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Seepage-induced instabilities pose a challenge in many geotechnical applications. Particle-scale mechanisms govern the initiation of instability. However, current understanding is based on a macro-scale perspective that draws on continuum mechanics. Recent developments in imaging and numerical analysis can provide the particle-scale fundamental perspective needed to develop a comprehensive insight. This contribution demonstrates the value of combining particle-scale experimental and numerical studies. The experiments consider transparent soil samples created using refractive image matching and monitored by particle image velocimetry (PIV). Three-dimensional pore topology is extracted from a series of two-dimensional images and imported into computational fluid dynamics (CFD) simulations. Permeability is estimated by three distinct approaches: using flow rate, PIV- and CFD-generated data. The flow fields obtained from PIV and CFD are in good agreement considering both flow rate contour plots and flow rate distributions; this demonstrates the successful reconstruction of three-dimensional pore structure and flow-field analysis. The comparison also reveals that the side boundary effects in CFD simulations are constrained within a limited region. The multi-plane results characterise the variance of flow velocity with the three-dimensional pore topology. Finally, the fluid–particle interactions obtained from CFD results show a larger variance in the angular particle packings.

The three-dimensional computational fluid dynamics (3D-CFD) of a pulsating flow applied to the fluid catalytic cracking (FCC) reaction was investigated in the riser of a circulating fluidized bed reactor. The kinetic parameters of the FCC and coke burning reactions for predicting the reactant conversion and product yield percentages were applied. To increase the reactant conversion level and product yield, the effect of the pulsating flow operating parameters was considered using a 2k statistical experimental design with four factors (amplitude, frequency, types of the waveform, and amplitude ratio). The 3D-CFD simulation was successfully validated from the experimental literature data. The frequency and type of the waveform were found to be the significant operating parameters. The expression of the fitted regression model and response surface contour were derived and revealed that the pulsating flow provides a higher reactant conversion level and product yield percentages compared to a non-pulsating or steady flow.

With the imminent digitalisation of the manufacturing processes of gas turbine components, a large volume of geometric data of as-manufactured parts is being generated. This geometric data can be used in aerodynamic simulations to predict component performance. Both the cost and accuracy of these simulations increase with their fidelity. To efficiently exploit Digital Twin technology, one must therefore understand how realistic the aerodynamic simulations need to be to give useful performance predictions. This paper considers this issue for a sample of scrapped high-pressure turbine rotor blades from a civil aero engine. The measured geometric data was used to build aerodynamic models of varying degrees of realism, ranging from quasi-three-dimensional blade sections for an Euler solver to three-dimensional, multi-passage and multi-stage Reynolds-Averaged-Navier-Stokes models. The flow near the tip of these shrouded blades is sensitive to manufacturing variability and can switch between two quasi-stable horseshoe vortex modes. In general, capacity and exit flow angle can be adequately predicted by three-dimensional, single-passage calculations: averaging single-passage calculations gives a good prediction of the multi-passage behaviour. For efficiency and stage loading, the approach of averaging single-passage calculations is less accurate as the multi-passage behaviour requires an accurate prediction of the horseshoe vortex modes.

Thermoacoustics is about conversion between thermal and acoustical energies to provide alternative green technology for power cycle and cooling system. The oscillatory flow across porous structure inside the system is playing the role of energy conversion between the acoustic wave and the surface of the porous structure. Better understanding of fluid dynamics of oscillatory flow inside thermoacoustic system is therefore important for the thermoacoustic based energy conversion system. This paper presents the ‘entrance’ and ‘exit’ effects of the oscillatory flow within a parallel-plate structure that is placed inside a standing-wave thermoacoustic environment. Two-dimensional SST k-ω CFD models which were validated using experimental data and theoretical predictions were used for this investigation. Two different operating frequencies of 14.2 Hz and 23.6 Hz were studied for flow with five different amplitudes that were represented using drive ratios of 0.3%, 0.83%, 1.5%, 2.1% and 3%. These correspond to cases with Reynolds numbers between 5936 and 62926. Due to the cyclic nature of the flow, a region defined as an ‘exit’ region was observed in addition to the usual ‘entrance’ region and the fully developed region for flow inside a channel. The change of shape of velocity profiles from the ‘m’ shape profile, to the ‘slug-like’ profile and ‘parabolic-like’ profile was discussed in relation to the ‘entrance’ and ‘exit’ effects on flow inside the channel. The ‘entrance’ and ‘exit’ effects become bigger as drive ratio increases. The effect of ‘entrance’ and ‘exit’ are slightly reducing as frequency increases from 14.2 Hz to 23.6 Hz. This may be related to the shorter travel distance of fluid as the frequency increases. The results shown in this paper suggest that the flow within a 200 mm parallel-plate structure should be treated as developing flow especially for flow with low resonance frequency at drive ratio higher than 1%.

Mesoscale bubbles exist inherently in bubbling fluidized beds and hence should be considered in the constitutive modeling of the drag force. The energy minimization multiscale bubbling (EMMS/bubbling) drag model takes the effects of mesoscale structures (i.e., bubbles) into the modeling of drag coefficient and thus improves the coarse-grid simulation of bubbling and turbulent fluidized beds. However, its dependence on the bubble diameter correlation has not been thoroughly investigated. The hydrodynamic disparity between homogeneous and heterogeneous fluidization is accounted for by the heterogeneity index, Hd, which can be affected by choice of bubble diameter correlation. How this choice of bubble diameter correlation influences the model prediction calls for further fundamental research. This article incorporated seven different bubble diameter correlations into EMMS/bubbling drag model and studied their effects on Hd. The performance of these correlations has been compared with the correlation used previously by EMMS/bubbling drag model. We found that some of the correlations predicted lower Hd by order of a magnitude than the correlation used by the original EMMS/bubbling drag. Based on such analysis, we proposed a modification in the EMMS drag model for bubbling and turbulent fluidized beds. A computational fluid dynamics (CFD) simulation using two-fluid model with the modified EMMS/bubbling drag model was performed for two bubbling and one turbulent fluidized beds. Voidage distribution, time averaged solid concentration and axial solid concentration profiles were studied and compared with the previous version of the EMMS/bubbling drag model and experimental data. We found that the right choice of bubble diameter correlations can significantly improve the results for CFD simulations.

