Turbulent Dispersion Simulation of Radioactive Aerosol Applied to the Infrastructure of the NPP-2006 Industrial Site

The goal of this work is to simulate the processes of transport and deposition of aerosol particles in a turbulent flow, taking into account the infrastructure of the industrial site of the NPP. The developed model for calculating the dynamics of the spread of the pollutant emissions in emergency situations is presented, the limits of applicability of turbulence models are determined and the main mechanical and thermal sources of turbulence in the NPP infrastructure are analyzed. The mechanisms of radioactive substances deposition for emergency situations have been assessed taking into account turbulent effects. According to the results of the numerical modeling, the zones of predominant deposition of radioactive aerosols on the characteristic surfaces of the NPP infrastructure have been determined, which is the basis for emergency actions planning and assessment of the personnel doses.

Beyond well-mixed: a simple probabilistic model of airborne disease transmission in indoor spaces

We develop a simple model for assessing risk of airborne disease transmission that accounts for non-uniform mixing in indoor spaces and is compatible with existing epidemiological models. A database containing 174 high-resolution simulations of airflow in classrooms, lecture halls, and buses is generated and used to quantify the spatial distribution of expiratory droplet nuclei for a wide range of ventilation rates, exposure times, and room configurations. Imperfect mixing due to obstructions, buoyancy, and turbulent dispersion results in concentration fields with significant variance. The spatial non-uniformity is found to be accurately described by a shifted lognormal distribution. A well-mixed mass balance model is used to predict the mean, and the standard deviation is parameterized based on ventilation rate and room geometry. When employed in a dose-response function risk model, infection probability can be estimated considering spatial heterogeneity that contributes to both short- and long-range transmission.

Assessing representativity of NH₃ measurements influenced by boundary-layer dynamics and turbulent dispersion of a nearby emission source

This study presents a fine scale simulation approach to assess the representativity of ammonia (NH3) measurements in proximity of an emission source. Close proximity to emission sources (< 5 km) can introduce a bias in regionally representative measurements of the NH3 molar fraction and flux. Measurement sites should therefore be located a significant distance from emission sources, but such requirements are poorly defined and can be difficult to meet in densely agricultural regions. This study presents a consistent criterium to assess the regional representativity of NH3 measurements in proximity of an emission source, calculating variables that quantify the NH3 plume dispersion using a series of numerical experiments at a fine resolution (20 m). Our fine scale simulation framework with explicitly resolved turbulence enables us to distinguish between the background NH3 and the emission plume, including realistic representations of NH3 deposition and chemical gas-aerosol transformations. We introduce the concept of blending-distance, based on the calculation of turbulent fluctuations, to systematically analyze the impact of the emission plume on simulated measurements, relative to this background NH3. This sensitivity analysis includes systematic experiments varying meteorological factors, emission/deposition and NH3 dependences. Considering these sensitivities, we find that NH3 measurements should be located at a minimum distance of 0.5–2.5 km and 1–3.5 km from an emission source, for NH3 molar fraction and flux measurements respectively. The simulation framework presented here can easily be adapted to local conditions and paves the way for future ammonia research at high spatio-temporal resolution.

Passive Front Propagation in Intense Turbulence: Early Transient and Late Statistically Stationary Stages of the Front Area Evolution

The influence of statistically stationary, homogeneous isotropic turbulence (i) on the mean area of a passive front propagating in a constant-density fluid and, hence, (ii) on the mean fluid consumption velocity u¯T is explored, particularly in the case of an asymptotically high turbulent Reynolds number, and an asymptotically high ratio of the Kolmogorov velocity to a constant speed u0 of the front. First, a short early transient stage is analyzed by assuming that the front remains close to a material surface that coincides with the front at the initial instant. Therefore, similarly to a material surface, the front area grows exponentially with time. This stage, whose duration is much less than an integral time scale of the turbulent flow, is argued to come to an end once the volume of fluid consumed by the front is equal to the volume embraced due to the turbulent dispersion of the front. The mean fluid consumption velocity averaged over this stage is shown to be proportional to the rms turbulent velocity u′. Second, a late statistically stationary regime of the front evolution is studied. A new length scale characterizing the smallest wrinkles of the front surface is introduced. Since this length scale is smaller than the Kolmogorov length scale ηK under conditions of the present study, the front is hypothesized to be a bifractal with two different fractal dimensions for wrinkles larger and smaller than ηK. Finally, a simple scaling of u¯T∝u′ is obtained for this late stage as well.

