Search Results (60)

Various nature-based solutions (NbS)—such as constructed wetlands, drainage ditches, and vegetated buffer strips—have recently demonstrated strong potential for mitigating pollutant transport in open channels and river systems. Numerical modeling is a widely adopted and effective approach for assessing the performance of these interventions. This study presents the first development of a two-dimensional (2D) meshless advection–diffusion model based on an Eulerian smoothed particle hydrodynamics (SPH) framework, specifically designed to simulate passive pollutant transport in open channel flows. The proposed model marks a pioneering application of the ESPH technique to environmental pollutant transport problems. It couples the 2D depth-averaged shallow water equations with an advection–diffusion equation to represent both fluid motion and pollutant concentration dynamics. A uniform particle arrangement ensures that each fluid particle interacts symmetrically with eight neighboring particles for flux computation. To represent the pollutant transport process, the dispersion coefficient is defined as the sum of molecular and turbulent diffusion components. The turbulent diffusion coefficient is calculated using a prescribed turbulent Schmidt number and the eddy viscosity obtained from a Smagorinsky-type mixing-length turbulence model. Three analytical case studies, including one-dimensional transcritical open channel flow, 2D isotropic and anisotropic diffusion in still water, and advection–diffusion in a 2D uniform flow, are employed to verify the model’s accuracy and convergence. The model demonstrates first-order convergence, with relative root mean square errors (RRMSEs) of approximately 0.2% for water depth and velocity, and 0.1–0.5% for concentration. Additionally, the model is applied to a laboratory experiment involving 2D pollutant dispersion in a 90° junction channel. The simulated results show good agreement with measured velocity and concentration distributions. These findings indicate that the developed model is a reliable and effective tool for evaluating the performance of NbS in mitigating pollutant transport in open channels and river systems. Full article

Infectious diseases can spread through virus-laden respiratory droplets exhaled into the air. Ventilation systems are crucial in indoor settings as they can dilute or eliminate these droplets, underscoring the importance of understanding their efficacy in the management of indoor infections. Within the field of fluid dynamics methods, the dispersed droplets may be approached through either a Lagrangian framework or an Eulerian framework. In this study, various Eulerian methodologies are systematically compared against the Eulerian–Lagrangian (E-L) approach across three different scenarios: the pseudo-single-phase model (PSPM) for assessing the transport of gaseous pollutants in an office with displacement ventilation (DV), stratum ventilation (SV), and mixing ventilation (MV); the two-fluid model (TFM) for evaluating the transport of non-evaporating particles within an office with DV and MV; and the two-fluid model-population balance equation (TFM-PBE) approach for analyzing the transport of evaporating droplets in a ward with MV. The Eulerian and Lagrangian approaches present similar agreement with the experimental data, indicating that the two approaches are comparable in accuracy. The computational cost of the E-L approach is closely related to the number of tracked droplets; therefore, the Eulerian approach is recommended when the number of droplets required by the simulation is large. Finally, the performances of DV, SV, and MV are presented and discussed. DV creates a stratified environment due to buoyant flows, which transport respiratory droplets upward. MV provides a well-mixed environment, resulting in a uniform dispersion of droplets. SV supplies fresh air directly to the breathing zone, thereby effectively reducing infection risk. Consequently, DV and SV are preferred to reduce indoor infection. Full article

CAMx-LPiG (Comprehensive Air Quality Model with Extensions—Linear Plume in Grid) is an online hybrid model based on the Chemistry and Transport Model (CTM) CAMx, which includes a sub-grid scale module to simulate the dispersion of linear road traffic emissions called LPiG. LPiG is a plume in grid module specifically developed by extending the capabilities of the Lagrangian puff sub-grid model available in CAMx. The online integration of the local scale model within the Eulerian CTM allows for a multiscale simulation of air quality from the regional scale to the urban scale, preserving a coherent description of the chemical state of the atmosphere at all spatial scales and avoiding any double counting of the emissions simulated by the sub-grid module. In this work, the model is presented and evaluated against measured NO₂ concentrations for the city of Milan for the month of January 2017. The model can introduce road traffic-induced gradient in NO₂ concentration at sub-grid resolution. Moreover, CAMx-LPiG has been shown to reduce bias compared to CAMx stand-alone simulations. Full article

