Effect Of Turbulent Dispersion Research Articles

A novel transparent cabin used in the classroom during the coronavirus pandemic: a CFD analysis

A coronavirus family is a diverse group of many viruses. Coronavirus disease 19 (COVID-19) spreads when an infected person breathes out droplets and very small particles that contain the virus. These droplets and particles can be breathed in by other people or land on their eyes, noses, or mouths. In this paper, the airflow distribution and the movement of coronavirus particles during normal breathing and sneezing in classrooms have been studied using a CFD model developed in ANSYS® 2022R2. The objective is to find ways to control the spread of the virus that enable us to practice academic activity and deal normally with the pandemic and the spread of the disease. Experiments were done with more than one turbulence model to know which was closest to the experiments as well as to determine the best number of meshes in the classroom. The effect of turbulent dispersion on particles is resolved using a discrete random walk model for the discrete phase and the RANS model for the continuous phase in a coupled Eulerian–Lagrangian method. Furthermore, that is done in two scenarios: the first is to find the best ventilation configuration by investigating the following parameters: the effect of air change per hour, the height of the air inlets and outlets, and the infected student's position. The second is to control the spread of the coronavirus in the classroom in the event of sneezing from an infected student by placing cabins and an air filter with optimal design installed at the top around each student. It was found that optimal ventilation is achieved when fresh air enters from the side walls of the classroom at a distance of 1 m from the floor and the air exits from the ceiling in the form of two rows, and the rate change of air per hour (ACH) is 4, which leads to energy savings. In addition, a novel transparent cabin is designed for the student to sit in while in the classroom, consisting of a high-efficiency particulate air filter (HEPA) that collects any contamination and recirculates it from the top of the cabin back into the classroom with different fan speeds. Through this study, this cabin with a filter was successfully able to prevent any sneeze particles inside from reaching the rest of the students in the classroom.

QEEFoam: A Quasi-Eulerian-Eulerian model for polydisperse turbulent gas-liquid flows. Implementation in OpenFOAM, verification and validation

In this paper we present a new multiphase computational model for polydisperse turbulent gas-liquid flows. In this model the gas phase is transported by a single convection equation and the effect of turbulent dispersion is addressed by including a diffusion term. In order to close the system of equations, the gas phase velocity is calculated by employing the slip velocity concept or by solving an ODE. This procedure shares similarity with the Euler-Lagrange (E-L) method, in which the gas velocity is updated by bubble Lagrangian tracking, and with the Euler-Euler (E-E) method, and for this reason it is called the Quasi-Eulerian-Eulerian (Q-E-E) method. In order to account for polydispersity one single transport equation is added to describe the effects of bubble breakage and coalescence on the mean bubble size. The novel Q-E-E method was implemented in the open-source code OpenFOAM-7 and was used to simulate turbulent gas-liquid flows with three different geometries operating under different conditions. The predictions for the dynamical vortex structures, local phase fraction, global gas holdup, mean bubble size and vertical/horizontal liquid velocities were verified against the solution provided by the E-L solver or against published experimental data. Good agreement was found and with extremely small computational costs.

Large-Eddy Simulation of Turbulent Dispersion Effects in Direct Injection Diesel and Gasoline Sprays

