Impact of adhesive ingredients on adhesion between rubber and brass-plated steel wire in tire

Proficiency on underlying mechanism of rubber-metal adhesion has been increased significantly in the last few decades. Researchers have investigated the effect of various ingredients, such as hexamethoxymethyl melamine, resorcinol, cobalt stearate, and silica, on rubber-metal interface. The role of each ingredient on rubber-metal interfacial adhesion is still a subject of scrutiny. In this article, a typical belt skim compound of truck radial tire is selected and the effect of each adhesive ingredient on adhesion strength is explored. Out of these ingredients, the effect of cobalt stearate is found noteworthy. It has improved adhesion strength by 12% (without aging) and by 11% (humid-aged), respectively, over control compound. For detailed understanding of the effect of cobalt stearate on adhesion, scanning electron microscopy and energy dispersive spectroscopy are utilized to ascertain the rubber coverage and distribution of elements. X-ray photoelectron spectroscopy results helped us to understand the impact of Cu_XS layer depth on rubber-metal adhesion. The depth profile of the Cu_XS layer was found to be one of the dominant factors of rubber-metal adhesion retention. Thus, this study has made an attempt to find the impact of different adhesive ingredients on the formation of Cu_XS layer depth at rubber-metal interface and establish a correlation with adhesion strength simultaneously.     

Training and optimization of an artificial neural network controlling a hybrid power filter

A hybrid power compensator (HPC) consisting of a static VAr compensator and a dynamic compensator needs to be optimally controlled during the compensation of nonlinear loads. The HPC must be controlled to meet minimum requirements in terms of power factor and harmonic distortion, while at the same time minimizing its total cost. An artificial neural network (ANN) is used to control the HPC amidst a very dynamic power system environment. The performance of a reference ANN is evaluated while controlling an HPC connected to a typical nonlinear industrial load. The training and performance of the ANN is then optimized in terms of training set size, training set packing and ANN topology and the performance compared to the reference ANN. This paper highlights the importance of optimising the mentioned ANN parameters to achieve optimum ANN training and modeling accuracy. The results obtained reveals that the application of an ANN in controlling an HPC is feasible given that the ANN parameters are chosen appropriately.     

Changes in Volatile Components of Stored Tangerines and Other Specialty Citrus Fruits with Different Coatings

ABSTRACT: Shellac and wax-based citrus coatings were applied to Fallglo, Robinson, Sunburst, Dancy and Murcott tangerines, Nova and Orlando tangelos, and Temple oranges. Flavor volatiles were measured before and after storage. Concentrations of ethyl acetate, ethyl butyrate, isopentanol and 2-methyl-3-buten-2-ol increased markedly for fruit with shellac-based coatings, and were highly correlated with ethanol content, but at different ratios for the different varieties. The concentration increases were relatively less for fruit coated with the wax-based coatings, and suggest that high-gloss shellac and resin-based coatings are not appropriate for tangerines.     

台北101层国际金融中心之结构施工技术与其设计考量概述

本文旨在简要说明目前正在施工中之超高层大楼—台北国际金融中心之结构系统、钢结构工程、钢筋混凝土工程基础与深开挖工程等特殊施工技术,并佐以相关之设计考量与施工规划概要,以供工程界做参考。     

The function of bleaching earths in the processing of palm,palm kernel and coconut oils

The results presented in the literature, which attempt to elucidate the mechanisms by which triglyceride oils are bleached by earths, are reviewed. The impact of this work and how the mechanistic proposals affect changes in oil properties are considered, with particular emphasis on the needs of the palm oil processor. Important properties include color, metals and phosphorus content and oxidative stability of the oil. Investigations made in our own laboratories have been aimed at elucidating the effect of varying physical and chemical properties of the bleaching earth on the quality of bleached and deodorized oils. Techniques used in this work are pore-size distribution, surface area, scanning and transmission electron microscopy and a variety of chemical and X-ray analysis methods. The ability to vary such parameters in montmorillonite clays by alteration of process conditions to give materials with specific performance characteristics is demonstrated. Comparisons are made between acid-activated montmorillonites and other clay types.     

Lean philosophy: implementation in a forging company

This research addresses the implementation of lean philosophy in a forging company with a focus on radial forging production flow lines. Here, the prime motive is to evolve and test several strategies to eliminate waste on the shop floor. In this research, a systematic approach is suggested for the implementation of lean principles. This paper describes an application of value stream mapping (VSM). Consequently, the present and future states of value stream maps are constructed to improve the production process by identifying waste and its sources. Furthermore, Taguchi’s method of design of experiments is pursued here to minimize the forging defects produced due to imperfect operating conditions. A noticeable reduction in set-up time and work-in-process (WIP) inventory level is substantiated. Finally, we conclude with a discussion of managerial implications and the future scope of research.     

The Design of Discrimination Experiments

Experimentation plays a fundamental role in scientific discovery. Scientists experiment to gather data, investigate phenomena, measure quantities, and test theories. In this article, we address the problem of designing experiments to discriminate between two completing theories. Given an initial situation for which the two theories make the same prediction, the experiment design problem is to determine how to modify the situation such that the two theories make different predictions for the modified situation. The modified situation is called a discrimination experiment. We present a knowledge-intensive method called DEED for designing discrimination experiments. The method analyzes the differences in the two theories' explanations of the prediction for the initial situation. Based on this analysis, it determines modifications to the initial situation that will result in a discrimination experiment. We illustrate the method with the design of experiments to discriminate between several pairs of qualitative theories in the fluids domain.