An annular die has been designed having a very thin gap distance between two coaxial cylinders. The die was then used to measure wall normal stresses along the longitudinal direction of polymer melts flowing through the thin annulus. The materials investigated were high-density polyethylene, low-density polyethylene, polypropylene, and polystyrene. Also investigated were blends of polystyrene and polypropylene, and blends of polystyrene and high-density polyethylene The measurements of wall normal stresses were used to determine the rheological properties of the melts, namely, the melt viscosity from the slope of axial wall normal stress profiles and the melt elasticity from exit pressures. The interpretation of the experimental data was made possible by the fact that the narrow-gap annular die can be considered as a substitute for a thin slit die. It has been found that the results obtained in the present study are consistent with those reported earlier by the author, who at that time used both capillary and slit dies. 相似文献
Collaboration representation-based classification (CRC) was proposed as an alternative approach to the sparse representation method with similar efficiency. The CRC is essentially a competition scheme for the training samples to compete with each other in representing the test sample, and the training class with the minimum representation residual from the test sample wins the competition in the classification. However, the representation error is usually calculated based on the Euclidean distance between a test sample and the weighted sum of all the same-class samples. This paper exploits alternative methods of calculating the representation error in the CRC methods to reduce the representation residual in a more optimal way, so that the sample classes compete with each other in a closer range to represent the test sample. A large number of face recognition experiments on three face image databases show that the CRC methods with optimized presentation residual achieve better performance than the original CRC, and the maximum improvement in classification accuracy is up to 12 %. 相似文献
The viscosities of mixtures of low-density polyethylene and fluorocarbon blowing agent were determined from the measurement of wall normal stress along the longitudinal axis of a capillary die. For the study, three different grades of commercial high-pressure low-density polyethylene were used, together with the following fluorocarbon blowing agents, dichlorodifluoromethane (FC-12), dichlorotetrafluoroethane (FC-114), and blends of FC-12 and FC-114. In the experiment, blowing agent concentration and melt temperature were varied for each combination of polymer and blowing agent employed. Analysis of the experimental data has led to a correlation between the viscosity reduction factor (VRF) and the blowing agent concentration, in which VRF is defined as the ratio of the viscosity of polymer-blowing agent mixture to that of the polymer alone. It was found that the correlation obtained is independent of shear rate and temperature and dependent upon only the type of fluorocarbon blowing agent. The practical significance of the correlation is discussed. We have shown that the entrance pressure drop obtained in the absence of phase separation in the entrance region may be used as a measure of the elastic properties of mixtures of fluorocarbon blowing agent and low-density polyethylene resin. 相似文献
Group decision making is a multi-criteria decision-making method applied in many fields. However, the use of group decision-making techniques in multi-class classification problems and rule generation is not explored widely. This investigation developed a group decision classifier with particle swarm optimization (PSO) and decision tree (GDCPSODT) for analyzing students’ mathematic and scientific achievements, which is a multi-class classification problem involving rule generation. The PSO technique is employed to determine weights of condition attributes; the decision tree is used to generate rules. To demonstrate the performance of the developed GDCPSODT model, other classifiers such as the Bayesian classifier, the k-nearest neighbor (KNN) classifier, the back propagation neural networks classifier with particle swarm optimization (BPNNPSO) and the radial basis function neural networks classifier with PSO (RBFNNPSO) are used to cope with the same data. Experimental results indicated the testing accuracy of GDCPSODT is higher than the other four classifiers. Furthermore, rules and some improvement directions of academic achievements are provided by the GDCPSODT model. Therefore, the GDCPSODT model is a feasible and promising alternative for analyzing student-related mathematic and scientific achievement data. 相似文献
Summary: Compacted fiber composites offer unique properties due to their lack of an extraneous matrix. The conditions of processing ultra‐high molecular weight polyethylene (UHMWPE) fibers were simulated in a heated pressure cell. In situ X‐ray diffraction measurements were used to follow the relevant transitions and the changes in the degree of crystallinity during melting and crystallization. The results strongly support the suggestion that the hexagonal crystal phase, in which the chain conformation is extremely mobile on the segmental level, constitutes the physical basis of compaction technologies for processing UHMWPE fibers into a single‐polymer composite. This report suggests that using a pseudo‐phase diagram outlining the occurrence of different phases during slow heating and the degree of crystallinity can provide valuable insight into the technological parameters relevant for optimal processing conditions.
Degree of crystallinity as a function of pressure and temperature in a region relevant to compaction processes. 相似文献