<div class="section abstract"><div class="htmlview paragraph">In most large-eddy simulation (LES) applications to two-phase engine flows, the liquid-air interactions need to be accounted for as source terms in the respective governing equations. Accurate calculation of these source terms requires the relative velocity “seen” by liquid droplets as they move across the flow, which generally needs to be estimated using a turbulent dispersion model. Turbulent dispersion modeling in LES is very scarce in the literature. In most studies on engine spray flows, sub-grid scale (SGS) models for the turbulent dispersion still follow the same stochastic approach originally proposed for Reynolds-averaged Navier-Stokes (RANS). In this study, an SGS dispersion model is formulated in which the instantaneous gas velocity is decomposed into a deterministic part and a stochastic part. The deterministic part is reconstructed using the approximate deconvolution method (ADM), in which the large-scale flow can be readily calculated. The stochastic part, which represents the impact of the SGS flow field, is assumed to be locally homogeneous and isotropic and, therefore, governed by a Langevin-type equation. The model is applied to the spray G and spray H conditions defined by the engine combustion network (ECN) group. Simulation results are compared with the available experimental data for spray characteristics such as penetration rates, mixture fraction profile, and droplet velocity and Sauter mean diameter (SMD) distributions. Simulations with no dispersion and the commonly used RANS-type stochastic model are also performed for comparison purposes. Results show that the turbulent dispersion has a considerable impact on quantitative spray characteristics such as projected liquid volume (PLV) fraction, droplet SMD and velocity, and fuel vapor mixture fractions. On the other hand, the macroscopic spray characteristics such as liquid- and vapor-phase penetrations are not significantly affected by the dispersion modeling. The proposed SGS model also improves the prediction of spray and ignition characteristics at the spray conditions studied in this work.</div></div>

Effect of turbulent dispersion on hydrodynamic characteristics in a liquid jet ejector

Gas induction using a liquid jet is an extensively studied phenomenon. Many studies have been published detailing various hydrodynamic and mass transport aspects of gas induction in ejectors. Conversely, multiple studies have been published detailing jet dynamics, jet break up, nozzle geometry, effects of turbulence etc. In the modelling of the jet ejector systems CFD framework is used as the flow of gas is coupled with the liquid flow and the flow parameters like volume fraction, pressure drop/profile and velocity profiles both local and average are highly interdependent. Hence, it becomes important to capture all the flow physics in the simulations in order to understand the hydrodynamics. In the previous models the effect of turbulent dispersion was not included which led to incorrect calculation of phase profile, and other related parametric values. In the present work, the turbulence effects and its impact on the jet dynamics and gas induction rate in an ejector have been studied. Capturing the correct phase as well as velocity profile is imperative for the extension of the model to mass transfer and reactions. Lastly, other hydrodynamic properties like pressure drop, phase hold up and pressure profile help better the design correlations for jet ejectors.

Numerical investigation of jet agitation in a nuclear liquid waste storage tank

Radioactive liquid waste is often stored in a large capacity (150 m3) horizontal cylindrical tanks. It is necessary to keep the contents of the tank agitated to prevent the settling of fine solids in the tank. In extreme cases, solids settled at the tank base may invoke the system malfunction. This paper deals with the Computational Fluid Dynamic (CFD) modeling of the agitation mechanism considering the turbulent dispersion effects. The simulations are conducted on a standard tank geometry to arrive the optimum jet velocity required to suspend the settled solid particles thoroughly. The distribution of volume phase fraction, velocity magnitude, turbulence kinetic energy (TKE) and eddy dissipation of each phase for different inlet jet velocities (v = 10–25 m/s) have been presented. The spatial variation of these quantities are measured at three different planes in the vessel mainly in the vicinity of the nozzle exit. The results indicate that the jet velocity is a significant parameter that influences the particle suspension. Parametric studies have also been carried out for four different particle sizes, viz. dp = 5, 10, 50 and 100 μm. The present study revealed that, for the range of parameters covered, the smallest (dp = 5 μm) and the largest (dp = 100 μm) particle sizes has least effect in terms of solids suspension.