The mixing characteristics of industrial flotation columns were investigated using computational fluid dynamics (CFD). Particular emphasis was placed on the clarification of the relationship between the liquid and solids mixing parameters such as the mean residence time and axial dispersion coefficients. The effects of particle size and bubble size on liquid dispersion in the column were also studied. An Eulerian-Eulerian method was applied to simulate the multiphase flow, while additional scalar transport equations were introduced to predict the liquid residence time distribution (RTD) and particle age distribution inside the column. The results obtained show that particle residence time decreases with increasing particle size. The residence time of the coarser particles (112.5 pm) was found to be at least 60% of the liquid residence time, while the finer particles (19 pm) had a residence time similar to the liquid. The results also show that an increase in the particle size of the solids results in a decrease in the liquid vessel dispersion number, while a decrease in the bubble size increases liquid axial mixing. Finally, the simulated axial velocity profiles confirm the similarity between the liquid and solids axial dispersion coefficients in column flotation.

In this work, the effect of using baffles and vortex generators on the cooling performance of a gas turbine combustion chamber is numerically investigated. The RNG k-ɛ model is utilized in order to simulate the flow turbulence. The effects of baffles and vortex generator pitch, hydraulic diameter and bypass ratio on the Nusselt number and friction coefficient at different Reynolds number are studied. The cooling performance of applying baffles and vortex generators are also evaluated and compared based on the Performance Evaluation Criterion (PEC). The numerical results are verified with available experimental data. The results show that the pitch increment results in the decrement of the Nusselt number and the wall friction coefficient due to the lower vortices generation and the turbulence kinetic energy dissipation. Also, the Nusselt number is increased by increasing both the bypass ratio and the hydraulic diameter. It is also found that vortex generators and baffles improve the cooling performance of the gas turbine combustion chamber by 18.8% and 26% respectively through decreasing the external wall temperature.

The force-generation mechanism of a dovelike flapping-wing micro air vehicle was studied by numerical simulation and experiment. To obtain the real deformation pattern of the flapping wing, the digital image correlation technology was used to measure the dynamic deformation of the wing. The dynamic deformation data were subsequently interpolated and embedded into the CFD solver to account for the aeroelastic effects. The dynamic deformation data were further used to calculate the inertial forces by regarding the wing as a system of particles to take into account the wing flexibility. The temporal variation of the forces produced by the flapping wing was measured by a miniature load cell. The numerical results provide more flow details of the unsteady aerodynamics of the flapping wing in terms of vortex formation and evolution. The calculated results of the inertial forces are analyzed and compared with the CFD results which represent the aerodynamic forces. In addition, the total forces, i.e., the sum of the CFD result and inertial result, are compared with the experimental results, and an overall good agreement is obtained.

A wave rotor is suitable for compact and efficient pressure-exchange between gas flows. This work measured the circumferential pressure distribution of the rotor/stator interfaces and utilized a CFD method to simulate the unsteady pressure waves. The experimental and CFD results showed some slopes in the circumferential pressure distributions, and the slopes indicated the traces of specific unsteady pressure waves. Such traces varied regularly if the rotational speed varied within a range from −11% to +11% off the baseline value, but they were seriously disturbed if the rotational speed varied by −45% from the baseline value. It verified that a pressure wave in a wave rotor tended to keep its pressure ratio and propagation velocity unchanged if the rotational speed varied by a small extent, and that the pressure wave could not keep its propagation patterns if the rotational speed varied by a large extent. Because of the pressure wave behaviors, the wave rotor demonstrated specific regulations of the rotational speed effects on its operational states.

The chemical looping hydrogen production (CLHP) process is a new approach for hydrogen ( H 2 ) fuel production. The proposed process consists of three reactors which are air reactor (AR), fuel reactor (FR) and steam reactor (SR). In this study, the gas solid flow behaviour in a cold model of the proposed CLHP process was simulated using computational fluid dynamics (CFD) with kinetic theory of granular flow. The effect of drag coefficient models on the pressure profile of each reactor was investigated and the results from the modified Syamlal–O’Brien drag model agreed well with the experimental data. The model was further used to investigate effects of the operating parameters on the hydrodynamics profiles of each reactor. The solid flux increased with the increasing of inlet velocity of AR and FR but decreased with the increasing of the inlet velocity of SR. At the same time, the solid flux increased with the increasing of the solid inventory.

This paper studies a novel gas cyclone with a cylindrical filter face installed in the center from the vortex finder to the bottom hopper. The experimental results show that this composite cyclone has a higher collection efficiency and a lower pressure drop than the original cyclone. The mechanisms for the improvement are analyzed by both physical experiments and numerical simulations. By measuring dust samples collected at different places it is revealed that the center filter can prevent fine particles from entering the inner vortex and escaping, which accounts for the increase of the collection efficiency. In addition, the flow field of the composite cyclone is simulated by computational fluid dynamics and compared with that of the original cyclone. The analysis shows that with the filter layer installed, the swirling flow disappears in the vortex finder, which decreases the kinetic energy dissipation and hence lowers the pressure drop.

