Scanning Electron Microscopy Studies on Tear and Wear Failure of Short Kevlar Fiber-Thermoplastic- Polyurethane Composite

Tear and wear properties of short kevlar fiber, thermoplastic polcurethane (TPU) composite with respect to fiber loading-and fiber onentation has been studied and the fracture surfaces were examined under scanning electron microscope (SEM). Tear strength first decreased up to 20 phr fiber loading and then gradually increased with increasing fiber loading. Anisotropy in tear strength was evident beyond a fiber loading of 20 phr. Tear fracture surface of unfilled TPU showed sinusoidal folding characteristics of high strength matrix. At low fiber loading the tear failure was mainly due to fibermatrix failure whereas at higher fiber loading the failure occurred by fiber breakage. Abrasion loss shows a continuous rise with increasing fiber loading, the loss in the transverse orientation of fibers being higher than that in the longitudinal orientation. The abraded surface showed lone cracks and ridges parallel to the direction of abrasion indicating an abrasive wear mechanism. In the presence of fber the abrasion loss was mainly due to fiber low.

Cure Characteristics and Mechanical Properties of Short Nylon Fiber Reinforced Acrylonitrile Butadiene Rubber/Reclaimed Rubber Blends

Cure characteristics and mechanical properties of short nylon fiber reinforced acrylonitrile butadiene rubber-reclaimed rubber composites were studied. Minimum torque, (maximum-minimum) torque and cure rate increased with fiber concentration. Scorch time and cure time decreased by the addition of fibers. Properties like tensile strength, tear strength, elongation at break, abrasion loss and heat build up were studied in both orientations of fibers. Tensile and tear properties were enhanced by the addition of fibers and were higher in the longitudinal direction. Heat build up increased with fiber concentration and were higher in the longitudinal direction. Abrasion resistance was improved in presence of short fibers and was higher in the longitudinal direction. Resilience increased on the introduction of fibers. Compression set was higher for blends.

Effect of Urethane Based Bonding Agent on the Cure Characteristics and Mechanical Properties of Styrene Butadiene Rubber - Whole Tyre Reclaim - Short Nylon Fiber Composite

The cure characteristics and mechanical properties of short nylon fiber- styrene /whole tyre reclaim (SBR/WTR) composites with and without an interfacial bonding agent based on 4,4 diphenyl methane diisocyanate and polyethylene glycol (MDI/PEG) have been studied. An 80:40 blend of SBR/ WTR reinforced with 20 phr of short nylon fiber has been selected and the MDI/ PEG ratio has been changed from 0.67:1 to 2:1. The minimum and maximum torques increased with isocyanate concentration. The scorch time and cure time showed an initial reduction. The cure rate showed an initial improvement. Tensile strength, tear strength and abrasion resistance increased with MDI/PEG ratio, these values were higher in longitudinal direction. Resilience and compression set increased with isocyanate concentration.

Studies on Acrylonitrile Butadiene Rubber - Short Nylon Fiber Composites

Acrylonitrile butadiene rubber (NBR) matrix was reinforced with different levels of short nylon fiber loading. Cure characteristics and mechanical properties of composites in longitudinal and transverse directions have been studied. Cure time was reduced while processability, as indicated by the minimum torque, was marginally reduced with increase in fiber loading. Tensile and tear properties improved with fiber concentration and the values were higher in longitudinal direction of fiber orientation. Abrasion resistance, resilience and compression set were increased in presence of fibers. Elongation at break values showed a drastic drop on introduction of fibers. Heat build up was higher for composites.

A Novel Decision Tree Algorithm for Numeric Datasets - C 4.5*Stat

Decision trees are very powerful tools for classification in data mining tasks that involves different types of attributes. When coming to handling numeric data sets, usually they are converted first to categorical types and then classified using information gain concepts. Information gain is a very popular and useful concept which tells you, whether any benefit occurs after splitting with a given attribute as far as information content is concerned. But this process is computationally intensive for large data sets. Also popular decision tree algorithms like ID3 cannot handle numeric data sets. This paper proposes statistical variance as an alternative to information gain as well as statistical mean to split attributes in completely numerical data sets. The new algorithm has been proved to be competent with respect to its information gain counterpart C4.5 and competent with many existing decision tree algorithms against the standard UCI benchmarking datasets using the ANOVA test in statistics. The specific advantages of this proposed new algorithm are that it avoids the computational overhead of information gain computation for large data sets with many attributes, as well as it avoids the conversion to categorical data from huge numeric data sets which also is a time consuming task. So as a summary, huge numeric datasets can be directly submitted to this algorithm without any attribute mappings or information gain computations. It also blends the two closely related fields statistics and data mining