Effects of Turbulent Dispersion on Water Droplet Impingement Based on Statistics Method

Research on the water droplet motion and impact on surface is the basis of aircraft icing prediction and design of ice protection system. First, a new computational method based on statistical theory was developed in the Euler–Lagrange framework to calculate the local water impingement coefficient on the surface, which could be used to study the effect of turbulent dispersion on the water droplet motion and impingement characteristics. Second, based on the RANS model for the air flow field, taking engine cone surface with or without slot as examples, the influence of turbulent dispersion on the water impingement coefficient on the surface was comparatively analyzed with the discrete random walk model. For the cone without film slot, turbulence causes a little impact on water droplet impingement. However, for the slotted cone, water droplet collection calculation must consider the effect of turbulence due to the stronger turbulence induced by the jet air. Further studies show that the effect is enhanced with the decrease of water droplet diameter. Finally, discussion about turbulent effects was proposed. This research about the influence of turbulent dispersion will be helpful to improve the accuracy of the water droplet impingement calculation for some complex geometries.

A method to quantitatively apportion pollutants at high spatial and temporal resolution: the Stochastic Lagrangian Apportionment Method (SLAM).

We introduce a method to quantify upwind contributions to concentrations of atmospheric pollutants. The Stochastic Lagrangian Apportionment Method (SLAM) carries out the following: (1) account for chemical transformations and depositional losses; (2) incorporate the effects of turbulent dispersion; (3) simulate the locations of the sources with high spatial and temporal resolution; and (4) minimize the impact from numerical diffusion. SLAM accomplishes these four features by using a time-reversed Lagrangian particle dispersion model and then simulating chemical changes forward in time, while tagging and keeping track of different sources. As an example of SLAM's application, we show its use in apportioning sources contributing to ammonia (NH3) and ammonium particulates (p-NH4(+)) at a site in southern Ontario, Canada. Agricultural emissions are seen to dominate contributions to NH3 and p-NH4(+) at the site. The source region of NH3 was significantly smaller than that of p-NH4(+), which covered numerous states of the American Midwest. The source apportionment results from SLAM were compared against those from zeroing-out individual sources ("brute force method"; BFM). The comparisons show SLAM to produce almost identical results as BFM for NH3, but higher concentrations of p-NH4(+), likely due to indirect effects that affect BFM. Finally, uncertainties in the SLAM approach and ways to address such shortcomings by combining SLAM with inverse methods are discussed.

An analytical model for dispersion of biological particles emitted from area sources: Inclusion of dispersion in the crosswind direction

An analytical model for dispersion of biological particles such as spores and pollens released from finite area sources into the atmospheric boundary layer is proposed. The model is applicable to rectangular fields aligned with the mean wind and accounts for effects of turbulent dispersion in the vertical and crosswind direction, as well as depletion of airborne material due to dry deposition. Predictions for the mean particle concentration above the area source and ground deposition downwind from it are derived and validated against detailed numerical simulations of pollen dispersal using large eddy simulation. Effects of particle settling velocity and area source size and geometry on dispersal patterns are investigated. Results show that along the centerline above the source, effects of crosswind dispersion are negligible (except for very narrow area sources). Ground deposition fluxes downwind from the source are strongly affected by crosswind dispersion. Similarly to area sources infinitely long in the crosswind direction, deposition fluxes far from rectangular sources display a power-law decay with distance. The power-law exponent is larger than the one for infinitely wide fields and depends on the relative importance of gravitational settling and turbulent dispersion in the vertical and crosswind directions, but does not depend on source geometry. However, the distance from the source at which the power-law decay is first observed does depend on source geometry.

Thin Phytoplankton Layers: Characteristics, Mechanisms, and Consequences

For over four decades, aggregations of phytoplankton known as thin layers have been observed to harbor large amounts of photosynthetic cells within narrow horizontal bands. Field observations have revealed complex linkages among thin phytoplankton layers, the physical environment, cell behavior, and higher trophic levels. Several mechanisms have been proposed to explain layer formation and persistence, in the face of the homogenizing effect of turbulent dispersion. The challenge ahead is to connect mechanistic hypotheses with field observations to gain better insight on the phenomena that shape layer dynamics. Only through a mechanistic understanding of the relevant biological and physical processes can we begin to predict the effect of thin layers on the ecology of phytoplankton and higher organisms.

