Homogenization with uncertainty in Poisson ratio for polymers with rubber particles

The main aim of this work is dual computer analysis of probabilistic coefficients for the homogenized tensor of the polymer filled with the rubber particles having randomized Poisson ratios of both constituents. The major issue is to verify an influence of a randomness in rubber Poisson ratio close to the compressibility limit on the uncertainty of the effective tensor probabilistic characteristics. Probabilistic analysis presented here is carried out using mainly the stochastic perturbation technique provided by the common application of the traditional FEM commercial code ABAQUS and the symbolic computations package MAPLE. This FEM-based technique employs polynomial response function of the optimum order recovered from the weighted least squares method and following a set of deterministic solutions obtained for various values of the randomized input parameter. Optimization procedure is released entirely into a symbolic environment, where maximization of the correlation factor together with minimization of the fitting variance and approximation error are applied. Homogenization technique consists in equating of deformation energies for the real composite and the artificial one characterized by the effective elasticity tensor with uncertainty.     

Dynamic mechanical analysis and thermal properties of LLDPE/EVA/modified silica nanocomposites

The effect of hexamethylene disilazane modified nanosilica on the dynamic mechanical analysis (DMA), crystallization, melting and thermal degradation behavior of linear low density polyethylene/ethylene vinyl acetate copolymer (LLDPE/EVA) blends are explored.Detailed DMA analysis is carried out in order to investigate the reinforcing behavior of nanosilica adopting Kerner–Nielson model. Oxidative degradation and thermal stabilities of samples are also studied by the thermogravimetery analysis. The high content of nanosilica particles results in significant shift of degradation temperature to higher temperatures in the oxygen atmosphere. This behavior might be attributed to the barrier properties of nanoparticles against oxygen and gaseous degradation products. However, incorporation of modified nanosilica into LLDPE/EVA blend is decreased the onset of degradation temperature of the unfilled system. In nitrogen atmosphere, no changes are observed in the thermal degradation range and only a reduction is documented in the onset of degradation temperature. Considering important role of onset of degradation temperature, activation energy of starting of degradation temperature is calculated utilizing Kissinger-Ozawa model in both oxygen and nitrogen atmospheres. Results showed that activation energy of degradation reaction is decreased by ∼ 20 kJ/mol. This decrease is owing to the release of modifiers from the nanoparticles.     

Optimal-correlation-based reconstruction for distributed compressed video sensing

Distributed compressed video sensing (DCVS) is a framework that integrates both compressed sensing and distributed video coding characteristics to achieve a low-complexity video coding. However, how to design an efficient joint reconstruction by leveraging more realistic signal models is still an open challenge. In this paper, we present a novel optimal-correlation-based reconstruction method for compressively sampled videos from multiple measurement vectors. In our method, the sparsity is mainly exploited through inter-signal correlations rather than the traditional frequency transform, wherein the optimization is not only over the signal space to satisfy data consistency but also over all possible linear correlation models to achieve minimum-l₁-norm correlation noise. Additionally, a two-phase Bregman iterative based algorithm is outlined for solving the optimization problem. Simulation results show that our proposal can achieve an improved reconstruction performance in comparison to the conventional approaches, and especially, offer a 0.7–9.9 dB gain in the average PSNR for DCVS.     

Application of Vis–NIR hyperspectral imaging in classification between fresh and frozen-thawed pork Longissimus Dorsi muscles

Fresh and frozen-thawed (F-T) pork meats were classified by Vis–NIR hyperspectral imaging. Eight optimal wavelengths (624, 673, 460, 588, 583, 448, 552 and 609 nm) were selected by successive projections algorithm (SPA). The first three principal components (PCs) obtained by principal component analysis (PCA) accounted for over 99.98% of variance. Gray-level-gradient co-occurrence matrix (GLGCM) was applied to extract 45 textural features from the PC images. The correct classification rate (CCR) was employed to evaluate the performance of the partial least squares-discriminate analysis (PLS-DA) models, by using (A) the reflected spectra at full wavelengths and (B) those at the optimal wavelengths, (C) the extracted textures based on the PC images, and (D) the fused variables combining spectra at the optimal wavelengths and textures. The results showed that the best CCR of 97.73% was achieved by applying (D), confirming the high potential of textures for fresh and F-T meat discrimination.     

