Relation between interfacial shear strength and compressive strength of carbon fiber/epoxy resin composite strands

The mechanism with which the fiber-matrix interfacial strength exerts its influence on the compressive strength of fiber reinforced composites has been studied by measuring the axial compressive strength of carbon fiber/epoxy resin unidirectional composite strands having different levels of interfacial shear strength. The composite strands are used for experiments in order to investigate the compressive strength which is not affected by the delamination taking place at a weak interlayer of the laminated composites. The interfacial strength is varied by applying various degrees of liquid-phase surface treatment to the fibers. The efficiency of the compressive strength of the fibers utilized in the strength of the composite strands is estimated by measuring the compressive strength of the single carbon filaments with a micro-compression test. The compressive strength of the composite strands does not increase monotonically with increasing interfacial shear strength but showes lower values at higher interfacial shear strengths. With increasing interfacial shear strength, the suppression of the interfacial failure in the misaligned fiber region increases the compressive strength, while at higher interfacial shear strengths, the enhancement of the crack sensitivity decreases the compressive strength.     

MRI investigation of granular interface rheology using a new cylinder shear apparatus

The rheology of granular materials near an interface is investigated through proton magnetic resonance imaging. A new cylinder shear apparatus has been inserted in the magnetic resonance imaging device, which allows the control of the radial confining pressure exerted by the outer wall on the grains and the measurement of the torque on the inner shearing cylinder. A multi-layer velocimetry sequence has been developed for the simultaneous measurement of velocity profiles in different sample zones, while the measurement of the solid fraction profile is based on static imaging of the sample. This study describes the influence of the roughness of the shearing interface and of the transverse confining walls on the granular interface rheology.     

Rheological Behavior of Dope Solutions of Poly(acrylonitrile‐co‐itaconic acid) in N,N‐dimethylformamide: Effect of Polymer Molar Mass

The rheological behavior of dope solutions of poly(acrylonitrile‐co‐itaconic acid) or poly(AN‐co‐IA) is important from the point of view of deriving the spinning conditions for good quality special acrylic fibers. The viscosity of the resin dope is dictated by the polymer concentration, molar mass, temperature and shear force. The dynamic shear rheology of concentrated poly(AN‐co‐IA) polymer dope solutions in N, N‐dimethylformamide, in the molar mass (M¯_v) range of 1×10⁵ to 1×10⁶ g/mol, was investigated in the shear rate (γ′) range of 1×10¹ to 5×10⁴ min^?1. An empirical relation between η and M¯_v was found to exist at constant shear rate. The dope viscosity was dependent on the molar mass and the shear rate at a given temperature (T) and concentration. The polymer molar mass index of dope viscosity (m) was calculated as functions of concentration (c), shear rate and temperature. The m values increased with shear rate and temperature. A master equation relating m, with shear rate and temperature was derived for a given dope concentration. At higher shear rates, m tends to the value of 3.4, which is close to the molar mass index of viscosity reported for molten thermoplastics. m increased significantly with shear rate and nominally with temperature, while an increase in concentration decreased it. The onset of shear thinning of the dope shifted to a lower shear rate regime with an increase in polymer concentration and the molar mass. For a given value of molar mass, the increase in viscosity of the dope solution with polymer concentration was dependent on the shear rate.     

Investigation on the Stability of the Dispersion System of Cross-Linked Polyacrylamide Microspheres

The salt resistance, temperature resistance, and shear stability of a cross-linked polyacrylamide microsphere system are studied by microfiltration, light diffraction analysis, and optical microscopy. The results show that other conditions being equal, the particle diameter of cross-linked polyacrylamide microspheres decreases with increased NaCl concentration. When NaCl concentration is lower than 10,000 mg/L, its effect on the plugging performance of a cross-linked polyacrylamide microsphere system in regard to the nuclear pore membrane is weak in comparison with a linked polymer solution, but the former system has better salt tolerance. Particle diameter decreases with increased swelling temperature. When the swelling temperature is below 90°C, its effect on the plugging performance of the cross-linked polyacrylamide microsphere system in regard to nuclear pore membrane is weak in comparison with the linked polymer solution, but has better temperature tolerance. Particle size shows little change, with shearing rate being increased, while the shape remains about the same and the effect of shearing on the plugging performance of the cross-linked polyacrylamide microsphere dispersion system in regard to the nuclear pore membrane is weak in comparison with the linked polymer solution, but has better shear stability. The salt tolerance, temperature tolerance, and shear stability of microspheres are associated with a particular cross-linked structure.     

