baffled reactor the wider is the secondary suspension flow and the intensity of the flow below the impeller decreases. For this reason, complete suspension of the NaX zeolite particles in the solution was achieved at a higher PBT impeller speed. Due to the swirling motion of the suspension, this phenomenon is not observed in the unbaffled reactor for all the impellers used besides the smallest one. The power consumption per zeolite mass, at the state of complete zeolite suspension, increases in baffled reactor and decreases in unbaffled reactor with increasing impeller diameter having significantly lower values in the unbaffled reactor. The significantly lower power consumption per zeolite mass in an unbaffled system could be attributed to, not only the generally lower NJS values, but also to the resistance force which baffles make to the tangential fluid flow. The Ritchie model and Mixed surface reaction and diffusion controlled adsorption kinetic model were used for the kinetic analysis of the experimental kinetic data. The kinetic results indicate that the process is faster when the impeller is at the standard of bottom clearance, regardless of the presence of the baffles.

Enhancing TiO2 Precipitation Process through the Utilization of Solution-Gas-Solid Multiphase CFD Simulation and Experiments

Ensuring uniform particle size distribution is a crucial role in the precipitation process of manufacturing white pigment. This study presents a comprehensive investigation that combines multiphase computational fluid dynamics (CFD) simulations with experimental research to effectively address the challenge of achieving uniform particle distribution during TiO2 precipitation. The objective of this study was to enhance three-phase CFD simulations involving the mixing process of TIOSO₄ solution, steam as a gas phase, and solid seed particles. By analyzing the trajectories of the seed particles using CFD, the optimal injection position for the seed particles within the mixing process was determined. Subsequently, a lab scale test and real field test were conducted based on the insights gained from the CFD simulations. The particle size distribution of two different types of seed inlets was analyzed and compared using Transmission Electron Microscopy (TEM) and Scanning Electron Microscope (SEM). The findings of this study demonstrate that the developed multiphase CFD simulation can effectively enhance the precipitation process for the production of anatase titanium dioxide particles. Additionally, using the developed multiphase CFD solver, the real physics involved in the precipitation process were identified, leading to a better understanding of the process itself. Furthermore, TiO2 particles with uniform particle size had a positive impact on the washing and bleaching processes following the precipitation process, resulting in a significant reduction in the annual defect production rate.

Carbon dioxide desorption behavior of potassium carbonate supported on gamma-alumina solid sorbent in wet fluidized bed under steam atmosphere

Since the carbon dioxide (CO2) capture using solid sorbent is a reversible reaction, the solid sorbent can be regenerated by the desorption process. Therefore, the desorption process is one of the key important processes for the CO2 capture system. Traditionally, most of the literature studies focus on the desorption of solid sorbent under an N2 atmosphere. However, the desorption process of the solid sorbent is inappropriate in the real system because the system will need another process to separate CO2 and nitrogen (N2) after the desorption process. This study focused on the CO2 desorption of potassium carbonate supported on gamma-alumina (K2CO3/γ-Al2O3) in a wet fluidized bed under a steam atmosphere by using the multiphase computational fluid dynamics (CFD) simulation. The effects of water thickness and dry restitution coefficient on CO2 desorption rate were investigated to provide a realistic particle collision behavior and to explore their effects on CO2 desorption phenomena. Moreover, the effect of steam velocity on the hydrodynamic behaviors of fluidization which on CO2 desorption rate was studied. The simulated results demonstrated that all the parameters, water thickness, dry restitution coefficient, and steam velocity had significantly affected system hydrodynamics and CO2 desorption rate in the wet fluidization desorption process. Furthermore, the effect of desorption temperature on CO2 desorption rate was evaluated for finding the appropriate temperature for CO2 desorption process of K2CO3/γ-Al2O3. The results showed that the appropriate desorption temperature for CO2 desorption under steam atmosphere was the temperature over 150 °C.