In this research, a Graphical Processing Unit (GPU) accelerated Discrete Element Method (DEM) code was developed and coupled with the Computational Fluid Dynamic (CFD) software MFiX to simulate granular and multiphase flows with heat transfers and chemical reactions. The Fortran-based CFD solver was coupled with the CUDA/C++ based DEM solver through inter-process pipes. The speedup to the CPU version of MFiX-DEM is about 130–243 folds in the simulation of particle packings. In fluidized bed simulations, the DEM computation time is reduced from 91% to 17% with a speedup of 78 folds. The simulation of Geldart A particle fluidization revealed a similar level of importance of both fluid and particle coarse-graining. The filtered drag derived from the two-fluid model is suitable for Euler-Lagrangian simulations with both fluid and particle coarse-graining. It overcorrects the influence of sub-grid structures if used for simulations with only fluid coarse-graining.

The present study addresses the first steps of development and validation of a coupled Finite Volume-Blade Element Model (FV-BEM) simulation tool dedicated to offshore wind turbine farm modeling. The fluid domain is solved using the incompressible formulation of the CFD solver Grid-flow. The turbines are taken into account using FAST (from NREL) and their effects are imposed into the fluid domain through an actuator line model (ALM) for which specific enhancements are proposed. The Grid-flow solver and its two-way coupling with the aero-elastic modules from FAST is introduced and detailed. The simulation of the case of two in-line wind turbines using the FV-BEM coupling proposed is presented, together with comparisons against experimental results for validation purposes. Finally, a discussion on performances, advantages and limitations of the formulation proposed is provided.

The micro-nozzle allows small spacecraft to realize the orbital maneuvering and precise station-keeping. Due to the rarefaction effect of the gas flow in micro-nozzles, the velocity-slip and temperature-jump exists near inner wall, and thus, affecting the operating characteristics of micro-nozzles. Various gas-solid theories and models have been developed to describe the velocity slip and temperature jump in computational fluid dynamics (CFD). In this study, numerical simulations of a micro-nozzle with five classical slip boundary models, which are based on the Maxwell scattering and Langmuir adsorption, are conducted to analyze the applicability of these models through comparing with the results obtained by direct simulated Monte Carlo (DSMC) method. The results show that the inlet pressure dramatically influences the flow regime of the micro-nozzle. The lower the inlet pressure, the higher the influence of the rarefaction effect. The results also indicate that the Langmuir slip model can accurately simulate the flow field in the transition regime. However, the modified Maxwell and Langmuir models proposed by Agrawal et al. (2008) and Le et al. (2012), respectively, are valid in the slip regime.

Computational mesh is an important ingredient that affects the accuracy and efficiency of CFD numerical simulation. In light of the introduced large amount of computational costs for many adaptive mesh methods, moving mesh methods keep the number of nodes and topology of a mesh unchanged and do not increase CFD computational expense. As the state-of-the-art moving mesh method, the variational mesh adaptation approach has been introduced to CFD calculation. However, quickly estimating the flow field on the updated meshes during the iterative algorithm is challenging. A mesh optimization method, which embeds a machine learning regression model into the variational mesh adaptation, is proposed. The regression model captures the mapping between the initial mesh nodes and the flow field, so that the variational method could move mesh nodes iteratively by solving the mesh functional which is built from the estimated flow field on the updated mesh via the regression model. After the optimization, the density of the nodes in the high gradient area increases while the density in the low gradient area decreases. Benchmark examples are first used to verify the feasibility and effectiveness of the proposed method. And then we use the steady subsonic and transonic flows over cylinder and NACA0012 airfoil on unstructured triangular meshes to test our method. Results show that the proposed method significantly improves the accuracy of the local flow features on the adaptive meshes. Our work indicates that the proposed mesh optimization approach is promising for improving the accuracy and efficiency of CFD computation.

A numerical simulation approach is substantiated and verified for predicting the Taylor-Couette flow with an impermeable outer stationary cylinder and porous rotating inner one. An imposed throughflow is considered, supplied via one end of the annular gap and leaving the domain through another gap end (retentate) and from inside of the rotating cylinder (permeate). The flow is typical for dynamic filtration by rotating cylindrical filters. In contrast to known publications, the rotating porous cylinder is included into the computational domain and the liquid flow inside of it is fully resolved. The influence of the permeate-retentate ratio and permeability of the rotating inner cylinder onto the centrifugal stability boundary and supercritical flow details is discussed. It is found that filtration velocity becomes distributed not uniformly along the porous cylinder when its hydraulic resistance is less than a definite value. After some critical threshold, the flow structure drastically changes, and spiral vortices appears, which crosses the porous rotating cylinder back and forth several times, providing multiple flow recirculation through the porous cylinder. The results obtained create the basis for the development of dynamic rotational filters for various applications.

Unsteady lifting-line theory (ULLT) is a low-order method capable of modeling interacting unsteady and finite wing effects at low computational cost. Most formulations of the method assume inviscid flow and small amplitudes. Although these assumptions might be suitable for small-amplitude aeroelastic problems at high Reynolds numbers, modern engineering applications increasingly involve lower Reynolds numbers, large-amplitude kinematics, and vortex structures that lead to aerodynamic nonlinearities. This paper establishes that ULLT still provides a useful solution for low-Reynolds-number, large-amplitude kinematics problems, by comparing ULLT results against those of experimentally validated computational fluid dynamics simulations at Re=10,000. Three-dimensional effects stabilize leading-edge vortex (LEV) structures, resulting in a good prediction of whole wing force coefficients by ULLT. Although the inviscid spanwise force distributions are accurate for small-amplitude kinematics, the ULLT cannot model three-dimensional vortical structures, and thus it cannot correctly predict the force distribution due to the LEV. It can, however, predict the shedding of LEVs to a limited extent via the leading-edge suction parameter criterion. This can then be used as an indicator of the usefulness of the force distribution results.