Thermoplastic–epoxy interactions and their potential applications in joining composite structures – A review

This paper presents a literature survey on the theoretical backgrounds and the past research efforts in relation to the interactions between certain thermoplastics and epoxies, and their applications in polymer blending, epoxy toughening and composite joining. The main objectives are to understand the possible mechanisms of interfacial adhesion between thermoplastic and thermoset polymers, and also to explore the feasible approaches to improve interfacial adhesion for the purposes of joining fibre reinforced polymer (FRP) composite structures by fusion bonding. Further, it is expected that the review would provide some visions to the potential applications of the thermoplastic–thermoset interfacial interactions for the quick assembly of composite structures in cost-effective manufacturing of composite structures, through the uses of the technologies, such as thermoset composite fusion bonding, welding of thermoplastic composites with thermoset composites, and thermoplastic article attachment on thermoset composites.     

A novel methodology for the rapid identification of the water diffusion coefficients of composite materials

The paper presents a novel methodology for the rapid identification of the water diffusion coefficients of composite materials. The methodology consists in employing a numerical parametric Proper Generalized Decomposition (PGD) method allowing incorporating the diffusion coefficients among the number of degrees of freedom. Compared to classical identification schemes, often based on Finite Element Method (FEM) iterations, the proposed method allows achieving consistent CPU time gain. The method is general and can be applied when diffusion anomalies take place or when diffusion–reaction coupling must be taken into account, moreover can deal with anisotropic materials. However, for the scope of illustration, in the present case, it is applied to the simple case of “classical diffusion” (Fick’s model with constant boundary conditions) and concerns isotropic materials.     

Design of natural fiber composites utilizing interfacial crystallinity and affinity

Butanediol initiated poly(ε-caprolactone) (PCL) has recently been reported as a toughening agent for cationically curing cycloaliphatic epoxides providing plasticized thermosets with excellent properties (Lützen et al., 2013). In this contribution that promising toughening approach was applied for the first time for the development of novel natural fiber composites (NFC). NFCs based on conventional brittle thermosetting polymers often suffer from poor interfacial adhesion and stress cracking. Composites made up of the novel plasticized thermosets and woven flax fiber preserved the elastomer-like properties and increased tensile strength and elongation at break up to 60 MPa and 5%, respectively. Furthermore, PCL was shown not only to toughen the epoxide but also to modulate the affinity of the matrix to the fiber. In conclusion, improved interfacial adhesion and the resulting excellent mechanical properties of cationically curable NFCs were achieved by both interfacial crystallization and affinity.     

Pressure sensor matrix for indirect measurement of grip and push forces exerted on a handle

To date, a large part of workers is exposed to vibrations (23% in Europe) which can negatively impact on their health. This work discusses the importance of measuring grip and push forces in the context of hand-arm vibration tests, bearing in mind the state-of-art of current standards. It proposes a method for indirect measurement of coupling forces using a matrix of polymeric pressure capacitive sensors and discusses the model used for defining these quantities. The matrix of pressure sensors is wrapped around the tool handle and the acting forces, exchanged with the handle, are derived from the pressure values measured by the matrix. Calibration is presented and the effect of curvature is discussed. The work continues with the experimental validation of the model proposed for push force measurements carried out through lifting tests using known masses with a cylindrical handle. An experimental correction coefficient is defined in correlation to the type of grip. The method for measuring the push force, thus corrected, is assessed by means of push force tests on an instrumented handle. Finally the experimental data are analysed in order to assess the uncertainty of the proposed method for measuring the push force, highlighting the contribution of the different sources of uncertainty. The proposed measurement method allows to measure the push and the grip force (known influencing quantities for the measurement of the hand-arm vibration) during tool test and without modifying the handles.     

Investigation of mechanical and tribological behaviors of multilayer graphene reinforced Ni3Al matrix composites

Multilayer graphene (MLG) shows an attractive prospect for the demanding engineering applications. This paper reports the mechanical and tribological properties of MLG reinforced Ni₃Al matrix composites (NMCs) under dry sliding at varying sliding speed. The hardness and elastic modulus of the NMCs are significantly influenced with MLG content. It is found that the hardness and elastic modulus of the NMCs are found to be increased by increasing MLG content up to 1.0 wt.%, while decreased when MLG content is above 1.0 wt.%. Tribological experiments suggest that MLG can dramatically improve the wear resistance and decrease the friction coefficient of the NMCs. Such marked improvement of wear resistance is attributed to the reinforcing mechanisms of MLG, such as crack deflection and pull-out, and reduction of friction coefficient is related to the formation of a tribofilm on the sliding contact surface.