Through-thickness permeability modelling of woven fabric under out-of-plane deformation

When a woven fabric is subject to a normal uniform loading, its properties such as tightness and through-thickness permeability are both altered, which relates to the fabric out-of-plane deformation (OPD) and dynamic permeability (DP). In this article, fabric OPD is analytically modelled through an energy minimisation method, and corresponding fabric DP is established as the function of loading and fabric-deformed structure. The total model shows the permeability a decrease for tight fabric and an increase for loose fabric when the uniform loading increases. This is verified experimentally by fabric OPD, static and dynamic permeabilities. Experimental tests for both permeabilities showed good agreement with the corresponding predictions, indicating the fact that tight fabric becomes denser and loose fabric gets more porous during OPD. A sensitivity study showed that an increase of fabric Young’s modulus or a decrease of fabric test radius both lead to an increase of DP for tight fabric and opposite for loose fabric. The critical fabric porosity and thickness were found for inflexion of fabric DP trend during the OPD, which contributes to the optimum design of interlacing structure applied to protective textiles and composites.     

Fractal growth of the dense-packing phase in annealed metallic glass imaged by high-resolution atomic force microscopy

Unlike crystalline metals, which have a well-understood periodical structure, the amorphous structure of metallic glasses (MGs) is still poorly understood, particularly when such a structure rearranges itself at the nanoscale under external agitations. In this article, we provide compelling evidence obtained from a recently developed high-resolution atomic force microscopy (HRAFM) technique that reveals the nanoscale structural heterogeneity after thermal annealing in a Zr–Ni metallic glass. Through the HRAFM technique, we are able to uncover the annealing-induced fractal growth of the dense-packing phases in the binary MG thin film, which exhibits a fractal dimension of ～1.7, in line with a two-dimensional diffusion limited aggregation process. The current findings not only reveal the evolution process of atomic packing in the annealed MG thin film, but also shed light on the possible cooling rate effect on the atomic structure of MGs.     

Microstructure and sliding wear behavior of pseudo-alloy PS45/CuAl8 composite coating sprayed by HVAA technique

A pseudo-alloy PS45/CuAl8 composite coating was sprayed on steel substrate by high-velocity activated arc spraying (HVAA) process. Its sliding wear behavior at room temperature was evaluated by M-2000 wear tester. For comparison, a single CuAl8 coating was also prepared and tested under the same conditions. It is found that the pseudo-alloy composite coating consists of α-Cu and γ-Ni metallic matrix phases together with homogenously distributed minor Al 2 O 3 , Cr 2 O 3 oxide phases. Moreover, pseudo-alloy coating possesses much better sliding wear resistance than CuAl8 coating due to the enhanced hardness and microstructural homogenization. Fatigue wear and abrasive wear are responsible for the wear-down mechanism of the pseudo-alloy coating.     

Effects of oxidised linoleic acid on the formation of Nε‐carboxymethyl‐lysine and Nε‐carboxyethyl‐lysine in Maillard reaction system

This study investigated the effects of oxidised linoleic acid (18:2) on N^ε‐carboxymethyl‐lysine (CML) and N^ε‐carboxyethyl‐lysine (CEL) formation in Maillard reaction systems. Model systems of lysine/glucose (L/G), lysine/18:2 (L/18:2), lysine/18:2/glucose (L/18:2/G), myofibrillar protein/glucose (MFP/G), MFP/18:2 and MFP/18:2/G were maintained at 37 °C for 6 weeks. The results showed that CML/CEL contents in L/G (6.99 and 0.96 mmol mol^?1 lysine, respectively) were significantly higher than those in L/18:2/G (1.43 and 0.41 mmol mol^?1 lysine, respectively), and there is a small amount of CML/CEL generation in L/18:2. However, the CML/CEL levels in MFP/G (197.2 and 83.8 ng mg^?1 protein, respectively) were markedly lower than those in MFP/18:2/G (283.2 and 118.5 ng mg^?1 protein, respectively). 18:2 favours the formation of CML/CEL in MFP/18:2/G, not in L/18:2/G. All these findings indicated that the role of 18:2 on CML/CEL formation in Maillard reaction system was complex, and depended on CML/CEL formation rate and substrate types (lysine or lysine residue in protein).     

