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Knowing the environmental spreading pathway of COVID-19 is crucial for improving safety practices, particularly for health care workers who are more susceptible to exposure. This paper focuses on the possible secondary transmission due to resuspension of virus-laden droplets from common surfaces, which several studies have shown to be possible under external disturbances. Such disturbances could be body motion during walking, running, clothes removal, or airflow in the environment. In this paper, a three-dimensional two-phase model is utilized to study respiratory droplet resuspension dynamics on various surfaces due to sudden agitation. The velocity range and variation during walking, surgical glove removal, and dropping an object are studied experimentally. A parametric study is performed to characterize the effects of droplet size and surface wettability on the minimum initial droplet velocity required for detachment from surfaces. The results are reported as average droplet velocity during the detachment process, total detachment time, and detached droplet volume. The obtained results indicate that respiratory droplets larger than 200 μm can detach from typical surfaces due to normal daily activities. Droplets are partially separated from hydrophilic surfaces with contact angle ≤ 90 ° , while the entire droplet is detached from hydrophobic surfaces with contact angle > --> 90 °. Furthermore, the minimum initial droplet velocity to induce the resuspension depends on the droplet size. Droplet velocity immediately after detachment is a function of droplet size, initial droplet velocity, and surface wettability. Bigger droplets have larger detached volume percentage as well as higher velocity after detachment compared to smaller droplets. Finally, a higher initial velocity is needed to separate droplets from hydrophilic surfaces as compared to hydrophobic surfaces. In accordance with the results, the droplet minimum initial velocity to cause detachment is 2 m s−1, while our experiments show that surface velocity can reach up to 3 m s−1 during normal human activities. We also develop an analytical model to predict the required kinetic energy to detach droplets from different surfaces, which is in good agreement with numerical results. The mechanism of droplet detachment is dictated by a competition between droplet kinetic energy induced by surface motion and surface energy due to droplet–surface interaction as well as droplet–vapor and surface–vapor interactions. We believe that the results of this fundamental study can potentially be used to suggest proper surface wettability and safe motion that reduce respiratory droplet resuspension from various surfaces. [ABSTRACT FROM AUTHOR]

In this study, a new coupled surface shape design (SSD) methodology named direct design method is presented for the solution of problems containing different types of convection heat transfer in which a specific distribution of either heat flux or temperature is given instead of the shape of a boundary. In the proposed method, the governing equation, without using any mathematical transformation for the physical domains, is manipulated so that the grid generation, solving fluid flow, and heat transfer as well as shape updating can all be carried out simultaneously. Five different inverse shape design problems containing different types of convection heat transfer are solved by the proposed method. All the problems are also solved using the ball-spine algorithm (BSA), which is a recently developed de-coupled algorithm, for the sake of comparison. In all problems, the effects of using different under-relaxation parameters are investigated and the capability of both approaches is compared with each other. The results show that the proposed coupled method can solve the problems better than the BSA in the sense that the direct design method converges sooner than the BSA when the same under-relaxation parameter is used for both methods. Also, it is shown that the computational cost of solving a SSD problem using the direct design method is slightly greater than solving an analysis problem. [ABSTRACT FROM AUTHOR]

Inverse shape design in the context of fluid flow problems is commonly referred to the determination of the boundary shape corresponding to a given target surface pressure. Designers naturally turn to this class of problems whenever there are concerns regarding pressure-related phenomena such as cavitation, separation, shock waves, surface loading, etc. Numerical solution is often unavoidable and, therefore, three computational tools, i.e. a grid generator, a flow field solver and a shape updater, are required in an iterative solution procedure. In all existing iterative inverse design methods, the shape updater comes from separate mathematical or physical considerations that are not derived solely from the equations governing the flow field. In this paper, the currently used strategies to solve inverse shape design problems are categorized and reviewed, and then a truly physical-based iterative inverse shape design method is introduced in which the governing equations are not only used in the flow solver, but are also employed to update the shape. To explore the features of the proposed method, it is used to solve a number of shape design problems. The previously developed direct shape design method and a typical iterative solution approach are also explained and used for the solution of the same problems for the purpose of comparison. Computational results reveal that the proposed algorithm has a two to three times faster convergence rate as compared to the iterative algorithm. The convergence rate of the proposed algorithm usually stalls after three or two orders of magnitude reduction of the residual. For the test cases in this study, the direct design method is the fastest and most accurate method as compared to other algorithms. Both in-house developed computer codes and commercial software are used as a field solver to show the general applicability of the proposed method in its current state of development. [ABSTRACT FROM PUBLISHER]

In this paper, natural convection due to two heated cylinders inside a rhombus enclosure with lower temperature with respect to the cylinders is investigated. Here, Cu-water is the working nanofluid. The numerical algorithm is based on an iterative direct immersed boundary method (IBM). The focus of this article is on stability, instability, symmetry as well as asymmetry of nanofluid flow pattern in three different Rayleigh (Ra) numbers, i.e. 104, 105 and 106. The effects of important parameters such as cylinder diameters, nanoparticle volume fraction and distance between two cylinders are analyzed. The results of this study disclose that at both Ra = 104 and 105, nanofluid flow is symmetric and stable, while at Ra = 106 four different flow regimes including steady-symmetric, steady-asymmetric, unsteady-asymmetric with periodic oscillations and unsteady-asymmetric with irregular oscillations are observed. In addition to geometrical parameters, nanoparticle volume fraction has a considerable impact on the flow regime. Furthermore, the possibility of unsteady-asymmetric flow increases considerably by increasing the distance between two cylinders. [ABSTRACT FROM AUTHOR]