After the Spanish flu pandemic, it was apparent that airborne transmission was crucial to spreading virus contagion, and research responded by producing several fundamental works like the experiments of Duguid [J. P. Duguid, J. Hyg. 44, 6 (1946)] and the model of Wells [W. F. Wells, Am. J. Hyg. 20, 611–618 (1934)]. These seminal works have been pillars of past and current guidelines published by health organizations. However, in about one century, understanding of turbulent aerosol transport by jets and plumes has enormously progressed, and it is now time to use this body of developed knowledge. In this work, we use detailed experiments and accurate computationally intensive numerical simulations of droplet-laden turbulent puffs emitted during sneezes in a wide range of environmental conditions. We consider the same emission—number of drops, drop size distribution, and initial velocity—and we change environmental parameters such as temperature and humidity, and we observe strong variation in droplets’ evaporation or condensation in accordance with their local temperature and humidity microenvironment. We assume that 3% of the initial droplet volume is made of nonvolatile matter. Our systematic analysis confirms that droplets’ lifetime is always about one order of magnitude larger compared to previous predictions, in some cases up to 200 times. Finally, we have been able to produce original virus exposure maps, which can be a useful instrument for health scientists and practitioners to calibrate new guidelines to prevent short-range airborne disease transmission.

Pilot‐ignited high‐pressure direct‐injection (HPDI) natural gas engines have drawn much attention since being proposed, as these engines can maintain high performance and lead to clean combustion compared with conventional diesel engines. This prospective concept is not only used in vehicle engines but also used in large‐scale marine engines. In this study, the effects of injection strategies of dual fuels on combustion characteristics and emissions were investigated using the computational fluid dynamics (CFD) code CONVERGE coupled with a reduced n‐heptane/methane mechanism. The results showed that the effects of absolute injection timing (AIT) on the combustion characteristics and emissions are similar to those of traditional diesel engines. As the AIT varies from advanced by 4°CA to retarded by 4°CA, the peak values of the in‐cylinder pressure and temperature decrease gradually. However, a conventional trade‐off between NOx and soot/CO/HC/ISFC emissions can also be observed as the AIT is retarded. In contrast, relative injection timing (RIT) has more complicated impacts on the combustion and emissions characteristics. The in‐cylinder temperature distribution and concentration stratification change as the gas jet initially interacts with the pilot flame. The effects of the gas injection timing on the combustion characteristics and indicated specific fuel consumption are also similar to those of the AIT, but the emissions are quite different. The pilot injection timing shows minimal influence on the main combustion process. Better performance can be obtained with partially premixed combustion with a slightly late injection timing compared with that of the original (ORG) base case.

In a wide range of applications, the estimate of droplet evaporation time is based on the classical D 2 -law, which, assuming a fast mixing and fixed environmental properties, states that the droplet surface decreases linearly with time at a determined rate. However, in many cases the predicted evaporation rate is overestimated. In this Letter, we propose a revision of the D 2 -law capable of accurately determining droplet evaporation rate in dilute conditions by a proper estimate of the asymptotic droplet properties. Besides a discussion of the main assumptions, we tested the proposed model against data from direct numerical simulations finding an excellent agreement for predicted droplet evaporation time in dilute turbulent jet-sprays.

The outbreak of the COVID-19 pandemic highlighted the importance of accurately modelling the pathogen transmission via droplets and aerosols emitted while speaking, coughing and sneezing. In this work, we present an effective model for assessing the direct contagion risk associated with these pathogen-laden droplets. In particular, using the most recent studies on multi-phase flow physics, we develop an effective yet simple framework capable of predicting the infection risk associated with different respiratory activities in different ambient conditions. We start by describing the mathematical framework and benchmarking the model predictions against well-assessed literature results. Then, we provide a systematic assessment of the effects of physical distancing and face coverings on the direct infection risk. The present results indicate that the risk of infection is vastly impacted by the ambient conditions and the type of respiratory activity, suggesting the non-existence of a universal safe distance. Meanwhile, wearing face masks provides excellent protection, effectively limiting the transmission of pathogens even at short physical distances, i.e. 1 m.

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