Massive transformation and absolute stability

Under carefully chosen conditions, solidification theory may be applied to solid-state transformations, and this has been done here for composition-invariant diffusion transformations. The predictions of the modeling are compared with isovelocity experiments in two iron systems, Fe-7.29 wt pct Cr and Fe-3.1 wt pct Ni. The ferrite to austenite phase transformation is used to demonstrate that stabilization of a planar transformation front at absolute stability is the natural lower velocity limit for a composition-invariant (massive) transformation. The results of the model, which includes nonequilibrium effects, clearly show that steady-state plane-front growth leading to composition invariance can be obtained at various temperatures depending on the growth velocity. In the lower velocity range, at the limit of absolute stability (of the order of 10 μm/s in the systems studied), the transformation interface moves under conditions of local equilibrium, and the temperature corresponds to the lower solvus temperature. At higher velocity (of the order of the interface diffusion rate, which in these systems is of the order of cm/s), the transformation is predicted to proceed at temperatures close to T ₀. At even higher rates, atom attachment kinetic undercooling will decrease the transformation temperature with respect to T ₀. In some cases, this temperature might even drop below the lower solvus. This article is based on a presentation made at the symposium entitled “The Mechanisms of the Massive Transformation,” a part of the Fall 2000 TMS Meeting held October 16–19, 2000, in St. Louis, Missouri, under the auspices of the ASM Phase Transformations Committee.     

Preparation and characterization of chitosan‐based dispersions

Complexation of chitosan in aqueous solutions by low molecular weight electrolytes is one of the simplest methods for the preparation of aqueous chitosan dispersions. In this work, the influence of storage time, sulfate concentration, method of preparation and surfactant content on some properties of the resultant chitosan dispersions (turbidity, viscosity and zeta potential) was analyzed. Turbidimetry was adequate to monitor the formation of particles, while viscometry was suitable to monitor changes in the dispersing phase. An analysis of the properties of these systems, mainly in terms of particle–particle and macromolecule–macromolecule interactions was carried out. Copyright © 2004 Society of Chemical Industry     

Self-adjusting the intensity of assortative mating in genetic algorithms

Mate selection plays a crucial role in both natural and artificial systems. While traditional Evolutionary Algorithms (EA) usually engage in random mating strategies, that is, mating chance is independent of genotypic or phenotypic distance between individuals, in natural systems non-random mating is common, which means that somehow this mechanism has been favored during the evolutionary process. In non-random mating, the individuals mate according to their parenthood or likeness. Previous studies indicate that negative assortative mating (AM)—also known as dissortative mating—, which is a specific type of non-random mating, may improve EAs performance by maintaining the genetic diversity of the population at a higher level during the search process. In this paper we present the Variable Dissortative Mating Genetic Algorithm (VDMGA). The algorithm holds a mechanism that varies the GA’s mating restrictions during the run by means of simple rule based on the number of chromosomes created in each generation and indirectly influenced by the genetic diversity of the population. We compare VDMGA not only with traditional Genetic Algorithms (GA) but also with two preceding non-random mating EAs: the CHC algorithm and the negative Assortative Mating Genetic Algorithm (nAMGA). We intend to study the effects of the different methods in the performance of GAs and verify the reliability of the proposed algorithm when facing an heterogeneous set of landscapes. In addition, we include the positive Assortative Mating Genetic Algorithm (pAMGA) in the experiments in order test both negative and positive AM mechanisms, and try to understand if and when negative AM (or DM) speeds up the search process or enables the GAs to escape local optima traps. For these purposes, an extensive set of optimization test problems was chosen to cover a variety of search landscapes with different characteristics. Our results confirm that negative AM is effective in leading EAs out of local optima traps, and show that the proposed VDMGA is at least as efficient as nAMGA when applied to the range of our problems, being more efficient in very hard functions were traditional GAs usually fail to escape local optima. Also, scalability tests have been made that show VDMGA ability to decrease optimal population size, thus reducing the amount of evaluations needed to attain global optima. We like to stress that only two parameters need to be hand-tuned in VDMGA, thus reducing the tuning effort present in traditional GAs and nAMGA.     

Hardware and software architecture for power quality analysis

This paper presents a novel concept for power quality hardware and software architecture. Software tools related to detection, classification and characterization of power quality events can be integrated into a Distribution Control Center in which the interconnection between different subsystems is being carried out through the Internet allowing flexibility to the system. This system is implemented using wavelet analysis applied in all proposed algorithms. Different power quality events are taken as examples to illustrate the capabilities of the proposed method. The obtained results reveal that the proposed architecture is feasible to be implemented as an integral part of a control center system.The proposed system has the property of fast and accurate detection and classification of any power quality disturbance event and introduces a new PQ index determination that allows characterizing any type of disturbance including the non-periodic signals.     

Identification of thermoresistive solar radiation sensors

An identification procedure to estimate the parameters of a thermoresistive solar radiation sensor is presented. The proposed technique employs only electrical excitation for the sensor. The estimation algorithm is recursive and is applied to the sensor model derived from the thermodynamic equilibrium differential equations. The simulation and the experimental results demonstrate the validity of the proposed approach     

Morphological analysis of poly(o-methoxyaniline) thin-films deposited by spin coating technique

Morphological study of conducting polymer thin films obtained by spin coating is reported. Poly(o-methoxyaniline) films were deposited onto glass substrates and analyzed by profilometry and atomic force microscopy (AFM). It is shown that final thickness is correlated by a power law with spin speed with a solution concentration varying coefficient and that surface roughness decreases with increasing spin speed.     

Screening of supports for the immobilization of pectinmethylesterase from acerola (Malpighia glabra L)

A partially purified extract of pectinmethylesterase (PME) from acerola fruit was immobilized on various supports: glass, celite, chrysotile, agarose, concanavalin A Sepharose 4B, egg shell, polyacrylamide and gelatin. In addition, reticulation with glutaraldehyde was assessed, as well as the use of gelatin in the presence of celite, glass and silica. The highest immobilization yields were obtained when the pectinmethylesterase was immobilized in concanavalin A Sepharose 4B (81.7%) and in gelatin‐water (78.0%). Copyright © 2004 Society of Chemical Industry