In this work, a statistical method is applied to a multiphase CFD simulation of concrete mixing performed in a truck mixer. The numerical model is based on an Eulerian–Eulerian approach in a transient regime. The aggregate materials are simulated as dispersed solid particles of various diameters, while the cement paste is simulated as a non-Newtonian continuous fluid. The first ten drum revolutions are analyzed from the condition of the completely segregated materials. The cell mixing index, defined by a statistical method in terms of mean, variance, and density probability function, is applied to the analysis of the simulation results. The statistical variables are implemented using the fluid dynamics code in the post-processing result analyses. The method predicts the distribution efficiency of the materials within a truck mixer as a function of its internal geometry, rotation speed, and mixture composition. As the number of revolutions increases, the distribution qualitatively improves, as shown by the motion fields, velocities, and vortices of the various materials, quantified through the calculation of the mixing index. The illustrated method can be used to predictively calculate the distribution effectiveness of new truck mixer designs before prototyping them and can be applied to other types of mixers. Furthermore, this study can be applied to liquid–solid mixing processes analyzed via the Eulerian multiphase numerical approach. Full article

In this paper, droplet vaporization dynamics in a heated bubbling fluidized bed was studied. A volatile hydrocarbon liquid jet comprising acetone was injected into a hot bubbling fluidized bed of Geldart A-type glass ballotini particles heated at 150 °C, well above the saturation temperature of acetone (56 °C). Intense interactions were observed among the evaporating droplets and hot particles during contact with the re-suspension of particles due to a release of vapour. A non-intrusive schlieren imaging method was used to track the hot air and vapour mixture plume in the freeboard region of the bed and the acetone vapour fraction therein was mapped. The jet vaporization dynamics in the bubbling fluidized bed was modelled in a Eulerian–Lagrangian CFD (computational fluid dynamics) modelling framework involving heat and mass transfer sub models. The CFD model indicated a dispersion of the vapour plume from the evaporating droplets which was qualitatively compared with the schlieren images. Further, the CFD simulation predicted a significant reduction (~60 °C) in the local bed temperature at the point of the jet injection, which was indirectly confirmed in an experiment by the presence of particle agglomerates. Full article

A computational fluid dynamics study of the horizontal oil–water flow was performed using the Eulerian–Eulerian and mixture multiphase models in conjunction with the realizable k–ε turbulence model for the characterization of flow patterns. The experimental tests were carried out using water and mineral oil with a density of 880 kg/m³ and a viscosity of 180 cP, varying the superficial velocities of both fluids in ranges of 0.1–1.2 m/s and 0.1–0.5 m/s, respectively. The numerical model was defined under the same initial and boundary conditions as in the experiment. Moreover, the model is defined such that entering the fluids in a mixed state, the stratified pattern could form adequately with the two multiphase models. Although the Eulerian–Eulerian model, together with the geometric reconstruction scheme, allowed us to visualize the three-dimensional dispersed patterns in a very similar way to the experimental results, the mixture model did not exhibit such similarity, especially in the oil-in-water dispersions. Additionally, the Eulerian–Eulerian model was able to predict the experimental holdup values with an average error of 15.2%. Full article

A first-order linear and numerically non-diffusive Eulerian transport algorithm, minVAR, was recently developed for preservation of correlations between interrelated tracers during advective transport. The present study extends this work by: (1) providing further investigation of several interesting geometric constructions found in contours of constant minVAR, short for minimum variance, through extension to three coordinate dimensions. These contours capture point-by-point representations of thousands of individual atmospheric aerosol and/or cloud particles as they evolve and are rendered on Eulerian grids at a level of sub-grid resolution limited only by numerical precision; and (2) exploration of geometric similarities between the Arakawa C-grid, used to obtain interpolated values of the wind field at grid scale and minVAR. In particular, we consider interpolation of the u and v horizontal components of wind velocity from grid to sub-grid scales. The last results are motivated by recent applications of the Weather Research and Forecasting (WRF) model applied in the coastal Houston region, where the recent TRacking Aerosol Convection Interactions ExpeRiment (TRACER) field campaign was organized. A unique and fully consistent mapping is obtained between particles moving along meteorological wind trajectories and the non-diffusive, non-dispersive representation of such trajectories on an Eulerian grid. Full article

