Background About 15 million people worldwide were affected by the Sars-Cov-2 infection, which already caused 600,000 deaths. This virus is mainly transmitted through exhalations from the airways of infected persons, so that Heating, Ventilation and Air Conditioning (HVAC) systems might play a role in increasing or reducing the spreading of the infection in indoor environments. Methods We modelled the role of HVAC systems in the diffusion of the contagion through Computational Fluid Dynamics (CFD) simulations of cough at the “Bambino Gesù” Vatican State Children’s Hospital. Both waiting and hospital rooms were modeled as indoor scenarios. A specific Infection-Index (η) parameter was used to estimate the amount of contaminated air inhaled by each person present in the simulated indoor scenarios. The potential role of exhaust air ventilation systems placed above the coughing patient’s mouth was also assessed. Results Our CFD-based simulations of the waiting room show that HVAC air-flow remarkably enhances infected droplets diffusion in the whole indoor environment within 25 seconds from the cough event, despite the observed dilution of saliva particles containing the virus. At the same time also their number is reduced due to removal through the HVAC system or deposition on the surfaces. The proper use of Local Exhaust Ventilation systems (LEV) simulated in the hospital room was associated to a complete reduction of infected droplets spreading from the patient’s mouth in the first 0.5 seconds following the cough event. In the hospital room, the use of LEV system completely reduced the η index computed for the patient hospitalized at the bed next to the spreader, with a decreased possibility of contagion. Conclusions CFD-based simulations for indoor environment can be useful to optimize air conditioning flow and to predict the contagion risk both in hospitals/ambulatories and in other public/private settings.

Lean burn combustion is increasing its popularity in the aeronautical framework due to its potential in reducing drastically pollutant emissions (NOx and soot in particular). Its implementation, however, involves significant issues related to the increased amount of air dedicated to the combustion process, demanding the redesign of injection and cooling systems. A reduced coolant mass flow rate in conjunction with higher compressor discharge temperature negatively affect the cooling potential thus requiring the exploitation of efficient schemes such as effusion cooling. This work describes the experimental and numerical final validation of an aeronautical effusion-cooled lean-burn combustor. Full annular tests were carried out to measure temperature profiles and metal temperature distributions at different operating conditions of the ICAO cycle. Such an outcome was obtained also with an in-house developed CHT methodology (THERM3D). RANS simulations with the Flamelet Generated Manifold combustion model were performed to estimate aerothermal field and heat loads, while the coupling with a thermal conduction solver returns the most updated wall temperature. The heat sink within the perforation is treated with a 0D correlative model that calculates the heat pickup and the temperature rise of coolant. The results highlight an overall good capability of the proposed approach to estimate the metal temperature distribution at different operating conditions. It is also shown how more advanced scale-resolving simulations could significantly improve the prediction of turbulent mixing and heat loads.

Face masking proved essential to reduce transmission of COVID-19 and other respiratory infections in indoor environments, but standards and literature do not provide simple quantitative methods for quantifying air leakage at the face seal. This study reports an original method to quantify outward leakage and how wearing style impacts on leaks and filtration efficiency. The amount of air leakage was evaluated on four medical masks and four barrier face coverings, exploiting a theoretical model and an instrumented dummy head in a range of airflows between 30 and 160 L/min. The fraction of air leaking at the face seal of the medical masks and barrier face coverings ranged from 43% to 95% of exhaled air at 30 L/min and reduced to 10–85% at 160 L/min. Filter breathability was the main driver affecting both leak fraction and total filtration efficiency that varied from 5% to 53% and from 15% to 84% at 30 and 160 L/min, respectively. Minor changes were related to wearing style, supporting indications on the correct mask use. The fraction of air leaking from medical masks and barrier face coverings during exhalation is relevant and varies according to design and wearing style. The use of highly breathable filter materials reduces air leaks and improve total filtration efficiency.

The adoption of lean-burn technology in modern aero-engines influences the already critical aerothermal conditions at turbine entry, where the absence of dilution holes preserves the swirl component generated by burners and prevents any control on pattern factor. The associated uncertainty and lack of confidence entail the application of wide safety margins in turbine cooling design, with a detrimental effect on engine efficiency. Computational fluid dynamics (CFD) can provide a deeper understanding of the physical phenomena involved in combustor–turbine interaction, especially with hybrid Reynolds-averaged Navier–Stokes (RANS) large eddy simulation (LES) models, such as scale adaptive simulation (SAS), which are proving to overcome the well-known limitations of the RANS approach and be a viable approach to capture the complex flow physics. This paper describes the numerical investigation on a test rig representative of a lean-burn, effusion cooled, annular combustor developed in the EU Project Full Aerothermal Combustor-Turbine interactiOns Research (FACTOR) with the aim of studying combustor–turbine interaction. Results obtained with RANS and SAS were critically compared to experimental data and analyzed to better understand the flow physics, as well as to assess the improvements related to the use of hybrid RANS-LES models. Significant discrepancies are highlighted for RANS in predicting the recirculating region, which has slight influence on the velocity field at the combustor outlet, but affects dramatically mixing and the resulting temperature distribution. The accuracy of the results achieved suggests the exploitation of SAS model with a view to the future inclusion of the nozzle guide vanes in the test rig.

Layered double hydroxides (LDHs) have been combined with graphene and/or carbon nanotubes to prepare new composite materials with fascinating electrochemical features. For the first time, this work describes the development of an electrosynthesis protocol that allows the deposition of thin films of a Ni/Al LDH on glassy carbon electrodes previously modified with carbon nanomaterials. Three different approaches (potentiostatic, galvanostatic and potentiodynamic) were investigated in order to identify the best procedure. In all cases the potentiodynamic synthesis exhibits better reproducibility than the potentiostatic one which is the most used in literature. The reliability of the synthesis protocol was evaluated by performing the LDH electrodeposition using glassy carbon electrodes modified with multiwalled carbon nanotubes and/or electrochemically reduced graphene oxide arranged in five configurations. XRD and SEM analysis confirmed the LDH formation. Cyclic voltammetry shows the graphene presence ensured a large electrochemically active area with values 3 times higher than the one observed for an LDH deposited on a bare glassy carbon.Moreover, impedance electrochemical spectroscopy highlights that carbon nanomaterials play a key role in reducing the charge transfer resistance. In fact, it decreases from 2800 KΩ recorded for LDH deposited on bare glassy carbon to about 600 Ω for the best composite material. The materials were tested for glucose electrooxidation which was exploited for the fabrication of a sensor with high sensitivity (2.6 A M -1 cm -2 for the best device) and low limit of detection (0.6 µM for the best device).