The inclusion of transition to turbulence effects in computational fluid dynamics simulations makes it possible to design laminar flow airframes. It also increases the level of physical representat...

The quest to achieve high launching frequency and higher speed is one of the key goals for researchers in the field of underwater projectiles. Many methods have been proposed for reducing the drag force to reach higher speed, such as superhydrophobic surface, compliant surface, and so on. One of the most effective methods is supercavitating drag reduction technology, which can be used to achieve a significant reduction of hydrodynamic drag by wrapping a large, continuous cavity around the underwater projectile. To increase launching frequency and decrease drag force of underwater projectiles, a serial multi-projectiles structure based on the principle of supercavitation is proposed in this paper. However, the matching relationships of serial multiprojectiles between different conditions (cavitation number, distance between projectiles, etc.) and the drag characteristics have not been investigated, because obtaining the relationship between drag characteristics and different conditions requires simulation time and extensive calculations. In this paper, computational fluid dynamics (CFD) method and machine learning method were coupled to investigate the natural supercavitation phenomenon of the serial projectiles to reduce the computational cost and improve the simulation accuracy. Firstly, the numerical simulation model for the underwater supercavitating projectile is established and verified by experimental data. Then the evolution of the supercavitation for the serial multi-projectiles is described. In addition, the effects of different cavitation numbers and different distances between projectiles are investigated to demonstrate the supercavitation and drag reduction performance. Finally, the artificial neural network (ANN) model is established to predict the evolution of drag coefficient based on the data obtained by CFD. The results predicted by ANN are in good agreement with the data obtained by CFD. The findings provide helpful guidance for the research on the drag reduction characteristics of underwater serial projectiles. The main conclusions of the study are as follows: (1) The cavity will develop, fuse and collapse in the water and natural supercavitation phenomenon is observed when underwater serial projectiles move at a high speed. The serial multi-projectile structure can reduce the drag of the second projectile and achieve the goal of drag reduction. (2) The length and aspect ratio of supercavity around serial projectiles decrease with the decreasing of the cavitation number, and the drag coefficient of the second projectile decreases. The length and aspect ratio of supercavity decrease with the 3 decreasing of the distance between serial projectiles, and the drag coefficient of the second projectile decreases. (3) The drag coefficient of the second projectile predicted from the ANN model has a high accuracy, where the regression R2 values of training, validation, and testing samples are above 0.99. Machine learning has an obvious advantage in simplifying computational complexity and increasing computational efficiency. Furthermore, the discussion of different cases is based on static projectiles. However, in real-world applications, the movement of serial projectiles should be considered. This is the future direction for this work.

As a valid numerical method to obtain a high-resolution result of a flow field, computational fluid dynamics (CFD) have been widely used to study coolant flow and heat transfer characteristics in fuel rod bundles. However, the time-consuming, iterative calculation of Navier-Stokes equations makes CFD unsuitable for the scenarios that require efficient simulation such as sensitivity analysis and uncertainty quantification. To solve this problem, a reduced-order model (ROM) based on proper orthogonal decomposition (POD) and machine learning (ML) is proposed to simulate the flow field efficiently. Firstly, a validated CFD model to output the flow field data set of the rod bundle is established. Secondly, based on the POD method, the modes and corresponding coefficients of the flow field were extracted. Then, an deep feed-forward neural network, due to its efficiency in approximating arbitrary functions and its ability to handle high-dimensional and strong nonlinear problems, is selected to build a model that maps the non-linear relationship between the mode coefficients and the boundary conditions. A trained surrogate model for modes coefficients prediction is obtained after a certain number of training iterations. Finally, the flow field is reconstructed by combining the product of the POD basis and coefficients. Based on the test dataset, an evaluation of the ROM is carried out. The evaluation results show that the proposed POD-ROM accurately describe the flow status of the fluid field in rod bundles with high resolution in only a few milliseconds.

Scale-up of the liquid-liquid extraction columns like asymmetric rotating impeller column (ARIC) from laboratory to industry is an expensive procedure in terms of resources, inventory, human resources, and time. Local hydrodynamics of the column governs the breakage and coalescence of the drop and thus the mass transfer performance of the column. The correlations developed for scale-up procedures by experimentation at laboratory scale cannot ensure the local properties like velocities, turbulence, and dispersed phase holdup to be the same in the large scale columns. In the present work, the CFD methodology has been proposed for the scale-up of ARICs. CFD simulations have been carried out in three geometrically similar ARICs, to check for the kinematic similarity. The predicted dispersed phase holdup is found to agree with the experimental results with an average absolute value of the relative error within 20%. The local velocities and turbulence properties are compared for three scales. The local velocities and turbulence are observed to scale with the tip speed. CFD simulations show that the flow patterns and turbulence scale with increased column diameter and scale-up can be made based on geometric similarity at equal specific power and tip speed.

Compressible cavity flows exist widely in aeronautical vehicles. The cost of the computational fluid dynamics to solve compressible cavity flows is high. To address this issue, in this work, a nove...