The primary focus of this article is to derive a solution to obtain the asymptotic turbulent dispersion parameter provided by the spectral Taylor statistical diffusion model. Unlike previous articles, which employed the Dirac delta function to solve the eddy diffusivity formula, in this study, we used the Dirac delta function properties to obtain directly the asymptotic turbulent dispersion parameter from the particles’ spatial dispersion variance described in terms of the Eulerian turbulence spectrum and of the scale factor defined formally as the ratio between Lagrangian and Eulerian timescales. From the Kolmogorov 1941 theory, a detailed derivation for this scale factor is presented. Furthermore, using high mean wind speed data generated by local topographic features, a magnitude for the Kolmogorov constant for the neutral atmospheric boundary layer is evaluated. Thus, this magnitude when added to other values obtained from the selected studies found in the literature provides an average value for the Kolmogorov constant that agrees with large eddy simulation data results. Therefore, this average value allows to obtain a more reliable description of this scale factor. Finally, employing analytical formulations for the observed neutral turbulent spectra and for the velocity variances as well as turbulent statistical quantities measured in a surface neutral atmospheric boundary layer, a vertical dispersion parameter is derived. This vertical dispersion parameter when utilized in a simple Gaussian diffusion model is able to reproduce well contaminant observed concentrations.The Gaussian simulated concentrations also compare well with those simulated by a Lagrangian stochastic particle dispersion model that uses observed vertical spectral peak frequency values at distinct levels of the neutral surface boundary layer. Therefore, the present study shows that the observational determination of a single vertical spectral peak frequency is sufficient to obtain a realistic vertical dispersion parameter characterizing the dispersive effect in the turbulent environment of the surface neutral atmospheric boundary layer. Full article

This study presents an improved comprehensive atomization model for a pressure swirl atomizer. The model integrates internal flow predictions, linear instability analysis of a swirling annular liquid sheet, primary atomization sub-model, and droplet velocity sub-model. Measurement data combined with the inviscid theory model predict the internal flow, providing liquid sheet velocity and thickness at the atomizer outlet. The dispersion relation of surface disturbances is obtained through linear instability analysis. A primary breakup predictive model for particle size distribution is constructed based on the wavelength and growth rate within the full unstable wavenumber range of the dispersion relation. Assuming uniform circumferential distribution and a normal distribution of spray angles, the droplet velocity is assigned according to the liquid sheet velocity. The model is implemented into Eulerian–Lagrangian simulations as initial conditions for discrete phase droplets to simulate the spray field. Results show the model can accurately predict the Sauter mean diameter with an error of less than 6% and effectively predicts the spray structure and spray cone angle. The dependency of the model on its parameters is also studied, determining that the values of the ligament constant and dispersion angle have an obvious impact on the prediction of Sauter mean diameter and spray structure. Full article

Fluidization bed reactor is an attractive method to synthesize and process quantities of functional nanoparticles, due to the large gas–solid contact area and its potential scalability. Nanoparticles fluidize not individually but as a form of porous agglomerates with a typical porosity above 90%. The porous structure has a significant effect on the hydrodynamic behavior of a single nanoparticle agglomerate, but its influence on the flow behavior of nanoparticle agglomerates in a fluidized bed is currently unclear. In the present study, a drag model was developed to consider the porous structure effects of nanoparticle agglomerates by incorporating porous-structure-based drag laws in the Eulerian–Eulerian two-fluid model. Numerical simulations were performed from particulate to bubbling fluidization state to evaluate the applicability of porous-structure-based drag laws. Results obtained for the minimum fluidization and bubbling velocities, bed expansion ratio, and agglomerate dispersion coefficient show that, compared with the drag law of solid sphere, the porous-structure-based drag laws, especially the drag law of fractal porous spheres, provide a closer fit to the experimental data. This indicates that the pore structures have a great impact on gas–solid flow behavior of nanoparticle agglomerates, and the porous-structure-based drag laws are more suitable for describing flows in nanoparticle agglomerate fluidized beds. Full article

A two-way coupled model between polydisperse particle phases with compressible gases and a density-based coupling implicit solution method, combining the third-order MUSCL with QUICK spatial discretization scheme and the second-order temporal discretization scheme, are constructed based on the discrete-phase model (DPM) and the stochastic wander model (DRWM) in the Eulerian–Lagrangian framework in conjunction with a unitary particulate source (PSIC) approach and the SST k-ω turbulence model. The accuracy of the numerical prediction method is verified using previous supersonic nozzle gas-solid two-phase flow experiments. Numerical simulation of a two-phase jet of dry powder extinguishing agent gas with pilot-type supersonic nozzle was performed to analyze the influence of geometrical parameters, such as the length ratio r_L and the area ratio r_A of the main nozzle on the two-phase flow field, as well as on the jet performance indexes, such as the particle mean velocity v_p,a, velocity inhomogeneity Φ_vp, particle dispersion Ψ_p, particle mean acceleration a_p,a, etc. By analyzing the parameters, we indicate the requirements for the combination of jet performance metrics for different flame types such as penetrating, spreading, and dispersing. Full article