Numerical Modelling of Dispersed Water in Oil Flows Using Eulerian-Eulerian Approach and Population Balance Model

Formation of a dispersed oil—water flow pattern is a common occurrence in flow lines and pipelines. The capability of predicting the size of droplets, as well as the distribution of dispersed phase volume fraction is of utmost importance for proper design of such systems. The present study aims at modelling dispersed water in oil flows in a horizontal pipe by employing a multi-fluid Eulerian approach along with the population balance model. To this end, momentum and continuity equations are solved for oil and water phases, and the coupling between the phases is achieved by considering the drag, lift, turbulent dispersion, and virtual mass forces. Turbulent effects are modelled by employing the standard k-ε model. Furthermore, a population balance model, based on the method of class, along with the breakup and coalescence kernels is adopted for modelling the droplet size distribution. The obtained numerical results are compared to the experimental data in literature for either the in situ Sauter mean diameter or water volume fraction. A comparison among the obtained numerical results and the published experimental data shows a reasonable agreement.

Numerical Modeling of Face Shield Protection against a Sneeze

The protection provided by wearing masks has been a guideline worldwide to prevent the risk of COVID-19 infection. The current work presents an investigation that analyzes the effectiveness of face shields as personal protective equipment. To that end, a multiphase computational fluid dynamic study based on Eulerian–Lagrangian techniques was defined to simulate the spread of the droplets produced by a sneeze. Different scenarios were evaluated where the relative humidity, ambient temperature, evaporation, mass transfer, break up, and turbulent dispersion were taken into account. The saliva that the human body generates was modeled as a saline solution of 8.8 g per 100 mL. In addition, the influence of the wind speed was studied with a soft breeze of 7 km/h and a moderate wind of 14 km/h. The results indicate that the face shield does not provide accurate protection, because only the person who is sneezed on is protected. Moreover, with a wind of 14 km/h, none of the droplets exhaled into the environment hit the face shield, instead, they were deposited onto the neck and face of the wearer. In the presence of an airflow, the droplets exhaled into the environment exceeded the safe distance marked by the WHO. Relative humidity and ambient temperature play an important role in the lifetime of the droplets.

Statistical Model of Turbulent Dispersion Recapitulated

A comprehensive summary and update is given of Brouwers’ statistical model that was developed during the previous decade. The presented recapitulated model is valid for general inhomogeneous anisotropic velocity statistics that are typical of turbulence. It succeeds and improves the semiempirical and heuristic models developed during the previous century. The model is based on a Langevin and diffusion equation of which the derivation involves (i) the application of general principles of physics and stochastic theory; (ii) the application of the theory of turbulence at large Reynolds numbers, including the Lagrangian versions of the Kolmogorov limits; and (iii) the systematic expansion in powers of the inverse of the universal Lagrangian Kolmogorov constant C0, C0 about 6. The model is unique in the collected Langevin and diffusion models of physics and chemistry. Presented results include generally applicable expressions for turbulent diffusion coefficients that can be directly implemented in numerical codes of computational fluid mechanics used in environmental and industrial engineering praxis. This facilitates the more accurate and reliable prediction of the distribution of the mean concentration of passive or almost passive admixture such as smoke, aerosols, bacteria, and viruses in turbulent flow, which are all issues of great societal interest.

Numerical Modeling of the Spread of Cough Saliva Droplets in a Calm Confined Space

The coronavirus disease 2019 (COVID-19) outbreak has altered the lives of everyone on a global scale due to its high transmission rate. In the current work, the droplet dispersion and evaporation originated by a cough at different velocities is studied. A multiphase computational fluid dynamic model based on fully coupled Eulerian–Lagrangian techniques was used. The evaporation, breakup, mass transfer, phase change, and turbulent dispersion forces of droplets were taken into account. A computational domain imitating an elevator that with two individuals inside was modeled. The results showed that all droplets smaller than 150 μm evaporate before 10 s at different heights. Smaller droplets of <30 µm evaporate quickly, and their trajectories are governed by Brownian movements. Instead, the trajectories of medium-sized droplets (30–80 µm) are under the influence of inertial forces, while bigger droplets move according to inertial and gravitational forces. Smaller droplets are located in the top positions, while larger (i.e., heaviest) droplets are located at the bottom.