A feasible route for the design and manufacture of customised respiratory protection through digital facial capture

The World Health Organisation has called for a 40% increase in personal protective equipment manufacturing worldwide, recognising that frontline workers need effective protection during the COVID-19 pandemic. Current devices suffer from high fit-failure rates leaving significant proportions of users exposed to risk of viral infection. Driven by non-contact, portable, and widely available 3D scanning technologies, a workflow is presented whereby a user’s face is rapidly categorised using relevant facial parameters. Device design is then directed down either a semi-customised or fully-customised route. Semi-customised designs use the extracted eye-to-chin distance to categorise users in to pre-determined size brackets established via a cohort of 200 participants encompassing 87.5% of the cohort. The user’s nasal profile is approximated to a Gaussian curve to further refine the selection in to one of three subsets. Flexible silicone provides the facial interface accommodating minor mismatches between true nasal profile and the approximation, maintaining a good seal in this challenging region. Critically, users with outlying facial parameters are flagged for the fully-customised route whereby the silicone interface is mapped to 3D scan data. These two approaches allow for large scale manufacture of a limited number of design variations, currently nine through the semi-customised approach, whilst ensuring effective device fit. Furthermore, labour-intensive fully-customised designs are targeted as those users who will most greatly benefit. By encompassing both approaches, the presented workflow balances manufacturing scale-up feasibility with the diverse range of users to provide well-fitting devices as widely as possible. Novel flow visualisation on a model face is presented alongside qualitative fit-testing of prototype devices to support the workflow methodology.

Aerosol Release, Distribution and Prevention during Aerosol Therapy: A Simulated Model for Infection Control.

Background: Aerosol therapy is used to deliver medical therapeutics directly to the airways to treat respiratory illnesses. A potential side-effect of this form of treatment is the release of fugitive aerosols into the environment and the exposure of caregivers, other patients, and bystanders to potential viral infections. The aim of this work was to use both flow visualisation and aerosol particle characterisation techniques to study the dispersion, concentrations and size distributions of fugitive aerosols emitted during aerosol therapy delivered via a standard mouthpiece.Methods: Aerosol therapy was delivered via a nebuliser, aerosol holding chamber and mouthpiece to a spontaneously breathing adult patient model that could mimic the release of patient-derived bioaerosol. A combination of laser and Schlieren imaging were used to non-invasively visualise the release and dispersion of fugitive aerosol particles. Time varying aerosol particle number concentrations and size distributions were measured with optical particle sizers at clinically relevant positions. Results: The addition of a capture filter to the expiratory port of the mouthpiece significantly reduced the release and spread of fugitive aerosols. Capture filters were effective in curtailing the release of fugitive aerosols of respirable size, ≤ 5 µm in diameter (P ≤ 0.05). Conclusions: The findings suggest that, where possible, capture filters should be added to the expiratory ports of all aerosol therapy devices to prevent airborne transmission of respiratory illnesses and create safer conditions for healthcare workers and patients.

Wind Flow Characterisation over a PV Module through URANS Simulations and Wind Tunnel Optical Flow Methods

Despite their simplicity, photovoltaic (PV) modules are often arranged in structures that can be affected by severe and complex wind loads: in this context, the wind flow and the dynamic excitation induced by vortex shedding can introduce unexpected aeroelastic responses. This work introduces a novel wind tunnel application of experimental techniques to address this issue by the use of flow visualisation and video postprocessing, through the optical flow algorithm. Numerical simulations based on unsteady Reynolds-averaged Navier–Stokes (RANS) models are performed and compared against the experimental wind tunnel tests on a PV panel that was also instrumented with pressure taps. A setup with a 65∘ tilt angle was examined because, based on preliminary analyses, it was considered interesting for the free flow–wake transition associated with the dynamic response of the PV panel. The comparison of the experimental and numerical average wind fields supported that the proposed optical flow method was appropriate for characterising the wake of the panel, because there was enough seeding to perform the video postprocessing. Experiments and numerical predictions were compared as regards the average pressure distribution on the panel surfaces, and the average percentage was in the error of 7%; this supports that the URANS method was capable of reproducing the average behaviour of the panel, as well as for the selected configuration, which is particularly challenging. Furthermore, the simulated and measured power spectral densities of the wind speed were compared, and this resulted in the numerical model quite faithfully reproducing the frequency of the peak at 5 m/s, while the error was in the order of 20% for the 10 m/s case; this supports that, despite the URANS approach being affected by well-known critical points regarding the simulation of instantaneous quantities, it can be employed to elaborate information that can be particularly useful for the structural design of the panel. This kind of result can be considered as a first step, obtained with simplified and affordable methods, towards a characterisation of the dynamic behaviour of a PV panel in a real-world setup.