The exponential increase in greenhouse gas emissions necessitates urgent measures to mitigate climate change impacts. Carbon capture and storage (CCS) has emerged as a promising solution, capturing CO₂ from industrial processes and storing it underground. However, CCS implementation poses risks that demand sophisticated modeling. This review focuses on the numerical modeling of CO₂ plume dispersion from reservoir leaks during offshore CCS projects, including near- and far-field modeling and the comparison between Lagrangian and Eulerian modeling in particular. Near-field modeling examines CO₂ behavior in jet plume, considering depth-related changes. Far-field modeling, employing Eulerian and Lagrangian methods, evaluates dispersion in marine environments. Case studies illustrate the complexity and uniqueness of CO₂ dispersion events. The Lagrangian approach emphasizes gas bubble tracking, while the Eulerian approach employs fixed grid systems for detailed hydrodynamic modeling. Both approaches contribute valuable insights, with Eulerian models excelling in site-specific complexities and Lagrangian models offering computational efficiency. A hybrid approach may offer a comprehensive understanding of CO₂ dispersion. Full article

Recent advancements in particle dispersion modeling have significantly enhanced our understanding and capabilities in predicting and analyzing the behavior of particulate matter in various environments. However, this field still confronts several research gaps and challenges that span across scientific inquiry and technological applications. This paper reviews the current state of particle dispersion modeling, focusing on various models such as Lagrangian, Eulerian, Gaussian, and Box models, each with unique strengths and limitations. It highlights the importance of accurately simulating multi-phase interactions, addressing computational intensity for practical applications, and considering environmental and public health implications. Furthermore, the integration of emerging technologies like machine learning (ML) and artificial intelligence (AI) presents promising avenues for future advancements. These technologies could potentially enhance model accuracy, reduce computational demands, and enable handling complex, multi-variable scenarios. The paper also emphasizes the need for real-time monitoring and predictive capabilities in particle dispersion models, which are crucial for environmental monitoring, industrial safety, and public health preparedness. Full article

Offshore Wind Farm (OWF) foundations are considered to have a potential impact on the larval dispersion of benthic species. This study focused on OWFs’ impacts on larval dispersion, considering factors such as the foundation type, flow velocity, flow direction, and release type using numerical modelling. At the scale of monopile and gravity-based foundations, a combination of two numerical models was used: the Eulerian model (OpenFOAM), solving the 3D Navier–Stokes equations for computing the hydrodynamics, and the Lagrangian model (Ichthyop), solving the advection–diffusion equation for the larval dispersion simulations. The validation model tests were evaluated with experimental data as a first step of the study. Accurate results were achieved, yielding a Turbulent Kinetic Energy (TKE) Root-Mean-Squared Error (RMSE) in the range of 6.82–8.27 $\times {10}^{-5}\mathrm{kg}/\mathrm{m}·{\mathrm{s}}^2$ within the refined mesh, with a coefficient of determination ($R^2$) approaching unity. For the second phase, more-realistic simulations were modelled. Those simulations demonstrated turbulent wakes downstream of the foundations and horseshoe vortex formations near the bottom. A larval dispersion was simulated using passive particles’ motion. Vertical flumes in the wake with particles experiencing both upward and downward motions, impacting the fall velocities of the particles, were observed. The influence of gravity-based foundations might lead to a stepping-stone effect with a retention time of up to 9 min, potentially allowing the settlement of competent larvae. In a similar geometry with an angular spring tide velocity, 0.4% of particles were trapped. Full article

The self-purification capacity of semi-closed bays is closely related to the exchange process of open sea water. In recent years, with the enhancement of human development activities, environmental problems such as eutrophication, weak hydrodynamics, and poor water exchange capacity have appeared in the bays. In this paper, the water exchange time and flow field in Jiaozhou Bay (JZB) were investigated using the environmental fluid dynamics code with a coupled dye module. Specifically, Jiaozhou Bay was divided into seven zones to explore the effect mechanism of a monsoon on the water exchange process. A detailed analysis was performed on the current water exchange status in the highly polluted northeastern region of the bay and its influence on the surrounding areas. Based on the definition of the average residence time and considering the effect of the tracer release moment, the distribution of the water exchange time in the bay under three circumstances was obtained. Results showed that the timing of the tracer release exerted minimal influence on the average residence time. The water exchange process was influenced by a combination of astronomical and meteorological factors. The overall exchange capacity of the bay was strongest under the impact of a winter monsoon and tides, followed by a summer monsoon and tides, and the weakest exchange occurred under the influence of tides alone. Moreover, both summer and winter monsoons greatly facilitated water exchange in the heavily polluted northeastern region. However, pollutants from this region had a significant impact on surrounding areas during a summer monsoon. Changes in the structure and intensity of residual flow fields were the primary causes of exchange rate discrepancies. Full article