The increase in accessibility of fused filament fabrication (FFF) machines has inspired the scientific community to work towards the understanding of the structural performance of components fabricated with this technology. Numerous attempts to characterize and to estimate the mechanical properties of structures fabricated with FFF have been reported in the literature. Experimental characterization of printed components has been reported extensively. However, few attempts have been made to predict properties of printed structures with computational models, and a lot less work with analytical approximations. As a result, a thorough review of reported experimental characterization and predictive models is presented with the aim of summarizing applicability and limitations of those approaches. Finally, recommendations on practices for characterizing printed materials are given and areas that deserve further research are proposed.

Non-pathological mental fatigue is a recurring, but undesirable condition among people in the fields of office work, industry, and education. This type of mental fatigue can often lead to negative outcomes, such as performance reduction and cognitive impairment in education; loss of focus and burnout syndrome in office work; and accidents leading to injuries or death in the transportation and manufacturing industries. Reliable mental fatigue assessment tools are promising in the improvement of performance, mental health and safety of students and workers, and at the same time, in the reduction of risks, accidents and the associated economic loss (e.g., medical fees and equipment reparations). The analysis of biometric (brain, cardiac, skin conductance) signals has proven to be effective in discerning different stages of mental fatigue; however, many of the reported studies in the literature involve the use of long fatigue-inducing tests and subject-specific models in their methodologies. Recent trends in the modeling of mental fatigue suggest the usage of non subject-specific (general) classifiers and a time reduction of calibration procedures and experimental setups. In this study, the evaluation of a fast and short-calibration mental fatigue assessment tool based on biometric signals and inter-subject modeling, using multiple linear regression, is presented. The proposed tool does not require fatigue-inducing tests, which allows fast setup and implementation. Electroencephalography, photopletismography, electrodermal activity, and skin temperature from 17 subjects were recorded, using an OpenBCI helmet and an Empatica E4 wristband. Correlations to self-reported mental fatigue levels (using the fatigue assessment scale) were calculated to find the best mental fatigue predictors. Three-class mental fatigue models were evaluated, and the best model obtained an accuracy of 88% using three features, β/θ (C3), and the α/θ (O2 and C3) ratios, from one minute of electroencephalography measurements. The results from this pilot study show the feasibility and potential of short-calibration procedures and inter-subject classifiers in mental fatigue modeling, and will contribute to the use of wearable devices for the development of tools oriented to the well-being of workers and students, and also in daily living activities.

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Purpose The purpose of this paper is to study the feasibility of the fabrication of circle arc curved-layered structures via conventional fused deposition modeling (FDM) with three-axis machines and to identify the main structural parameters that have an influence on their mechanical properties. Design/methodology/approach Customized G-codes were generated via a script developed in MATLAB. The G-codes contain nozzle trajectories with displacements in the three axes simultaneously. Using these, the samples were fabricated with different porosities, and their influence on the mechanical responses evaluated via tensile testing. The load-displacement curves were analyzed to understand the structure-property relationship. Findings Circled arc curved-layered structures were successfully fabricated with conventional three-axis FDM machines. The response of these curved lattice structures under tensile loads was mapped to three main stages and deformation mechanisms, namely, straightening, stretching and fracture. The micro-structure formed by the transverse filaments affect the first stage significantly and the other two minimally. The main parameters that affect the structural response were found to be the transverse filaments, as these could behave as hinges, allowing the slide/rotation of adjacent layers and making the structure more shear sensitive. Research limitations/implications This paper was restricted to arc-curved samples fabricated with conventional three-axis FDM machines. Originality/value The FDM fabrication of curved-structures with controlled porosity and their relation to the resulting mechanical properties is presented here for the first time. The study of curved-lattice structures is of great relevance in various areas, such as biomedical, architecture and aerospace.

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