A comprehensive review on analysis of nanocomposites: from manufacturing to properties characterization

The study of nanocomposites in its diverse scientific fields has increased dramatically over the years with numerous theoretical and experimental techniques emerging and redefining the process of synthesis, analysis and cost control methodologies of nanocomposites. The present review is an attempt to identify the various methodologies, techniques, theories and formulations that are used in nanocomposite technology. As an overall qualitative appreciation it is possible to conclude that the diversity of processes involved in the manufacture and analysis of nanocomposites, impacts them differently, influencing their physical nature, chemical behaviour, biological interactions, optical properties and production costs which consequently may introduce some constraints to their application. Hence, a critical review on the best methodology would remain inconclusive. This work intends to collect and relate publications on different fields of the nanocomposites technology and application fields, aiming at contributing to achieve a wide perspective of different aspects of the nanocomposites processes and theories and with this, being an aid to ease and raise the production and analysis of nanocomposites to a higher level

Using 3D anthropometric data for the modelling of customised head immobilisation masks

Projeto IPL/2016/SoftImob/ISEL; Projeto IPL/2016/CardiaCor_ESTeSL; Projeto LAETA_UID/EMS/50022/2019.Head immobilization thermoplastic masks for radiotherapy purposes involve a distressful modeling procedure for the patient. To assess the possibility of using different acquisition and reconstruction methods to obtain a 3D skin surface model of PIXY-phantom-head and to present a proposal of an alternative head immobilization mask prototype. Phantom head geometry acquisitions using: computed tomography (reconstructed with ImageJ and Osirix); and 3D Laser Scanner (reconstructed with SolidWorks). From these reconstructed surface models, a set of landmarks was measured and subsequently compared with physical measurements obtained with a Rosscraft-Calliper. For statistical evaluation, relative deviations graphics and Friedman-test for non-parametrical paired samples were used, with a significance level of 5%. For a first assessment of the proposed mask performance, a radiotransparent material was considered, the strength and stiffness evaluation is performed using the finite element method. There are small differences between all the acquisitions and reconstructions methods and the physical measurements, statistically significant differences (X2F(6)) = 6.863, p=0.334) were not found. The proposed mask performed well from the strength and stiffness perspectives, leading to the desired immobilization aim. The immobilization mask design proposal may be an effective alternative to the present completely hand-made situation, which presents a high degree of discomfort and stress to the patients.info:eu-repo/semantics/publishedVersio

A Critical Assessment of Kriging Model Variants for High-Fidelity Uncertainty Quantification in Dynamics of composite Shells

This paper presents a critical comparative assessment of Kriging model variants for surrogate based uncertainty propagation considering stochastic natural frequencies of composite doubly curved shells. The five Kriging model variants studied here are: Ordinary Kriging, Universal Kriging based on pseudo-likelihood estimator, Blind Kriging, Co-Kriging and Universal Kriging based on marginal likelihood estimator. First three stochastic natural frequencies of the composite shell are analysed by using a finite element model that includes the effects of transverse shear deformation based on Mindlin’s theory in conjunction with a layer-wise random variable approach. The comparative assessment is carried out to address the accuracy and computational efficiency of five Kriging model variants. Comparative performance of different covariance functions is also studied. Subsequently the effect of noise in uncertainty propagation is addressed by using the Stochastic Kriging. Representative results are presented for both individual and combined stochasticity in layer-wise input parameters to address performance of various Kriging variants for low dimensional and relatively higher dimensional input parameter spaces. The error estimation and convergence studies are conducted with respect to original Monte Carlo Simulation to justify merit of the present investigation. The study reveals that Universal Kriging coupled with marginal likelihood estimate yields the most accurate results, followed by Co-Kriging and Blind Kriging. As far as computational efficiency of the Kriging models is concerned, it is observed that for high-dimensional problems, CPU time required for building the Co-Kriging model is significantly less as compared to other Kriging variants