Stability analysis of the propagation of periodic parallel hydraulic fractures

When multiple fractures are propagating simultaneously, the fracture spacing may coarsen gradually resulting from loss of stability of the fracture system, which can also occur during the propagation of multiple hydraulic fractures (HFs). In this paper, the stability of the propagation of periodic parallel HFs in brittle solids is investigated based on a representative unit cell consisting two HFs. The fractures are driven to propagate by the inside fluid flow and fluid–solid coupling effect is involved. Both the stress interaction acting in the solid medium and the flow of fluid medium can influence the stability. Stability criterions are given based on the variations of the rates of change of the stress intensity factor with respect to facture velocities. Stability results are obtained by solving the system with fully coupled numerical method which considers the deformation of solid medium, fracture propagation, fluid flow in fractures, fluid partitioning into each fracture. Based on the numerical results, the influences of propagation regimes, fracture lengths and the fracture distance on the stability of HFs are investigated.     

Parameterized ABD preconditioning technique for time-periodic convection–diffusion problems

In this paper, a parameterized additive block diagonal (PABD) preconditioning technique is present for solving the nine-point approximations of the time-periodic convection–diffusion problems. The explicit expressions for the eigenvalues and eigenvectors of the corresponding preconditioned matrices are presented. The range of the optimal parameters is derived. Numerical experiments show that the generalized minimal residual method preconditioned by the PABD preconditioner with the experimental optimal parameters or some special values is effective for a wide range of problem sizes.     

Preparation of polyacrylonitrile/graphene oxide by in situ polymerization

Highly oriented molecular structure is essential for high‐performance carbon fibers. The addition of a small amount of graphene sheets may enhance the degree of molecular orientation of precursor fibers during spinning and stabilization by limiting the disorientation of the chain segments. Graphene sheets merge into the carbon fiber structure during carbonization. The structure and properties of polyacrylonitrile containing graphene oxide (GO) prepared by in situ polymerization were investigated. With increasing GO loading, the molecular weight of the polymer decreased gradually from 69 000 g mol^?1 for the sample without GO to 60 600 g mol^?1 for the sample with 2.5 wt% loading of GO. Scanning electron microscopy and X‐ray diffraction results indicated that GO was dispersed in single layers in the polymer matrix. The degree of crystallization of the polymer with 0.5 wt% GO was increased by 8%. Moreover, differential scanning calorimetry and thermogravimetric analysis showed that an appropriate amount of GO, e.g. 0.5 wt%, made the carbon yield of the polymer increase by 5.0 wt%, because the GO in the composite improved the intermolecular crosslinking reaction. Copyright © 2012 Society of Chemical Industry     

Ensemble of extreme learning machine for landslide displacement prediction based on time series analysis

Landslide hazard is a complex nonlinear dynamical system with uncertainty. The evolution of landslide is influenced by many factors such as tectonic, rainfall and reservoir level fluctuation. Using a time series model, total accumulative displacement of landslide can be divided into the trend component displacement and the periodic component displacement according to the response relation between dynamic changes in landslide displacement and inducing factors. In this paper, a novel neural network technique called ensemble of extreme learning machine (E-ELM) is proposed to investigate the interactions of different inducing factors affecting the evolution of landslide. Grey relational analysis is used to sieve out the more influential inducing factors as the inputs in E-ELM. Trend component displacement and periodic component displacement are forecasted, respectively; then, total predictive displacement is obtained by adding the calculated predictive displacement value of each sub. Performances of our model are evaluated by using real data from Baishuihe landslide in the Three Gorges Reservoir of China, and it provides a good representation of the measured slide displacement behavior.