A large‐eddy model for cirrus clouds with explicit aerosol and ice microphysics and Lagrangian ice particle tracking

AbstractWe introduce a novel large‐eddy model for cirrus clouds with explicit aerosol and ice microphysics, and validate its central components. A combined Eulerian/Lagrangian approach is used to simulate the formation and evolution of cirrus. While gas and size‐resolved aerosol phases are treated over a fixed Eulerian grid similar to the dynamical and thermodynamical variables, the ice phase is treated by tracking a large number of simulation ice particles. The macroscopic properties of the ice phase are deduced from statistically analysing large samples of simulation ice particle properties. The new model system covers non‐equilibrium growth of liquid supercooled aerosol particles, their homogeneous freezing, heterogeneous ice nucleation in the deposition or immersion mode, growth of ice crystals by deposition of water vapour, sublimation of ice crystals and their gravitational sedimentation, aggregation between ice crystals due to differential sedimentation, the effect of turbulent dispersion on ice particle trajectories, diabatic latent and radiative heating or cooling, and radiative heating or cooling of ice crystals. This suite of explicitly resolved physical processes enables the detailed simulation and analysis of the dynamical–microphysical–radiative feedbacks characteristic of cirrus.We draw special attention to the ice aggregation process which redistributes large ice crystals vertically and changes the ice particle size distributions accordingly. We find that aggregation of ice crystals is the key process to generate precipitation‐sized ice crystals in stratiform cirrus. A process‐oriented algorithm is developed for ice aggregation based on the trajectories and sedimentation velocities of simulation ice particles for use in the dynamically and microphysically complex, multi‐dimensional large‐eddy approach. By virtue of an idealized model set‐up, designed to isolate the effect of aggregation on the cirrus development, we show that aggregation and its effect on the ice crystal size distribution in the model is consistent with a theoretical scaling relation, which was found to be in good agreement within situmeasurements. Copyright © 2010 Royal Meteorological Society

Mixing and Combustion Characteristics of Kerosene in a Model Supersonic Combustor

In this numerical study, supersonic combustion of kerosene in three model combustor configurations is investigated. To this end, 3-D, compressible, turbulent, nonreacting, and reacting flow calculations with a single step chemistry model have been carried out. For the nonreacting flow calculations, the droplet diameter distribution at different axial locations, variation of the Sauter mean diameter, and the mixing efficiency for three injection pressures are presented and discussed. In addition, the effect of turbulent dispersion on the mixing efficiency is studied using a stochastic model in conjunction with the two-equation shear stress transport k-ω turbulence model. For the reacting flow calculations, contours of heat release and axial velocity at several axial locations are used to identify regions of heat release inside the combustor. Combustion efficiency predicted by the present results is compared with earlier predictions for all the combustor models. Furthermore, the predicted variation of static pressure along the combustor top wall is compared with experimental data reported in the literature. Calculations show that the penetration and spreading of the fuel increases with an increase in the injection pressure. Predicted values of the combustion efficiency are more realistic when the spray model is used for modelling the injection of the fuel. The importance of the mixing process, especially for a liquid fuel such as kerosene, on the prediction of heat release is discussed in detail.

Choice of urea-spray models in CFD simulations of urea-SCR systems

The sensitivity of modeling choices to obtained results for Eulerian–Lagrangian CFD simulations of urea-SCR systems has been investigated for a system consisting of an AdBlue-spray located at the exhaust pipe wall, directed into the exhaust gas flow. The decomposition of urea is modeled as being heat transfer limited and taking place at a constant temperature (425 K). It is shown that modeling choices may affect the predicted extent of wall hit, which types of droplets that are predicted to hit the wall, and also where they will do so. The influence of the different forces due to drag, buoyancy, lift effects, thermophoresis and history effects was investigated, proving that only the forces due to drag and buoyancy are necessary to correctly describe droplet motion within this system. It is necessary to use a droplet drag coefficient that takes the current level of droplet distortion into account. A stochastic particle tracking model will describe the effects of turbulent dispersion, but also make the simulation results sensitive to the quality of the turbulence model's prediction of the turbulent fluctuating velocities. Using such a model will also resolve some of the enhancement of heat and mass transfer caused by the continuous acceleration/deceleration of droplets by turbulent eddies.