Mock circulatory loops used for testing cardiac assist devices: A review of computational and experimental models

Heart failure is a major health risk, and with limited availability of donor organs, there is an increasing need for developing cardiac assist devices (CADs). Mock circulatory loops (MCL) are an important in-vitro test platform for CAD’s performance assessment and optimisation. The MCL is a lumped parameter model constructed out of hydraulic and mechanical components aiming to simulate the native cardiovascular system (CVS) as closely as possible. Further development merged MCLs and numerical circulatory models to improve flexibility and accuracy of the system; commonly known as hybrid MCLs. A total of 128 MCLs were identified in a literature research until 25 September 2020. It was found that the complexity of the MCLs rose over the years, recent MCLs are not only capable of mimicking the healthy and pathological conditions, but also implemented cerebral, renal and coronary circulations and autoregulatory responses. Moreover, the development of anatomical models made flow visualisation studies possible. Mechanical MCLs showed excellent controllability and repeatability, however, often the CVS was overly simplified or lacked autoregulatory responses. In numerical MCLs the CVS is represented with a higher order of lumped parameters compared to mechanical test rigs, however, complex physiological aspects are often simplified. In hybrid MCLs complex physiological aspects are implemented in the hydraulic part of the system, whilst the numerical model represents parts of the CVS that are too difficult to represent by mechanical components per se. This review aims to describe the advances, limitations and future directions of the three types of MCLs.

The Impact of Steady Blowing from the Leading Edge of an Open Cavity Flow

Cavity flows occur in a wide range of low-speed applications (Mach number ≤0.3), such as aircraft wheel wells, ground transportation, and pipelines. In the current study, a steady jet is forced from a cavity leading edge at different momentum fluxes (0.11 kg/ms2, 0.44 kg/m·s2, and 0.96 kg/m·s2). The investigation was performed for an open cavity with length to depth ratio of 4 at the Reynolds number based on a cavity depth of approximately 50,000. Particle image velocimetry, surface oil flow visualisation, constant temperature anemometry, and pressure measurements were performed in this investigation. The aim of the jet blowing is to separate the cavity separated shear layer from the recirculation zone to reduce the cavity return flow, and hence stabilise the cavity separated shear layer. It was found that increasing the jet momentum flux causes an increase in the cavity return flow due to the increase in the thickness of the cavity separated shear layer. The study also found that the jet populates the separated shear layer with a large number of small-scale disturbances. These disturbances increase the broad band level of the pressure power spectra and Reynolds shear stress in the cavity separated shear layer. On the other hand, the jet disturbances make the shedding of the large vortical structures more intermittent.

ONE ARABESQUE IN THE SMALL WORLD OF OD WEBMAPS

Arabesque is an application for the exploration and geovisualisation of origin-destination flows (or spatial networks), developed within the framework of the Univ. Gustave Eiffel (ex. IFSTTAR)-funded research project geographic flow visualisation (gflowiz) geoflowiz, in collaboration with the CNRS. It allows both the exploration and the filtering of OD data and their representation, with a strong emphasis on geographic information layering and features' semiology. The key-objective is to propose an easy way to produce a modern cartography (a geovisualisation) of thematic flows (e.g. bilateral flow volume), at several geographic scales, even from your own datasets. The objective of this article is to position Arabesque in the range of geoweb applications for producing flow maps, by comparing its functionalities with those of similar web applications – Magrit, Kepler.gl, flowmap.blue – pointing out their respective advantages and limitations. The analysis of its functionalities is compared on the same flow dataset – MOBSCO, i.e. a dataset describing the school mobility of French pupils and students on a given year – for a practical and empirical “validation” of its contributions. We demonstrate that the configurations and appearances of these tools’ visual output depend largely on the culture of their developers, and on the use and audiences for which they have been developed.

Towards capturing a database of respiratory exhalations from flow visualisations

One of the most common modes of infection transmission is through pathogen laden droplets expelled during natural human respiratory exhalations such as speaking, coughing, and sneezing. Infection control guidelines for the prevention of respiratory infection make assumptions about two key parameters: the safe distance between an infected and healthy individual and the size of large and small droplets (Bahl et al., 2020). Studies in the past have utilised flow visualisation techniques to understand the dynamics of respiratory flows but most of them provide only qualitative data on respiratory droplets and do not provide sufficient detail to estimate accurate flow velocities (Bourouiba et al., 2014; Vansciver et al., 2011; Scharfman et al., 2016). One of the reasons this remains a demanding application is the vast range of droplet sizes that are expelled at various velocities. Here, we present an experimental framework using particle tracking to understand the flow dynamics of the expelled droplets. Three different illumination techniques were used to capture high-speed frames of different exhalations (see figure 1). The high density of droplets in case of sneezing lead to overlap of droplet trajectories with volume illumination approach, which was resolved using tailored optics to illuminate only a slice of sneeze flow. Thereafter, the image processing techniques required for precise PTV were refined to examine droplet dynamics of various exhalations (see figure 2). The techniques were applied to multiple cases of respiratory exhalations to understand subject to subject variability. The results for sneezing revealed a mean droplet velocity of 2 m/s to 5.4 m/s across different subjects. Additionally, less than 1% of droplets were expelled at velocities greater than 10 m/s and almost 80% of were expelled at velocities less than 5 m/s. These values were substantially lower than the values usually assumed in studies modelling or replicating sneezes (Xie et al., 2007; Atkinson and Wein, 2008). The results also revealed a high variation in the droplet dynamics, even among the sneezes from the same subject. Flow direction, spread angle, and head movement were also quantified, and the results reveal substantial variation between the subjects. In the case of coughing, maximum droplet velocities observed were in the range of 10−15 m/s however, these high velocities were detected only during the initial 0.05 s. This work addresses the critical gaps in the understanding of the respiratory transmission of infection by providing valuable data on the droplet dynamics of various exhalations, on which the experimental data was very limited in the existing literature. Furthermore, this data will aid in numerical modelling of respiratory flows, particularly for sneezes, as studies to date rely only on airflow data of the exhalations.