Discrete Phase Simulations Research Articles

On a model-based approach to improve intranasal spray targeting for respiratory viral infections

The nasopharynx, at the back of the nose, constitutes the dominant initial viral infection trigger zone along the upper respiratory tract. However, as per the standard recommended usage protocol (“Current Use”, or CU) for intranasal sprays, the nozzle should enter the nose almost vertically, resulting in sub-optimal nasopharyngeal drug deposition. Through the Large Eddy Simulation technique, this study has replicated airflow under standard breathing conditions with 15 and 30 L/min inhalation rates, passing through medical scan-based anatomically accurate human airway cavities. The small-scale airflow fluctuations were resolved through use of a sub-grid scale Kinetic Energy Transport Model. Intranasally sprayed droplet trajectories for different spray axis placement and orientation conditions were subsequently tracked via Lagrangian-based inert discrete phase simulations against the ambient inhaled airflow field. Finally, this study verified the computational projections for the upper airway drug deposition trends against representative physical experiments on sprayed delivery performed in a 3D-printed anatomic replica. The model-based exercise has revealed a new “Improved Use” (or, IU) spray usage protocol for viral infections. It entails pointing the spray bottle at a shallower angle (with an almost horizontal placement at the nostril), aiming slightly toward the cheeks. From the conically injected spray droplet simulations, we have summarily derived the following inferences: (a) droplets sized between 7–17 μm are relatively more efficient at directly reaching the nasopharynx via inhaled transport; and (b) with realistic droplet size distributions, as found in current over-the-counter spray products, the targeted drug delivery through the IU protocol outperforms CU by a remarkable 2 orders-of-magnitude.

Effects of guide holes on the performance of a vertical turbo air classifier

AbstractThe wide usage of guide parts makes it one of the most interesting research hot spots in the field of fluid machinery. To improve the flow field distribution of the vertical turbo air classifier, the guide holes in the air intake region are designed. The flow fields of the classifiers with and without guide holes are simulated using ANSYS‐FLUENT. The gas‐phase simulation results show that the guide holes have a ‘diversion’ effect on the airflow, decreasing the tangential velocity and increasing the radial velocity of the airflow. After the airflow passes through the guide holes, the small guide hole sizes cause the large radial velocity and the strong ‘diversion’ effect, which can improve the flow field distribution. The well‐distributed flow field of the elutriation region and annular region are obtained when the guide hole size is 7 mm × 7 mm. The discrete phase simulation results show that the cut size of the classifier without the guide holes is 9.1 μm. The cut size is 13.4 μm when the guide hole size is 7 mm × 7 mm. With the increase in the guide hole size, the cut size increases. However, when the guide hole size is larger than 10.5 mm × 10.5 mm, the cut size is almost kept unchanged, which is 22.9 μm.

Effects of a Guide Cone on the Flow Field and Performance of a New Dynamic Air Classifier

A new dynamic air classifier was designed to address the problems of uneven material dispersion and high dust concentration in industrial applications of turbo air classifiers. This paper presents a study on the use of guide cones in the new dynamic air classifier. The ANSYS-Fluent 19.2 software was implemented to simulate the airflow in the dynamic air classifier, and the impact of the guide cone size on the flow field and classification performance of the dynamic air classifier was investigated. The simulation results indicated that with the increase in the guide cone height, the flow field distribution becomes reasonable and the velocity distributions become uniform. When the guide cone height is greater than twice the distance between the guide cone and the bottom of the rotor cage, there is no discernible change in the flow field distribution and classification efficiency. When the guide cone diameter is approximately 0.9 times the diameter of the rotor cage, the airflow pathline is more reasonable, and the flow field and velocity distributions are more uniform. An improper guide cone diameter and height will worsen the classification environment, resulting in a significant decline in classification performance. The material experimental and discrete phase simulation (DPM) showed that DPM can anticipate the changing trends of the cut size and classification accuracy. This study provides theoretical assistance for the structural design and optimization of an air classifier.