Flocculation occurring in a feedwell plays a critical role in tailings slurry thickening process, which is complicated and significantly influenced by flow characteristics. This work presents a numerical approach to explore the effect of flow characteristics on flocculation performance. It combines an aggregation kernel and a breakage kernel, used to describe the polymer-bridging flocculation kinetics, with a conventional Computational Fluid Dynamics-Population Balance Model (CFD-PBM) coupling to model the complex flocculation-thickening behavior in a lab-scale gravity thickener. The solid-liquid phase interaction is described by an Euler-Euler approach with a modified Schiller-Naumann drag model. The turbulence of liquid phase is resolved by the RNG k-e turbulence model, while the solid kinematic eddy viscosity is described by a dispersed phase zero equation model. The capability of this proposed model is validated by a good agreement between experimental and predicted results in terms of single-liquid velocity and floc size distribution. The momentum and turbulence dissipation rates are investigated in and around the feedwell over a wide range of feed velocities, showing that the momentum and turbulence dissipation rates have a positive correlation with feed velocity. The momentum and turbulence dissipation rates decrease with the increase in scaled depth in the feedwell. The formation of large vortexes in the feedwell may cause a locally low turbulence dissipation rate. A reasonable increase of feed velocity favours the flocculation, however, an excessive feed velocity can cause a decrease in mean floc size. Modelling tailings flocculation is of great significance for understanding the flocculation behavior and revealing the effect of flow characteristics on flocculation performance.

Based on the principle of two-phase hydrodynamics and the mechanism of cavitation generation, this paper uses the finite volume method (FVM) in computational fluid dynamics (CFD) to analyse the features of fluid flow in jet amplifier, i.e., the pilot stage of jet pipe servo valve, and designs a lab bench to experimentally prove the accuracy of this numerical method. On this basis, the author discussed how four structural parameters influence the amplification efficiency of the jet amplifier. The amplification efficiency of the jet pipe servo valve can be maximized by setting the distance between nozzle and receiving holes of 0.1 mm, the diameter of receiving holes of 0.2 mm, the inclination angle of 22.5°, and the spacing between the two receiving holes of 0 mm (if possible). The research methods and results provide a solid basis for the design and performance prediction of the jet pipe servo valve.

With the increasing requirements for miniaturization and high braking torque, it is now necessary to analyze the thermal characteristics to the same extent as the electromagnetic design for eddy current brakes. However, due to the lack of suitable convection heat transfer correlations for axial flux eddy current brakes, it brings difficulties to designers. To solve this problem, the correlations for an axial flux permanent magnet (PM) eddy current brake are derived using the computational fluid dynamics (CFD) and the least square method. The proposed correlations considered the changes in design parameters and temperatures of the eddy current brake, and the accuracy is verified by the CFD. Subsequently, convective heat transfer coefficients calculated through the correlations are assigned to a thermal network model of the eddy current brake, and the thermal network model is verified by experimental tests. The results show that the thermal network model can accurately predict temperatures of the eddy current brake. Since the time required to calculate convective heat transfer coefficients through the correlations is significantly less than that required through CFD, and the variation of the geometrical parameters and temperatures can be considered, these correlations are very suitable for use in the optimization process.

We report a joint experimental and numerical study on the global thermal performance of a novel windowless vortex-based cavity receiver for potential thermal processing of suspended particles. This systematic study assesses the coupled influence of particle loading, Froude and Stokes number through variation of the inlet mass flowrate, particle size and loading on the global performance of the Solar Expanding Vortex Receiver-Reactor (SEVR) under steady-state conditions. The experiments employ polydispersed CARBO CP ceramic particles that are heated with an 18-kWel Metal Halide three-lamp solar simulator. A numerical study was also performed using computational fluid dynamics (CFD) software ANSYS/CFX 2019 R1. It was found that the particle volumetric loading and Froude number have primary controlling influence, while the Stokes number has a secondary influence on the global performance for these conditions. An overall thermal efficiency of 67% was obtained under high particle loading and Froude numbers.

Hydrocylones offer a process intensified environment for rapid, high-throughput and relatively sharp particle classification or phase separation. One of the main performance limitations of hydrocyclone is bypassing of fines to the underflow. To address this limitation, a novel design modification of fitting thin concentric rings to the cylindro-conical section has been proposed. The Computational Fluid Dynamics (CFD) modeling based methodology has been adopted to validate the hypothesis. Predictions using Realizable k-e, Reynolds Stress Model (RSM), and Large Eddy Simulation Wall Adopting Local Eddy viscosity (LES-WALE) turbulence models has revealed that LES-WALE matched better with the experimental observations. The experimental data included overall performance parameters and detailed observations of axial and tangential velocity profiles across the hydrocyclone. The validated CFD model and the methodology was then used to predict the behavior of the proposed designs. They established that the modifications held promise in reducing the bypass with additional benefits of sharper separation curve and finer D50.

Cyclone separators are the most cost-effective and economically gas separation devices. They are not very complex to design and offer high collection efficiency; still, their use for the waste management field, i.e., separating solid waste from the liquid, is not explored to its full extends. This paper presents a Computational Fluid Dynamics-based numerical simulation of a hydro-cyclone separator planned to separate suspended particles from the digestate of a biogas plant. The turbulent incompressible flow model is employed during the simulation. The discrete particle method is used to model and track the suspended solid particle trajectory. The fluid properties of the digestate are assigned to the fluid supplied with suspended particle sizes ranging from 10 to 100 µm during the simulation to obtain realistic flow results. The Stairmand high-efficiency hydro-cyclone geometry is redesigned by the numerical experiment method to obtain high collection efficiency for solid particles. Here the effect of inlet flow velocity and suspended solid particle diameter are simulated to understand their effects on the hydro-cyclone collection efficiency. The fluid flow dynamics are observed, and the detailed distribution of particles inside the hydro-cyclone is presented.

Numerical investigation of flow field characteristics of air injected through an inclined radial slot into a crossflowing stream has been studied for gas flaring applications. CFD is used to simulate turbulent mixing between the inclined slot jet and the crossflowing stream. The slot injection angle with respect to the crossflow, the slot jet velocity, and the slot height were varied in this study. Velocity profiles obtained from the simulations were compared to measured profiles. Simulation results showed that the centerline upflow axial velocities increased with decreasing injection angle and increasing slot height. Results also showed that decreasing injection angle increased the horizontal penetration of the jet flow into the crossflow stream.

