A review of image-based simulation applications in high-value manufacturing

Image-Based Simulation (IBSim) is the process by which a digital representation of a real geometry is generated from image data for the purpose of performing a simulation with greater accuracy than with idealised Computer Aided Design (CAD) based simulations. Whilst IBSim originates in the biomedical field, the wider adoption of imaging for non-destructive testing and evaluation (NDT/NDE) within the High-Value Manufacturing (HVM) sector has allowed wider use of IBSim in recent years. IBSim is invaluable in scenarios where there exists a non-negligible variation between the ‘as designed’ and ‘as manufactured’ state of parts. It has also been used for characterisation of geometries too complex to accurately draw with CAD. IBSim simulations are unique to the geometry being imaged, therefore it is possible to perform part-specific virtual testing within batches of manufactured parts. This novel review presents the applications of IBSim within HVM, whereby HVM is the value provided by a manufactured part (or conversely the potential cost should the part fail) rather than the actual cost of manufacturing the part itself. Examples include fibre and aggregate composite materials, additive manufacturing, foams, and interface bonding such as welding. This review is divided into the following sections: Material Characterisation; Characterisation of Manufacturing Techniques; Impact of Deviations from Idealised Design Geometry on Product Design and Performance; Customisation and Personalisation of Products; IBSim in Biomimicry. Finally, conclusions are drawn, and observations made on future trends based on the current state of the literature

Microstructural evaluation and recommendations for face masks in community use to reduce the transmission of respiratory infectious diseases

Background and objectives: Recommendations for the use of face masks to prevent and protect against the aerosols (5µm) and respiratory droplet particles (5µm), which can carry and transmit respiratory infections including severe acute respiratory syndrome coronavirus (SARS-CoV-2), have been in effect since the early stages of the coronavirus disease 2019 (COVID-19). The particle filtration efficiency (PFE) and air permeability are the most crucial factors affecting the level of pathogen transmission and breathability, i.e. wearer comfort, which should be investigated in detail. Methods: In this context, this article presents a novel assessment framework for face masks combining X-ray microtomography and computational fluid dynamics simulations. In consideration to their widespread public use, two types of face masks were assessed: (I) two layer non-woven face masks and (II) the surgical masks (made out of a melt-blown fabric layer covered with two non-woven fabric layers). Results: The results demonstrate that the surgical masks provide PFEs over 75% for particles with diameter over 0.1µm while two layer face masks are found out to have insufficient PFEs, even for the particles with diameter over 2µm (corresponding PFE is computed as 47.2%). Thus, existence of both the non-woven fabric layers for mechanical filtration and insertion of melt-blown fabric layer(s) for electrostatic filtration in the face masks were found to be highly critical to prevent the airborne pathogen transmission. Conclusions: The present framework would assist in computational assessment of commonly used face mask types based on their microstructural characteristics including fiber diameter, orientation distributions and fiber network density. Therefore, it would be also possible to provide new yet feasible design routes for face masks to ensure reliable personal protection and optimal breathability.peerReviewe