On the oxidation kinetics and mechanisms of various SiC-coated carbon-carbon composites

SiC coatings on the surface of C-C were produced by either silicone resin impregnation/ pyrolysis or reaction sintering. Cycles of resin impregnation/pyrolysis produced an SiC coating, on the walls of fine open pores, which was effective in reducing the oxidation rate of C-C and in shifting the transition temperature to a higher value. Unless it is pre-coated with a pyrocarbon layer before sintering, plain reaction sintered SiC has oxidation behaviors similar to those of the above-mentioned SiC. The dense pyrocarbon film deposition on the surface of C-C could form a better SiC film than others. The carbon film homogenized the surface of C-C and a dense SiC film was established. The oxidation of the coated C-C can be modelled by a set of “oxidation resistors” in series and/or in parallel, with each resistor corresponding to an oxidation element. The controlling mechanism can be resolved from the activation energy. A combined resistant layer, consisting of resin impregnation, pyrocarbon film and reaction sintering SiC, showed the best oxidation resistance of any single-layer coated C-C composite.     

Transient behaviour of encapsulated enzyme reactor systems

Mathematical models are developed for the transient behaviour of encapsulated enzyme reactor systems such as the continuous stirred tank reactor (CSTR) and the packed bed tubular reactor. The rate processes taking place in the encapsulated enzyme bed are approximated by using a combined rate control model of enzyme reaction and membrane diffusion. The change in transient substrate concentration is obtained by using the developed rate expression in the material balance over the substrate as a function of time for the CSTR and as a function of time and position for the packed bed tubular reactor. The effects of various parameters such as the enzymic reaction rate constant, Michaelis constant, diffusional resistance of membranes, and Peclet number on the substrate concentration distribution, which varies with respect to operating time, are investigated. This study affords insight into the transient operating characteristics of the encapsulated enzyme reactor system. The results should be useful in understanding the start-up performance of the reactor systems and to control such reactor systems at desired operating conditions.     

Experimental study on temperature stress calculation and temperature control optimization of concrete based on early age parameters

Temperature control curve is the key to achieving temperature control and crack prevention of high concrete dam during construction,and its rationality depends on the accurate measurement of temperature stress.With the simulation testing machine for the temperature stress,in the present study,we carried out the deformation process tests of concrete under three temperature curves：convex,straight and concave.Besides,we not only measured the early-age elastic modulus,creep parameters and stress process,but also proposed the preferred type.The results show that at early age,higher temperature always leads to greater elastic modulus and smaller creep.However,the traditional indoor experiments have underestimated the elastic modulus and creep development at early age,which makes the calculated value of temperature stress too small,thus increasing the cracking risk.In this study,the stress values of the three curves calculated based on the strain and early-age parameters are in good agreement with the temperature stress measured by the temperature stress testing machine,which verifies the method accuracy.When the temperature changes along the concave curve,the law of stress development is in consistent with that of strength.Under this condition,the stress fluctuation is small and the crack prevention safety of the concave type is higher,so the concave type is better.The test results provide a reliable basis and support for temperature control curve design and optimization of concrete dams.     

Fast‐moving coin recognition using deep learning

Multimedia Tools and Applications - Deep learning has made essential contributions to the development of visual object detection and recognition. Identifying fast-moving objects from the viewpoint...     

An ultrahigh-resolution image encryption algorithm using random super-pixel strategy

Multimedia Tools and Applications - Almost all existing image encryption algorithms are only suitable for low-resolution images in the standard image library. When they are used to encrypt...     

Full-scaled deep metric learning for pedestrian re-identification

Multimedia Tools and Applications - The pedestrian re-identification problem (i.e., re-id) is essential and pre-requisite in multi-camera video surveillance studies, provided the fact that...     

An efficient recursive rotational-coordinate-based formulation of a planar Euler–Bernoulli beam

Multibody System Dynamics - A recursive rotational-coordinate-based formulation of a planar Euler–Bernoulli beam is developed, where large displacements, deformations, and rotations are...     

A Performance Evaluation of Classic Convolutional Neural Networks for 2D and 3D Palmprint and Palm Vein Recognition

Palmprint recognition and palm vein recognition are two emerging biometrics technologies. In the past two decades, many traditional methods have been proposed for palmprint recognition and palm vein recognition, and have achieved impressive results. However, the research on deep learning-based palmprint recognition and palm vein recognition is still very preliminary. In this paper, in order to investigate the problem of deep learning based 2D and 3D palmprint recognition and palm vein recognition in-depth, we conduct performance evaluation of seventeen representative and classic convolutional neural networks (CNNs) on one 3D palmprint database, five 2D palmprint databases and two palm vein databases. A lot of experiments have been carried out in the conditions of different network structures, different learning rates, and different numbers of network layers. We have also conducted experiments on both separate data mode and mixed data mode. Experimental results show that these classic CNNs can achieve promising recognition results, and the recognition performance of recently proposed CNNs is better. Particularly, among classic CNNs, one of the recently proposed classic CNNs, i.e., EfficientNet achieves the best recognition accuracy. However, the recognition performance of classic CNNs is still slightly worse than that of some traditional recognition methods.