The rotating packed bed (RPB) has been widely used in gas-liquid flow systems as a process intensification device, exhibiting excellent mass transfer enhancement characteristics. However, the complex internal structure and the high-speed rotation of the rotor in RPB bring significant challenges to study the intensification mechanism by experiment methods. In the past two decades, Computational Fluid Dynamics (CFD) has been gradually applied to simulate the hydrodynamics and mass transfer characteristics in RPB and instruct the reactor design. This article covers the development of the CFD simulation of gas-liquid flow in RPB. Firstly, the improvement of the simulation method in the aspect of mathematical models, geometric models, and solving methods is introduced. Secondly, new progress of CFD simulation about hydrodynamic and mass transfer characteristics in RPB is reviewed, including pressure drop, velocity distribution, flow pattern, and concentration distribution, etc. Some new phenomena such as the end effect area with the maximum turbulent have been revealed by this works. In addition, the exploration of developing new reactor structures by CFD simulation is introduced and it is proved that such new structures are competitive to different applications. The defects of current research and future development directions are also discussed at last.

In this paper, one of the frequently asked questions for gas cyclone CFD simulation, that “How can the proper near-wall grid size be estimated?”, has been answered. The wall y+ definition was adopted to estimate the near-wall grid sizes. The velocities and friction factors for barrel and cone were obtained by simplifying the previous cyclone pressure drop prediction model to estimate near-wall grid sizes. The representative positions for cyclone cones have been investigated to simplify the near-wall grid estimation. Moreover, new correlations for velocities inside the vortex finder have been developed. The gas cyclones were properly simulated and compared to the previous works to assess the capability of this grid size estimation method. The CFD models developed by the estimated near-wall grid sizes represented the reasonable mean flow properties. Finally, this research concludes that the proposed near-wall grid size estimation method is essential and suitable for gas cyclone CFD simulation.

A numerical model by coupling Monte Carlo Ray Tracing (MCRT) and Computational Fluid Dynamics (CFD) was built to explore the convective heat loss of a cylindrical receiver with built-in coiled tube. Noted that the non-uniform heat flux boundary of the receiver was obtained by optical simulation and the effect of existence of the dish concentrator was taken into account. The variation of flow field and convective heat loss with inclination α, wind direction φ, wind velocity V were analyzed in detail. The results indicate that the presence of concentrator in a windy environment can significantly interfere with the air flow thus affecting the convective heat loss of receiver, and such effect gradually weakens with the increase of α. Except for the case of φ = -90° and 0°≤α ≤ 17°, the convective heat loss with concentrator is always less than that without concentrator. The effect of φ on convective heat loss is complicated and has a great relationship with both V and α. In most cases except for φ = 0°, the convective heat loss takes on a trend of first decreasing and then increasing with varying α. Additionally, a Nusselt number correlation for predicting the convective heat loss of receiver under the effect of dish concentrator was proposed.

This paper discusses about the effect of un-wetted area of tube on the heat transfer performance of horizontal tube falling film evaporation. A 2D CFD model was developed to perform simulations and investigate the output and validated them with published data available in the literature. In the present study the VOF method is used to track the boundary of the liquid vapour from the contours of volume fraction. Effect of varying tube wall temperature or wall super heat (6 to 11°C) on un-wetted area, heat transfer co-efficients and mass transfer co-efficients of the circular tube were obtained from the simulation model and the results were analysed and reasons were identified and discussed here. The threshold value of wall super heat above which phase change occurs between liquid film and tube surface is identified as 6°C. Also it is noted that mass transfer rate increases and then decreases with increase of wall super heat and heat transfer co-efficient showed declining trend.

In this paper, three machine learning (ML) algorithms, Support Vector Regression (SVR), Artificial Neural Networks (ANN), and Extreme Gradient Boosting (XGBoost), are validated to estimate the velocity and turbulence intensity of a wind turbine's wake at distinct downstream distances. To this end, a series of high-fidelity numerical simulations for the NREL Phase VI wind turbine is carried out to generate training and test datasets for the three machine learning algorithms. The predicted wake velocity and turbulence intensity from the ML models are also contrasted with significant existing analytical wake models. Machine learning algorithms estimate velocity and turbulence intensity in the wake in a way commensurate to the Computational Fluid Dynamics (CFD) simulations while running at a similar pace as low-fidelity wake models. The results demonstrate that machine learning-based algorithms can predict velocity and turbulence intensity better with higher precision than the traditional analytical wake models.

The current numerical study aimed for analayzing heat transfer of a spherical water droplet placed in a rectangular duct. The problem particularly deals with air-cooling of the droplet. The computational fluid dynamic technique is used to treat the problem. In order to study the problem, the effect of evaporation on the droplet's heat transfer is taken into consideration to make the problem more realistic. Moreover, various parameters like the inlet velocity and the temperature of the upstream are numerically checked. It is found out that with involving evaporation, the mean temperature of the droplets increases in comparison with the case that there is no evaporation involved. The outcomes of the current study offer useful and deep insight into the evaporative cooling of a water droplet.