Numerical Simulations of Capillary Aerosol Generation: CFD Model Development and Comparisons with Experimental Data

For a capillary aerosol generation system, the mechanisms governing droplet transport from the capillary tip through deposition in an enclosed geometry have not been previously explored. The objective of this study was to develop and validate a CFD model of transport and deposition for capillary-generated albuterol in water aerosols in a standard USP induction port used for pharmaceutical aerosol testing. Within this system, comparisons have been made between experimental measurements and numerical predictions of the jet angle, aerosol deposition in a sectioned induction port model, and size distributions of exiting particles. The CFD model employed accounts for multiscale and multicomponent flow initialized at the 57 μ m capillary tip and extending through the USP induction port with 30 L/min of co-flow air. A discrete Lagrangian particle tracking algorithm with corrections for near-wall anisotropic turbulence has been implemented to model the polydisperse particle phase including the effects of turbulent dispersion and evaporation. Results indicated good agreement between predictions of the numerical model and experimental in vitro measurements. The experimental mean (SD) total mass fraction of drug deposited in the sectioned induction port was 14.6 (1.1)%. Numerical predictions of deposited mass fraction for non-evaporating particles and evaporating droplets were 13.1% and 13.3%, respectively, resulting in relative differences of 10.3% and 8.9%. Comparisons between in vitro measurements and predictions within individual sections of the induction port resulted in relative differences as low at 0.75%. The predicted mass median diameters exiting the induction port for the particle and evaporating droplet models were 3.07 and 3.45 μ m, respectively, in comparison to an experimental value of 3.06 μ m. The numerical model developed in this study can be applied to optimize the capillary aerosol generation process and improve its delivery of aerosols to the lung.

Spray Measurements and Numerical Analysis on an Impinging Jet Injector

The spray characteristics of an impinging jet injector have been investigated experimentally and numerically. The droplet size distribution, the velocity and the mass flux distribution were measured using Phase-Doppler Anemometry (PDA), and approximated to distribution functions in order to obtain the input data for the numerical simulation by KIVA-3 V. The simulation indicated that the effects of turbulent dispersion on the behavior of droplets must be included in the numerical model. The local droplet size distribution is dominated by the turbulence intensity, because small droplets tend to be transported by the drag of surrounding turbulent gas flow, while the trajectories of large ones are almost straight. Computational grid sizes are also important factor because the turbulence intensity strongly depends on the radial width. Simulations with coarse grids resulted in poor predictions, in which the turbulence intensity was overestimated. It is important to choose proper grid sizes with considering the balance of the accuracy and the computational cost.

Effects of turbulent dispersion on the wind speed profile in the surface layer

New Reynolds mean momentum equations including turbulent viscosity and dispersion are used to analyze the vertical profile of wind speed in the surface layer. It is demonstrated that the wind profile of the surface layer including turbulent dispersion has a logarithmic modification on the classical power law. Under the condition of unstable stratification, the effect of dispersion is stronger than under stable stratification. Under neutral stratification, the power law degenerates to the logarithmic law, but the von Karman constant is replaced by k 1 = (1+ k / 4)−1 k, which can also be obtained by similarity theory.