The Role of HVAC Design and Windows on the Indoor Airflow Pattern and ACH

The purpose of heating, ventilation, and air conditioning (HVAC) systems are to create optimum thermal comfort and appropriate indoor air quality (IAQ) for occupants. Air ventilation systems can significantly affect the health risk in indoor environments, especially those by contaminated aerosols. Therefore, the main goal of the study is to analyze the indoor airflow patterns in the heating, ventilation, and air conditioning (HVAC) systems and the impact of outlets/windows. The other goal of this study is to simulate the trajectory of the aerosols from a human sneeze, investigate the impact of opening windows on the number of air changes per hour (ACH) and exhibit the role of dead zones with poor ventilation. The final goal is to show the application of computational fluid dynamics (CFD) simulation in improving the HVAC design, such as outlet locations or airflow rate, in addition to the placement of occupants. In this regard, an extensive literature review has been combined with the CFD method to analyze the indoor airflow patterns, ACH, and the role of windows. The airflow pattern analysis shows the critical impact of inflow/outflow and windows. The results show that the CFD model simulation could exhibit optimal placement and safer locations for the occupants to decrease the health risk. The results of the discrete phase simulation determined that the actual ACH could be different from the theoretical ACH as the short circuit and dead zones affect the ACH.

The quantitative characterization of the ignition process for a lean staged injector: Influence of the air split between pilot swirlers

The ignition of a lean staged injector aimed at aeronautical application is a transient and complex phenomenon, which involves fluid dynamics, turbulent mixing, chemical kinetics, as well as their mutual interactions. In the present research, a staged injector, designed based on stratified partially premixed combustion concept, is introduced. The ignition performance of stratified partially premixed injectors with different air split ratios between pilot swirlers are experimentally acquired, which exhibits apparent distinctions. In order to make quantitative analyses, the classical physical ignition model is improved, in which the flame propagation process is further divided into the axial and radial propagation sub-processes. Nonreacting flow field and discrete phase simulations, validated by experiment results, are utilized to obtain the velocity and spray distributions. Physical parameters characterizing the ignition sub-processes are defined and calculated based on the numerical simulation results. Conclusions are made by comparing the physical parameters of the ignition sub-processes. The radial propagation of the ignition kernel is responsible for the ignition performance difference between the two injectors with different pilot air split ratios (PASR) in that the average equivalence ratio along the radial propagation route of PASR = 7:3 is one order richer than that of PASR = 2:8. The present ignition analysis and model can be further extended and developed for the optimization of ignition performance of lean staged injector.

Trajectory integrated smoothening of exchange fields for discrete phase simulations

Eulerian-Lagrangian simulations often require a two-way coupling, where the discrete phase affects the continuous phase and vice versa. The continuous phase in a CFD-simulation is typically represented on a computational mesh, which consists of a number of discrete cells. As the discrete phase is not directly associated with this mesh, a mapping from the discrete phase to the continuous phase is required in order to couple the two phases. This will distribute the exchange rates from the discrete to the continuous phase, where the exchanged properties can be thermal energy, momentum, species etc.The mapping can be done in several ways, and different methods exist. Some of these include a smoothening step, which ensures that the exchange fields do not contain large spikes between any two neighbouring cells, which typically increases the convergence rate of the CFD simulation. Gaussian smoothening is often applied, where the discrete phase exchange rates are spread to the surrounding cells by a normal distribution with a specified standard deviation. This paper proposes a new weight for distributing the discrete phase exchange rates to the continuous phase cells. This is done by analytically integrating any distribution over the entirety of the particle trajectory, and only requires the probability- and cumulative density functions to be specified.The proposed weight is used in combination with three different smoothening methods: node-based, kernel-based, and cell-based. Common existing weight distributions are also investigated, which are used in combination with the different methods. Each method and weight combination is compared with the analytical ground-truth exchange field, where the distributions are accurately integrated over the cell volumes.The results show that the proposed weight has an average error of ≈ 2 % in the exchange field for the test case used. This is about three times more accurate compared to existing weights, where the exchange field is not integrated along the trajectory of the particle. Alternative distributions were investigated to decrease the computational requirements. It was found that a fourth-order polynomial distribution was about 20 times faster to evaluate, whilst the error induced by switching to this distribution was ≈ 4.5 % compared with the previous ≈ 2 %.