Two-body point absorbers are useful for wave energy conversion in high energetic and high wave period sea locations. Analysis and simulation show that the two-body point absorbers have high efficiencies which makes them a potential candidate to promote wave energy harvesting technology towards commercialization and implementation. The submerged body of the two-body point absorbers has a large effect on their performance, hence the question arises: which geometric shape of the submerged body will lead to the best performance of the two-body wave energy harvesters? This paper presents a comprehensive study that analyses the different shapes of the submerged bodies based on the numerical wave tank simulated viscous drag coefficient and hydrodynamic property parameters of the oscillating device. A set of transient and three-dimensional computational fluid dynamic simulations of a numerical wave tank were carried out in Ansys Fluent to determine the viscous drag coefficients of the different submerged body shapes. And then the boundary element hydrodynamic simulation and linear dynamic frequency-domain modeling have been applied to identify the optimized PTO damping. Finally, non-linear time-domain modeling has been applied with the identified viscous damping drag coefficient and PTO damping coefficients to predict and compare the power output performance of different large-scale devices with different shapes of submerged bodies. It is found that each submerged body shape is suitable for a different range of wave frequencies, as one must establish a balance between the hydrodynamic properties and the viscous drag of the submerged body based on the sea location. It is also found that the typical viscous drag coefficient values used in the past studies underestimate the drag coefficient, and the linearized model widely adopted in frequency domain models is non-accurate for the devices with large viscous drag forces.

In this work a CFD numerical study is performed to evaluate the influence of the geometry of the swirl generation chamber on the flow behaviour, the swirl intensity and the unstable oscillations in the airflow pattern. The study shows four different regimes for the flow, separated by three critical swirl intensities. The first one is used to identify the formation of the vortex breakdown. The second one makes a distinction between a free and a wall governed vortex. For a free vortex the instabilities of the flow pattern decrease when the swirl intensity increases showing a negative power correlation between them. However, in a wall governed vortex the instabilities do not correlate with the swirl intensity, being uncontrollable. The third critical swirl intensity indicates the formation of a backflow region near the walls at the bottom zone of the dryer but without impacting the top cylindrical part of the chamber.

Direct impingement (DI) erosion testing of steel and cobalt-based alloys is conducted with particles entrained in air and water. The tests are performed using 75- and 300-μm silica particles with three particle velocities and five impact angles. The mass loss results are used to develop an empirical equation that contains an explicit exponential term for the particle size effect. The erosion equation obtained from the gas jet experiments is implemented into a CFD solver with Lagrangian particle tracking for the liquid-submerged geometry. The CFD-based erosion predictions agree fairly with the experimental measurement for both particles. Strong effect has been observed for the exponential correction term in the erosion equation for liquid-solid flow cases; particularly with small particles at low impact velocities.

To study the internal flow characteristics of the photovoltaic pump under the transient change of solar radiation, the simulation algorithm of the photovoltaic pump system was established by MATLAB/Simulink and CFD for the first time and the results were validated by the test. Firstly, the change rule of pump flow rate and rotation speed under transient solar radiation was obtained by Simulink. Then the results of the change rule were transformed into the boundary condition of CFD by CEL function and the transient flow field in the photovoltaic pump was obtained. The internal flow characteristics and pressure pulsation in the pump were analyzed when the solar radiation increases or decreases transiently. The results demonstrate that the numerical calculation can provide accurate prediction for the characteristics of internal flow in the pump. The numerical results are closed to the experimental results, the minimum error of pressure is 0.93% and the maximum error is 1.78%. When the solar radiation increases transiently, the low pressure area at the impeller inlet gets larger obviously and the jet-wake at the impeller outlet becomes more obvious. The pressure pulsation in the impeller gradually increases and becomes stable after 0.6 s. The pressure from the impeller outlet to the guide vane outlet is stable at 123 kPa. When the solar radiation decreases transiently, the pressure in the impeller takes 1.6 s to be stable. Larger pressure pulsation occurs from the impeller outlet to the guide vane inlet and the maximum differential pressure is 10 kPa. Compared with the transient increase of solar radiation, the pressure in the impeller takes over 0.2 s to stabilize when the solar radiation transient decreases. Meanwhile, the results in this paper can provide references for other transient characteristics research. Highlight First, the relation between pump flow rate and rotation speed under transient solar radiation was obtained by Simulink. Then the results from Simulink were transformed to be the boundary condition of CFD by CEL function. The internal flow characteristics and pressure pulsation in the pump were analyzed under the instantaneous increase or decrease of the solar radiation.

Hydrodynamics in a newly invented bubble-induced inverse gas–liquid-solids three-phase fluidized bed has been studied via both experimental and numerical methods. With experiments in a 3.0 m column of 0.153 m in diameter, four fluidization regimes including a fixed bed regime, a bed expansion regime, a complete fluidization regime, and a freeboard regime have been identified with the increase in the superficial gas velocity. A three-phase Eulerian-Eulerian CFD model was developed to simulate the hydrodynamics in the inverse three-phase fluidized bed and the simulation results have a good agreement with the experimental data. The effects of the particle property and solids loading on the transitions across the flow regimes were numerically studied. A higher solids loading and/or a larger particle density are reported to contribute to an easier fluidization and a faster flow development to the complete fluidization regime. The radial flow structure becomes less uniform with increased inner circulation of the liquid after introducing more bubbles into the column.

Numerical simulations of silicone oil–water two-phase turbulent dispersion mixing in Q-type static mixers (QSM) are performed using computational fluid dynamics (CFD) coupled with a population bala...

A numerical study was performed on the three-dimensional interaction between a laminar boundary layer and the shock wave induced by a sharp, unswept fin mounted perpendicularly on a flat plate at f...

