Mechanical and microstructure studies on the modification of CA film by blending with PS

DriedMusa paradiciaca (banana) stem and veins of the leaves, which were hitherto discarded as a waste, were collected and used as starting material for the preparation of cellulose and cellulose acetate. This cellulose acetate was mixed with polystyrene to form blend of cellulose acetate-polystyrene in order to provide enhanced stability and extended utility to the end products. The films of these composites or their individual partners were made separately and studied for their mechanical properties, chemical modification and morphological changes. We report here that banana stem is good source of cellulose and that cellulose completely undergoes modification upon esterification.     

Undercooling and supersaturation of alloying elements in rapidly solidified Al-8.5% Fe-1.2% V-1.7% Si alloy

Dispersion-strengthened Al-8.5% Fe-1.2% V-1.7% Si alloy was produced by inert gas atomization and atomized melt deposition processes. Differential scanning calorimetry was used to estimate the extent of undercooling in the alloy powders as a function of powder size and in the atomized melt-deposited alloy as a function of process parameters. The estimated undercooling was found to be a strong function of powder size and processing conditions and varied from 380–200 °C. Alloy powders of diameter greater than 180 jam did not experience any undercooling during solidification. X-ray diffraction analysis was performed to study the dependence of supersaturation of alloying elements and metastable phase formation on the extent of undercooling. When the undercooled alloy was heated to about 400 dgC, formation of Al₁₂(Fe, V)₃Si phase with b c c crystal structure from the supersaturated matrix was observed.     

Spectrophotometric determination of some antioxidants with potassium permanganate and metol

New spectrophotometric methods for the assay of some antioxidants have been developed using potassium permanganate and metol (p-N-methyl amino phenol). Metol is oxidised at pH 3.0 with potassium permanganate and coupled with antioxidants to give λ_max at 560 nm for propyl gallate and gallic acid and 510nm for butylated hydroxy anisole. The method is simple, sensitive, reproducible and accurate within ±1% and applicable to the assay of antioxidants (gallic acid, propyl gallate and butylated hydroxy anisole) in oils and fats.     

Analysis of interfacial failure in a composite microbundle pull-out experiment

Modeling of the failure of polymer-matrix composites requires substantial information about the mechanisms of failure at the interface, and load redistribution around fiber breaks in the composite. Current interface experiments involving the use of ‘microcomposites’ of single embedded fibers in a matrix generally do not include all the key geometric features of the real composite; in particular, they do not include the effects of fiber volume fraction and the higher matrix shear resulting from closely neighboring fibers. A new experiment was recently devised to assess some of these effects: it is referred to as the single-fiber pull-out from microbundle (SFPOM) experiment. It consists of a hexagonal arrat of seven fibers in a matrix where the outer six fibers are restrained and the center fiber is pulled out. Recent experimental data from tests with this geometry are analyzed here using three mechanical models of the failure process, and parametric studies of the data are performed to assess the appropriateness of each model. Two of the models, based on fracture energy considerations as applied earlier to single embedded fibers in a matrix and adapted to our geometry, were found to model data from the SFPOM experiments poorly. The third model assumes the existence of three zones near a fiber break, including elastic, plastic and frictional debond zones, and was found to provide reasonable fit to the data under realistic assumptions.     

Thermophysical Properties of Binary Mixtures of Methyl Methacrylate+Di-Ethers (Ethyl, Isopropyl, and Butyl) at 298.15 and 308.15 K

Experimental data for the densities, dynamic viscosities, sound speeds, and relative permittivities and for three binary systems of methyl methacrylate (MMA)+di-ethers (ethyl, isopropyl, and butyl) at 298.15 and 308.15 K and at atmospheric pressure are reported. The mixture viscosities are correlated by Grunberg–Nissan, McAllister, and Auslander equations over the complete composition range. The sound speeds for the mixtures are also calculated by using free length and collision factor theories, and Nomoto and Junjie equations. From the measured primary properties, deviation functions such as deviations in viscosities, sound speeds, relative permittivities, molar polarizations, excess isentropic compressibilities, and molar electrical susceptibilities were calculated, and the compositional dependence of each of the functions was expressed with a Redlich–Kister type equation. The variation of the Kirkwood correlation factor was determined over the complete composition range.     

Foundations of data fusion for automation

This article discusses about the developing paradigms of data for sensor-actuator networks that perform engineering tasks. We provide a new foundation for data fusion based on two concepts: a conceptual framework and the goal-seeking paradigm. The conceptual framework emphasizes the dominant structures in the system. The goal-seeking paradigm is a mechanism for representing system evolution that explicitly manages uncertainty. The goal-seeking formulation for data fusion helps to distinguish between subjective decisions that can be executed by computers. These notions are useful for critical tasks, such as security management in large-scale distributed systems. Investigations in this area, and further refinement of the goal-seeking formulation for instrumentation and measurement applications, are likely to future systems that facilitate holistic user decision making.     

Using previous models to bias structural learning in the hierarchical BOA

Estimation of distribution algorithms (EDAs) are stochastic optimization techniques that explore the space of potential solutions by building and sampling explicit probabilistic models of promising candidate solutions. While the primary goal of applying EDAs is to discover the global optimum or at least its accurate approximation, besides this, any EDA provides us with a sequence of probabilistic models, which in most cases hold a great deal of information about the problem. Although using problem-specific knowledge has been shown to significantly improve performance of EDAs and other evolutionary algorithms, this readily available source of problem-specific information has been practically ignored by the EDA community. This paper takes the first step toward the use of probabilistic models obtained by EDAs to speed up the solution of similar problems in the future. More specifically, we propose two approaches to biasing model building in the hierarchical Bayesian optimization algorithm (hBOA) based on knowledge automatically learned from previous hBOA runs on similar problems. We show that the proposed methods lead to substantial speedups and argue that the methods should work well in other applications that require solving a large number of problems with similar structure.