Effects of the shape and height of artificial 2D roughness elements on deposition of nano and microparticles in the turbulent gas flow inside a horizontal channel

In this paper, deposition of the particles in turbulent incompressible gas flow inside a horizontal channel with different two-dimensional artificial roughness shapes and heights is studied. The Eulerian–Lagrangian method is used for numerical simulation of the particulate gas flow. The Reynolds stress model (RSM) with enhanced wall treatment is applied to simulate the anisotropic turbulence in the gas flow. The Lagrangian equation of the particles motion includes drag, gravity, Saffman lift, and Brownian forces. Discrete phase simulations are compared with the available correlations for a smooth channel to show the validation of the simulations. The results show that the rate of deposition for small particles is affected significantly by the flow pattern in the space between two roughness elements. For small particles (τ+<10), deposition of the particles depends on the v component of the gas velocity. Gravity force is assumed to be perpendicular to the main flow direction. For large particles (τ+>10), the gravity force is more effective on the deposition velocity.

Design of a new double layer spreading plate for a turbo air classifier

In order to improve the material dispersion and reduce the probability of collision and aggregation of particles in a turbo air classifier, compared to a single layer spreading plate, a new double layer spreading plate based on theoretical analysis on the material dispersion is presented in this paper. Discrete phase simulations between the single and double layer spreading plates are implemented using Fluent 6.3.26. The different travelling time of particles via the upper and lower plates indicates the double layer spreading plate can improve the material dispersion and the simulated Tromp curves of the single and double spreading plates also show the cut size and the imperfection are decreased while the sharpness of separation is increased for the turbo air classifier with the double layer spreading plate. Calcium carbonate classification experimental results are in agreement with the simulated results. Compared to single layer spreading plate, the cut size can be decreased up to 25.24% and the sharpness of separation can be increased up to 52.47% for double layer spreading plate, and the imperfection of Tromp curve for double layer spreading plate is smaller that means it closer to the ideal classification curve. It shows the double layer spreading plate put forward in this paper can effectively improve the material dispersion in the classifiers.

Effects of axial inclined guide vanes on a turbo air classifier

For a turbo air classifier, the upward axial velocity in the annular region will cause the negative influence on the stability of flow field, and it is also detrimental to material dispersion. As a result, the classification accuracy will be reduced. In order to decrease the upward axial velocity, a downward force must be introduced to offset it. According to the guiding principle of guide vanes, the axial direction of airflow will be changed when the guide vanes are inclined. In this paper an axial inclined guide vane model was designed. Four models (T-0, T-2.5, T-5, T-7.5) were established with axial inclined angles of 0°, 2.5°, 5° and 7.5°. Fluent software was used to simulate the inner flow field of different structures. The simulation results show that axial inclined guide vanes can decrease the upward axial velocity in the annular region. Especially, when the inclined angle is 2.5°, the upward axial velocity is decreased and the tangential velocity is increased. This is favorable to keep the flow field stable. At the same time the classification force field is enhanced to improve the dispersion of the powders. Discrete phase simulation results reveal that particle residence time in the annular region of structure T-2.5 is shorter than it is in the annular region of structure T-0. This can reduce the collision probability of particles and the energy cost is reduced. The partial classification efficiencies of T-2.5 are higher than that of T-0. From the numerical Tromp curves, it is observed that the cut size of T-2.5 is smaller than that of T-0. The classification accuracy of T-2.5 is 90.7%, while that of T-0 is 88.5%. That means that the classification performance is improved with the new structure. Calcium carbonate classification experiment results also show that the cut size decreases by 0.97–8.42μm and the accuracy increases by 6%–9% for the structure T-2.5, compared to the structure T-0. Therefore, the structure T-2.5 is more favorable for classification than the structure T-0. These actual experimental results are in good agreement with the simulation results and the significance of this optimization is proved.