On the modelling of bubble plumes in a liquid pool

Turbulent, bubble plumes are investigated numerically using the commercial, Computational Fluid Dynamics (CFD) code CFX-F3D. A six-equation, two-fluid model approach is adopted, in which interphase momentum exchange models include buoyancy, drag, added mass, lift and turbulent dispersion effects. Particular attention is paid to turbulence modelling, in which generation and dissipation resulting from interaction between bubbles and liquid are specifically taken into account within the context of an extended k − ϵ turbulence model. Results from a number of calculations are presented and compared against published, experimental bubble plume data. It is suggested that existing bubble/liquid interaction models for plumes may be grouped into three categories: those which produce lateral bubble spreading, those which diffuse the ambient liquid velocity field, and those which couple the plume to the surrounding liquid and thereby ultimately govern the pool mixing behaviour.

Experimental investigation of a turbulent bubbly mixing layer

An experimental investigation of a turbulent air-water bubbly flow in a plane vertical mixing layer is presented. An important characteristic of this bubbly flow is that the slip velocity is of the same order of magnitude as the liquid velocity. For various inlet conditions of liquid velocity and void fraction, the distributions of velocity, turbulence intensity and void fraction were measured. The mean velocity fields in both phases present self-similar evolutions that preserve the main characteristics of single-phase mixing layer. The spreading rate of the mixing layer is found to be significantly greater in bubbly flow than in single-phase flow. Moreover, the global structure of the flow proved to be sensitive to void fraction contrast at the inlet. The void fraction distributions exhibit a pronounced peak in the wake of the splitter plate. This peak decreases in intensity and is displaced significantly in the lateral direction. The turbulence intensity is also greater in bubbly mixing layers: it is shown that this effect is related to the bubble drift velocity. A heuristic model for the separation of bubble and shear-induced velocity fluctuations is presented and discussed. Finally, it is observed that the RMS velocity of the gas phase results from combined effects of turbulent dispersion and self-induced fluctuating motions of the bubbles.

Theoretical and Experimental Study on Two-Phase Structure of Planar Mixing Layer

A theoretical and experimental investigation is conducted to study the two-phase turbulent structure in a planar mixing layer with polydispersed drops. Mean and fluctuating velocity components, drop number density, as well as drop size distribution were measured with nonintrusive diagnostics of the two-component phase Doppler particle analyzer. Complete initial conditions required for theoretical calculation were also provided with measurements. Theoretical investigation is made with the Eulerian-Lagrangian formulation. Turbulent dispersion effects are numerically simulated using the Monte Carlo method. The well-defined experimental data have been used to assess the accuracy of the Eulerian-Lagrangian model. The comparisons show that the theoretical predictions, based on the Eulerian-Lagrangian model, yield reasonable agreement with the experimental data.

Experimental and theoretical study on hollow-cone spray

A theoretical and experimental investigation has been conducted to study the two-phase turbulent structure in an isothermal hollow-cone spray. Mean and fluctuating velocity components, drop number density, as well as drop-size distribution were measured with a nonintrusive diagnostic tool, a two-component phase Doppler particle analyzer. Complete initial conditions required for theoretical calculations were also provided with measurements. Theoretical calculations were made with an Eulerian-Lagrangian formulism. Turbulent dispersion effects were numerically simulated using a Monte Carlo method. Turbulence modulation effects were also taken into account in the modeling. The well-defined experimental data were used to assess the accuracy of the resultant Eulerian-Lagrangian model. Comparisons showed that the theoretical predictions, based upon the Eulerian-Lagrangian model, yielded reasonable agreement with the experimental data. The improvements made by inclusion of the selected turbulence modulation model were insignificant in this work.

Effects of turbulent dispersion of atmospheric balance motions of planetary boundary layer

New Reynolds’ mean momentum equations including both turbulent viscosity and dispersion are used to analyze atmospheric balance motions of the planetary boundary layer. It is pointed out that turbulent dispersion with γ 0 will increase depth of Ekman layer, reduce wind velocity in Ekman layer and produce a more satisfactory Ekman spiral lines fit the observed wind hodograph. The wind profile in the surface layer including turbulent dispersion is still logarithmic but the von Karman constantk is replaced byk1 = √ 1 —k/2, the wind increases a little more rapidly with height.