Shear‐induced lamellar phase of an ionic liquid crystal at room temperature

The phase behaviour of a number of N‐alkylimidazolium salts was studied using polarizing optical microscopy, differential scanning calorimetry and X‐ray diffraction. Two of these compounds exhibit lamellar mesophases at temperatures above 50°C. In these systems, the liquid crystalline behaviour may be induced at room temperature by shear. Sheared films of these materials, observed between crossed polarisers, have a morphology that is typical of (wet) liquid foams: they partition into dark domains separated by brighter (birefringent) walls, which are approximately arcs of circle and meet at “Plateau borders” with three or more sides. Where walls meet three at a time, they do so at approximately 120° angles. These patterns coarsen with time and both T1 and T2 processes have been observed, as in foams. The time evolution of domains is also consistent with von Neumann's law. We conjecture that the bright walls are regions of high concentration of defects produced by shear, and that the system is dominated by the interfacial tension between these walls and the uniform domains. The control of self‐organised monodomains, as observed in these systems, is expected to play an important role in potential applications.     

Additive hazards regression with random effects for clustered failure times

Additive hazards model with random effects is proposed for modelling the correlated failure time data when focus is on comparing the failure times within clusters and on estimating the correlation between failure times from the same cluster, as well as the marginal regression parameters. Our model features that, when marginalized over the random effect variable, it still enjoys the structure of the additive hazards model. We develop the estimating equations for inferring the regression parameters. The proposed estimators are shown to be consistent and asymptotically normal under appropriate regularity conditions. Furthermore, the estimator of the baseline hazards function is proposed and its asymptotic properties are also established. We propose a class of diagnostic methods to assess the overall fitting adequacy of the additive hazards model with random effects. We conduct simulation studies to evaluate the finite sample behaviors of the proposed estimators in various scenarios. Analysis of the Diabetic Retinopathy Study is provided as an illustration for the proposed method.     

Parametric inference for multiple repairable systems under dependent competing risks

The focus of this article is on the analysis of repairable systems that are subject to multiple sources of recurrence. The event of interest at the system level is assumed to be caused by the earliest occurrence of a source, thereby conforming to a series system competing risks framework. Parametric inference is carried out under the power law process model that has found significant attention in industrial applications. Dependence among the cause‐specific recurrent processes is induced via a shared frailty structure. The theoretical inference results are implemented to a warranty database for a fleet of automobiles, for which the warranty repair is triggered by the failure of one of many components. Extensive finite‐sample simulation is carried out to supplement the asymptotic findings. Copyright © 2014 John Wiley & Sons, Ltd.     

Determination of 12 potential nephrotoxicity biomarkers in rat serum and urine by liquid chromatography with mass spectrometry and its application to renal failure induced by Semen Strychni

In previous nephrotoxicity metabonomic studies, several potential biomarkers were found and evaluated. To investigate the relationship between the nephrotoxicity biomarkers and the therapeutic role of Radix Glycyrrhizae extract on Semen Strychni‐induced renal failure, 12 typical biomarkers are selected and a simple LC–MS method has been developed and validated. Citric acid, guanidinosuccinic acid, taurine, guanidinoacetic acid, uric acid, creatinine, hippuric acid, xanthurenic acid, kynurenic acid, 3‐indoxyl sulfate, indole‐3‐acetic acid, and phenaceturic acid were separated by a Phenomenex Luna C₁₈ column and a methanol/water (5 mM ammonium acetate) gradient program with a runtime of 20 min. The prepared calibration curves showed good linearity with regression coefficients all above 0.9913. The absolute recoveries of analytes from serum and urine were all more than 70.4%. With the developed method, analytes were successfully determined in serum and urine samples within 52 days. Results showed that guanidinosuccinic acid, guanidinoacetic acid, 3‐indoxyl sulfate, and indole‐3‐acetic acid (only in urine) were more sensitive than the conventional renal function markers in evaluating the therapeutic role of Radix Glycyrrhizae extract on Semen Strychni‐induced renal failure. The method could be further used in predicting and monitoring renal failure cause by other reasons in the following researches.     

Machine learning as an online diagnostic tool for proton exchange membrane fuel cells

Proton exchange membrane fuel cells are considered a promising power supply system with high efficiency and zero emissions. They typically work within a relatively narrow range of temperature and humidity to achieve optimal performance; however, this makes the system difficult to control, leading to faults and accelerated degradation. Two main approaches can be used for diagnosis, limited data input which provides an unintrusive, rapid but limited analysis, or advanced characterisation that provides a more accurate diagnosis but often requires invasive or slow measurements. To provide an accurate diagnosis with rapid data acquisition, machine learning methods have shown great potential. However, there is a broad approach to the diagnostic algorithms and signals used in the field. This article provides a critical view of the current approaches and suggests recommendations for future methodologies of machine learning in fuel cell diagnostic applications.