Technological scouting of bi-material face masks: experimental analysis on real faces.

The need for personal protective equipment rapidly grew during the COVID-19. Companies had to face problems related to their products' sustainability, adherence, and comfortability. Designing a face mask with proper adherence and comfortability in wearing and breathing became a matter of great importance. In this work, the adherence of an innovative face mask and its comfortability were experimentally tested with real faces, considering the deformation of the mask and the soft facial tissues. A stereophotogrammetric acquisition was made of the face with the face mask during these tests. A comparison between the geometries of the face and the mask, undeformed and deformed, gave the respective deformations. The force applied by the mask to the face was calculated, measuring the elastic strain of the mask bands during wearing and the deformation.

Technological scouting of bi-material face masks: simulation of adherence using 3D Facial Norms.

During the COVID-19 pandemic started in March 2020, the need for personal protective equipment rapidly grew as it became mandatory. The availability of a set of faces can be of great utility in designing a face mask with proper adherence and comfortability in wearing and breathing. A 3D geometry of a face with user-defined anthropometric measures was generated with Blender, a powerful development tool for creating 3D images. Using 3D Facial Norms, a free online database, it was possible to compute the mean anthropometric measures for the age groups of 17-20, 20-30, and 30-40 years old and then generate the respective faces for both genders. The adherence of an innovative face mask was then simulated with the reverse engineering software considering both the face mask and the faces rigid.

Visco-Hyperelastic Characterization of the Equine Immature Zona Pellucida.

This article presents a very detailed study on the mechanical characterization of a highly nonlinear material, the immature equine zona pellucida (ZP) membrane. The ZP is modeled as a visco-hyperelastic soft matter. The Arruda-Boyce constitutive equation and the two-term Prony series are identified as the most suitable models for describing the hyperelastic and viscous components, respectively, of the ZP's mechanical response. Material properties are identified via inverse analysis based on nonlinear optimization which fits nanoindentation curves recorded at different rates. The suitability of the proposed approach is fully demonstrated by the very good agreement between AFM data and numerically reconstructed force-indentation curves. A critical comparison of mechanical behavior of two immature ZP membranes (i.e., equine and porcine ZPs) is also carried out considering the information on the structure of these materials available from electron microscopy investigations documented in the literature.

Mechanical Identification of Materials and Structures with Optical Methods and Metaheuristic Optimization.

This study presents a hybrid framework for mechanical identification of materials and structures. The inverse problem is solved by combining experimental measurements performed by optical methods and non-linear optimization using metaheuristic algorithms. In particular, we develop three advanced formulations of Simulated Annealing (SA), Harmony Search (HS) and Big Bang-Big Crunch (BBBC) including enhanced approximate line search and computationally cheap gradient evaluation strategies. The rationale behind the new algorithms-denoted as Hybrid Fast Simulated Annealing (HFSA), Hybrid Fast Harmony Search (HFHS) and Hybrid Fast Big Bang-Big Crunch (HFBBBC)-is to generate high quality trial designs lying on a properly selected set of descent directions. Besides hybridizing SA/HS/BBBC metaheuristic search engines with gradient information and approximate line search, HS and BBBC are also hybridized with an enhanced 1-D probabilistic search derived from SA. The results obtained in three inverse problems regarding composite and transversely isotropic hyperelastic materials/structures with up to 17 unknown properties clearly demonstrate the validity of the proposed approach, which allows to significantly reduce the number of structural analyses with respect to previous SA/HS/BBBC formulations and improves robustness of metaheuristic search engines.