Understanding and control of wake vortices past a circular cylinder is a cardinal problem of interest to ocean engineering. The wake formation and vortex shedding behind a variety of ocean structures such as spars, are subjected to fatigue failure limiting their life span. The additional influences due to ocean waves and currents further exacerbate these effects. In the present study, flow past an isolated circular cylindrical structure subjected to an oscillatory upstream are numerically investigated. These studies involve high resolution simulations over the low Reynolds number range (100-200). Although the practical range of interest is in high Reynolds number range of 10 3 - 10 5 , the flow physics and a number of qualitative and quantitative aspects are similar to the low Reynolds number flows. In the high Reynolds number range, statistical averaging tools in conjunction with suitable closure models would be necessary. The control of wake vortices is achieved with the aid of two small rotors located in the aft of the main cylinder. A control algorithm was coupled to determine the quantum of actuation to the rotating elements. Although control of wake vortices was observed for harmonic in-let forcing, residual vortical structures were found to persist at higher amplitudes of oscillation. To study the efficacy of this control, numerical simulations were further extended, when the circular cylinder was flexibly mounted. The control of flow induced vibrations was observed to be reasonably effective in controlling the wake generated behind the main cylinder due to oscillatory upstream.

A novel vertical augmentation channel housing a direct-drive cross-flow turbine, with nozzles on both the sides of the turbine, was designed and an optimized configuration was obtained. The geometries of the guide nozzle and the front nozzle were optimized under steady flow conditions. The performance of the cross-flow turbine was analyzed using commercial computational fluid dynamics (CFD) code ANSYS-CFX. The optimized design was then evaluated as a wave energy converter both experimentally and computationally. The waves in the numerical wave tank (NWT) were generated using a piston type wave-maker. The optimized design gave a maximum output power of 13.2 W and an efficiency of 48.31% at a wave height of 0.2 m and wave period of 2.75 s for a rotational speed of 35 rpm. The difference between numerical and experimental efficiencies was within 3.5%. In addition to this, particle image velocimetry was used to study the flow characteristics in the augmentation channel and the turbine. The results show that the CFD code captures the flow in the augmentation channel and around the turbine accurately. The optimized design, which occupies less space than other wave energy converters, can be used to efficiently harness energy from the waves.

Particulate flows in a mixture of gas and liquid, i.e. gas–liquid–solid three-phase flows, are frequently encountered both in nature and industry. In such flows, complex interactions between multiple phases, i.e. particle–particle interactions, fluid–particle interactions and interfacial interactions (such as surface tension and particle wetting), play a crucial role. In literature, simulations of three-phase flows are sometimes performed by incorporating interface capturing methods (e.g. VOF method) into the CFD–DEM coupling model. However, it is practically impossible to perform large (industrial) scale simulation because of the high computational cost. One of the strategies often employed to reduce the computational cost in CFD–DEM is to upscale particle size, which is applied mainly to particle single-phase and fluid–solid two-phase flows. The present work is focused on the scaled-up particle model for gas–liquid–solid three-phase flows. The interaction forces between multiple phases are scaled using the general criteria derived from the continuum assumption of particulate flow. A colour function based interface-capturing method with improved interface smoothness is developed, and the diffusion based coarse graining is employed to ensure sufficient space resolution in CFD even when particle size is increased. It is shown that the model developed is capable of predicting the both particles and fluid behaviour in the original system.

The overset grid assembly (OGA) method is an effective computational fluid dynamics technique for the simulation of flows with complex geometries or relative moving parts. Using OGA, the effort for...

Strong laminar/transitional shock boundary layer interactions (SBLIs) have been investigated in a Mach 4 vacuum-driven wind tunnel with supporting computational fluid dynamics analysis. Such flows ...

During the pipeline plugging process, both the pipeline and the pipe isolation tool (PIT) will be greatly damaged, due to the violent vibration of the flow field. In this study, it was proposed for the first time to reduce the vibration of the flow field during the plugging process by optimizing the surface structure of the PIT. Firstly, the central composite design (CCD) was used to obtain the optimization schemes, and the drag coefficient and pressure coefficient were proposed to evaluate the degree of flow field changes. Secondly, a series of computational fluid dynamics (CFD) simulations were performed to obtain the drag coefficient and pressure coefficient during dynamic plugging. And the mathematical model of drag coefficient and pressure coefficient with the surface structure of the PIT were established respectively. Then, a modified particle swarm optimization (PSO) was applied to predict the optimal value of the surface structure of the PIT. Finally, an experimental rig was built to verify the effectiveness of the optimization. The results showed that the improved method could reduce the flow field vibration by 49.5 6%. This study provides a reference for the design of the PIT surface structure for flow field vibration technology.

Eulerian computational fluid dynamics (CFD) models that can predict bubbling behavior accurately are important to predict solids mixing, transport processes, and reactions in fluidized beds. In the...

Liquid atomization is crucial to ensure efficient combustion as it is an inherent part of the injector system. The combustion of fuels relies on effective atomization to increase the surface area of the fuel and consequently achieve high rates of mixing and evaporation. Pressure swirl atomizers are inexpensive and reliable type of atomizer for fuel injection owing to its superior atomization characteristics and relatively simple geometry. The Sauter mean diameter (SMD) of atomizer contributes significantly to the combustion chamber performance. This paper presents a two-step strategy to predict droplet SMD for atomisation model in pressure swirl atomizer through the combination of experimentally validated Computation Fluid Dynamics (CFD) and Optimal Latin Hypercubes (OLHC) Design of Experiments (DoE) techniques. A three-dimensional Eulerian two-phase CFD model is developed to account for liquid and gas phases as a single continuum with high-density variation at large Reynolds and Weber numbers and validated against experimental measurements, before being employed to carry out a parametric study involving operating conditions and fluid properties of the pressure swirl atomizer. The atomizer is then represented in terms of four design variables, namely liquid viscosity, liquid velocity, surface tension and atomizer exit diameter. An 87-point OLHC DoE is constructed within the design variables space using a permutation genetic algorithm resulting in an accurate SMD prediction. Results show the newly developed SMD prediction is found to be superior compared with existing correlations and indicate significant improvement in the droplets SMD.