Improving the applicability of discrete phase simulations by smoothening their exchange fields

Discrete phase (DP) models are widely used in simulating dilute particle flows. In these methods point-masses that are representing parcels of particles are traced through the computational domain by evaluating local force balances. Their influence on the continuous phase is expressed by momentum exchange fields, which are based on the loss or gain of the particles’ momentum. In order to ensure a numerically stable simulation it is important to guarantee smooth momentum exchange fields. As a consequence often an excessive number of parcel trajectories have to be traced. In many applications this trajectory calculation step is limiting the overall simulation performance. In this study three procedures of smoothening the DP momentum exchange fields, namely (a) diffusive smoothening, (b) particle cloud model as well as a (c) ‘darning socks’ model are presented. Their applicability is evaluated by an analytic test case [R. Garg, C. Narayanan, S. Subramaniam, A numerically convergent Lagrangian–Eulerian simulation method for dispersed two-phase flows, Int. J. Multiphase Flow 35 (2009) 376–388] as well as by a typical pneumatic conveying situation. It can be shown that with adequate smoothening approaches DPM simulations can be significantly accelerated due to fewer required trajectories and larger fluid flow time-steps.

Numerical studies of bubble formation dynamics in gas–liquid–solid fluidization at high pressures

A discrete phase simulation (DPS) is conducted to investigate multi-bubble formation dynamics in gas–liquid–solid fluidization systems. A numerical technique based on computational fluid dynamics (CFD) with the discrete particle method (DPM) and volume tracking represented by the volume-of-fluid (VOF) method is developed and employed for the simulation. A bubble-induced force (BIF) model, a continuum surface force (CSF) model, and Newton's third law are applied to account for the couplings of particle–bubble, bubble–liquid and particle–liquid interactions, respectively. A close-distance interactive effect between colliding particles is considered in the formulation of the particle–particle collision model. Two-dimensional simulations of the behavior of bubble formation from multi-orifices in liquids and liquid–solid suspensions are conducted at high pressures up to 19.4 MPa under constant gas flow conditions. Experiments are also conducted in this study to quantify the bubble formation behavior from a single orifice under comparable gas flow conditions. The study indicates that the liquid flow dynamics induced by adjacent bubbles and bubble wake significantly affects the multi-bubble formation process. The simulation results on the initial bubble size and bubble formation time under various pressures and solids hold-up are found to be in good agreement with those obtained experimentally as well as those predicted based on the analytical model developed earlier by the authors.

Discrete phase simulation of gas–liquid–solid fluidization systems: single bubble rising behavior

A computational scheme for discrete-phase simulation of a gas–liquid–solid fluidization system and a two-dimensional code based on it are developed in this study. In this scheme, the volume-averaged method, the dispersed particle method, and the volume-of-fluid (VOF) method are used to account for the flow of liquid, solid particles, and gas bubbles respectively. The gas–liquid interfacial mass, momentum and energy transfer is described by a continuum surface force (CSF) model. A close-distance interaction (CDI) model is introduced which illustrates the motion of the particle prior to its collision; upon collision, the hard sphere model is employed. The particle–bubble interaction is formulated by incorporating the surface tension force in the equation of motion of particles. The particle–liquid interaction is brought into the liquid phase Navier–Stokes (N–S) equations through the use of Newton's third law of motion. The volume-averaged liquid phase N–S equations are solved using the time-split two-step projection method. The simulation results using this scheme are verified for bed expansion and pressure drop in liquid–solid fluidized beds. The simulation of a single bubble rising in a liquid–solid suspension and the particle entrainment by a bubble on the surface of the bed is conducted and the results are in agreement with the experimental findings.

Numerical studies of bubble and particle dynamics in a three-phase fluidized bed at elevated pressures

A discrete phase simulation is conducted to study the bubble and particle dynamics in a three-phase fluidized bed at high pressures. The Eulerian volume-averaged method, the Lagrangian dispersed particle method, and the volume of fluid (VOF) method are employed to describe, respectively, the motion of liquid, solid particles, and gas bubbles. A bubble-induced force model, a continuum surface force (CSF) model, and Newton's third law are applied to illustrate, respectively, the coupling effect of particle–bubble, gas–liquid, and particle–liquid interactions. A close-distance interaction (CDI) model is included in the particle–particle collision analysis, which considers the liquid interstitial effect on colliding particles. Effects of the pressure and solids holdup on the bubble rise characteristics such as the bubble rise velocity, bubble shape and trajectory are examined. Simulations of the bubble rise velocity at various solids holdups and pressures are conducted along with the maximum stable bubble size and the particle–bubble interactions. The simulated results compare favorably with the experimental data and calculation from a mechanistic model.