Analysis of Thrombosis Formation and Growth Using Microfluidic Chips and Multiphase Computational Fluid Dynamics

Analysis of Thrombosis Formation and Growth Using Microfluidic Chips and Multiphase Computational Fluid Dynamics

Assessing low Reynolds number airfoil performance in microburst environments for micro/unmanned aerial vehicles: A numerical study

This study aims to investigate the impact of microbursts, which are a common meteorological phenomenon, on aircraft performance. A multiphase computational fluid dynamics model has been developed to simulate the microburst-generated downdraft environment over an airfoil. The simulations were conducted at a 12° angle of attack for takeoff conditions with a Reynolds number of 2×105. The lift and drag coefficients were compared to experimental results and exhibited a strong correlation. Additionally, this study examined the volume of fluid and the coefficient of pressure distribution. It also examined the boundary-layer velocity profiles at five different chord positions, the location of rivulet formation on the upper surface of the airfoil, and water film height. The results revealed a maximum variation of 72.18% and 16.53% in lift and drag coefficients, respectively, between the numerical and experimental results. These findings provide valuable insight into the effects of microbursts on aircraft performance and have implications for the aviation industry.

Multi-objective optimization of a double tapered flow field Proton Exchange Membrane Fuel cell

Flow fields are essential in Proton Exchange Membrane Fuel Cell (PEMFC) performance. Appropriate in-plane tapering in the main channels width of parallel flow fields enhances flow distribution uniformity, increasing performance. To the best of the authors, there is no literature discussing the through-plane inclination in a parallel flow field with in-plane tapered main channels. This study develops a surrogate model based on a data set to study double tapering in the flow field. The three-dimensional multiphase Computational Fluid Dynamics (CFD) generates the data set. Decision variables are the angle of depth tapering, operating pressure, temperature, stoichiometries, and voltage. Also, the objectives are power density and efficiency. Proper depth tapering increases mass transfer, decreasing the concentration loss. The increment of 19.6% in maximum power is captured by tapering. Depth tapering in the parallel flow field improves efficiency, especially at a higher temperature and lower pressure. Furthermore, a multi-layer multi-objective optimization methods are utilized. A reference depth tapering angle θ is defined. Optimum characteristics are the tapering angle of 0.13θ, the temperature of 329.9 K, the operating pressure of 4 atm, the operating voltage of 0.465 V, and the unit stoichiometry of both sides. Optimum characteristics bring the best performance, an efficiency of 21.55%, and a power density of 0.75 W cm−2.

Analysis of cavitation and shear in bellows pump: transient CFD modelling and high-speed visualization

Pneumatic drive bellows pumps (PDBPs) are a crucial fluid control component in the semiconductor industry. However, when dealing with specific chemical mechanical polishing (CMP) slurries, agglomeration of particles can occur, leading to scratches, particle residues, pits, and other defects on the wafer surface. The leading cause of agglomeration has been proposed to be cavitation and excessive shear in PDBPs. A high-fidelity multiphase computational fluid dynamics (CFD) model, which fully resolves the response of check valves under hydrodynamic and other external loads, was established to evaluate cavitation behaviour and shear distribution in PDBPs. Moreover, a test rig was built to visualize cavitating flow patterns in PDBPs and verify the accuracy of the CFD model. Among different cavitation regions captured by high-speed visualization, the region near the inner leading edge of the end-ring of the inlet valve is dominant, with high intensity, long duration, and complex morphology evolution. Detailed initiation and development process of cavities in the dominant region are analysed numerically. The shear rate in different domains of PDBPs is estimated, and the inlet valve domain stands out from the other. The strongest shear rate is observed near the leading edge of the end-ring. Furthermore, an analysis of the relationship between cavitation and shear indicates that the high-intensity vortices generated owing to strong shear account for the inception of cavitation. This study contributes to understanding inner flow details in PDBPs and provides a guideline for further optimization of similar pumps.

Optimizing the Disinfection Inactivation Efficiency in Wastewater Treatment: A Computational Fluid Dynamics Investigation of a Full‐Scale Ozonation Contactor

AbstractThe inactivation kinetics of total coliforms to increase the pathogenic removal efficiency in a full‐scale ozonation contactor in a wastewater treatment plant in Algeria is investigated. An enhanced ozone contactor design is proposed and 3D multiphase computational fluid dynamics simulations were conducted to optimize the operating parameters, including flow rates, ozone concentrations considering the treatment performance, and total operating cost. The existing design has several limitations, including poor mass‐transfer efficiency and uneven distribution of dissolved ozone. To address these issues, the optimized design includes new injection‐point settings and an increased number of diffusers. The optimized design achieved a significant improvement in mass transfer efficiency. The ozone treatment effectively reduced the total coliform counts in the wastewater samples compared to the existing design. The Chick‐Watson model predicted inactivation kinetics, with a reduction of up to 99.997 %. The practical implications of this research can significantly improve the inactivation kinetics of ozone treatments.