Radiation modeling of microplasma UV lamps for design analysis and optimization.

Microplasma UV lamps have recently emerged as viable excimer-based sources of UV radiation, garnering significant attention during the recent COVID-19 pandemic for their use in disinfection applications because of their ability to emit human-safe far-UVC (200-240 nm) spectrums. An accurate model to simulate the radiation profile of microplasma UV lamps is of paramount importance to develop efficient microplasma lamp-implemented systems. We developed a 3D numerical model of microplasma UV lamps using the ray optics method. The simulation results for lamp irradiance and fluence rate were experimentally validated with standard optical radiometry and actinometry measurements, respectively. To improve the optical efficiency of microplasma lamps, an in-depth analysis of radiation behavior inside the standard commercially available lamp was performed using the geometrical optics method, and several potential scenarios were explored. A 2D modeling of an individual microcavity indicated that the current common lamp design can be significantly improved by preventing radiation loss, and small modifications in optical design can greatly increase the energy performance of the system. Based on the findings of this study, several virtual design concepts were proposed, and their performances were numerically compared with that of the original design of commercial microplasma lamps. The developed model can potentially be integrated with hydrodynamic and kinetic models for the virtual prototyping of complex photoreactors operating with UV microplasma lamps.

Transmission of droplet aerosols in an elevator cabin: Effect of the ventilation mode.

The recent outbreak of COVID-19 has threatened public health. Owing to the relatively sealed environment and poor ventilation in elevator cabins, passengers are at risk of respiratory tract infection. However, the distribution and dispersion of droplet aerosols in elevator cabins remain unclear. This study investigated the transmission of droplet aerosols exhaled by a source patient under three ventilation modes. Droplet aerosols produced by nose breathing and mouth coughing were resolved using computational fluid dynamics (CFD) simulations. We adopted the verified renormalization group (RNG) k-ε turbulence model to simulate the flow field and the Lagrangian method to track the droplet aerosols. In addition, the influence of the ventilation mode on droplet transmission was evaluated. The results showed that droplet aerosols gathered in the elevator cabin and were difficult to discharge under the mixed and displacement ventilation modes with specific initial conditions. The inhalation proportion of droplet aerosols for air curtain was 0.016%, which was significantly lower than that for mixed ventilation (0.049%) and displacement ventilation (0.071%). The air curtain confined the transmission of droplet aerosols with the minimum ratios of inhalation, deposition, and suspension and is thus recommended to reduce the exposure risk.

Did the Tokyo Olympic Games enhance the transmission of COVID-19? An interpretation with machine learning.

BACKGROUND: In the summer of 2021, the Olympic Games were held in Tokyo during the state of emergency due to the spread of COVID-19 pandemic. New daily positive cases (DPC) increased before the Olympic Games, and then decreased a few weeks after the Games. However, several cofactors influencing DPC exist; consequently, careful consideration is needed for future international events during an epidemic. METHODS: The impact of the Olympic Games on new DPC were evaluated in the Tokyo, Osaka, and Aichi Prefectures using a well-trained and -evaluated long short-term memory (LSTM) network. In addition, we proposed a compensation method based on effective reproduction number (ERN) to assess the effect of the national holidays on the DPC. RESULTS: During the spread phase, the estimated DPC with LSTM was 30%-60% lower than that of the observed value, but was consistent with the compensated value of the ERN for the three prefectures. During the decay phase, the estimated DPC was consistent with the observed values. The timing of the decay coincided with achievement of a fully-vaccinated rate of 10%-15% of people aged <65 years. CONCLUSIONS: The up- and downsurge of the pandemic wave observed in July and September are likely attributable to high ERN during national holiday periods and to the vaccination effect, especially for people aged <65 years. The effect of national holidays in Tokyo was rather notable in Aichi and Osaka, which are distant from Tokyo. The effect of the Olympic Games on the spread and decay of the pandemic wave is neither dominant nor negligible due to the shifting of the national holiday dates to coincide with the Olympic Games.

Modeling the Virus Infection at the Population Level.

As pointed out by many researchers in the last few decades, differential equations with fractional (non-integer) order differential operators, in comparison with classical integer order ones, have apparent advantages in modeling. A Caputo fractional order system of ordinary differential equations is introduced to model the virus infection at the population level in this chapter. As well known, there are two main methods to study the dynamics of a model: qualitative analysis and numerical modeling. Here the qualitative analysis, including uniqueness, invariant set, and stability, is first presented with intuitive derivation. Then the famous genetic algorithm is introduced to numerically model the dynamics of virus infection, i.e. to adjust the parameters of the Caputo fractional model such that its solution can properly fit real data and predict future.

Design of a nonlinear model for the propagation of COVID-19 and its efficient nonstandard computational implementation.

In this manuscript, we develop a mathematical model to describe the spreading of an epidemic disease in a human population. The emphasis in this work will be on the study of the propagation of the coronavirus disease (COVID-19). Various epidemiologically relevant assumptions will be imposed upon the problem, and a coupled system of first-order ordinary differential equations will be obtained. The model adopts the form of a nonlinear susceptible-exposed-infected-quarantined-recovered system, and we investigate it both analytically and numerically. Analytically, we obtain the equilibrium points in the presence and absence of the coronavirus. We also calculate the reproduction number and provide conditions that guarantee the local and global asymptotic stability of the equilibria. To that end, various tools from analysis will be employed, including Volterra-type Lyapunov functions, LaSalle's invariance principle and the Routh-Hurwitz criterion. To simulate computationally the dynamics of propagation of the disease, we propose a nonstandard finite-difference scheme to approximate the solutions of the mathematical model. A thorough analysis of the discrete model is provided in this work, including the consistency and the stability analyses, along with the capability of the discrete model to preserve the equilibria of the continuous system. Among other interesting results, our numerical simulations confirm the stability properties of the equilibrium points.