Evaluation of the performance of α-SiAlON tool when turning Ti-6Al-4V alloy without coolant

Due to their high hardness and wear resistance, Si3N4 based ceramics are one of the most suitable cutting tool materials for machining cast iron, nickel alloys and hardened steels. However, their high degree of brittleness usually leads to inconsistent results and sudden catastrophic failures. This necessitates a process optimization when machining superalloys with Si3N4 based ceramic cutting tools. The tools are expected to withstand the heat and pressure developed when machining at higher cutting conditions because of their high hardness and melting point. This paper evaluates the performance of α-SiAlON tool in turning Ti-6Al-4V alloy at high cutting conditions, up to 250 m min-1, without coolant. Tool wear, failure modes and temperature were monitored to access the performance of the cutting tool. Test results showed that the performance of α-SiAl0N tool, in terms of tool life, at the cutting conditions investigated is relatively poor due probably to rapid notching and excessive chipping of the cutting edge. These facts are associated with adhesion and diffusion wear rate that tends to weaken the bond strength of the cutting tool.

Comparative analysis of strut-and-tie models using Smooth Evolutionary Structural Optimization

The strut-and-tie models are widely used in certain types of structural elements in reinforced concrete and in regions with complexity of the stress state, called regions D, where the distribution of deformations in the cross section is not linear. This paper introduces a numerical technique to determine the strut-and-tie models using a variant of the classical Evolutionary Structural Optimization, which is called Smooth Evolutionary Structural Optimization. The basic idea of this technique is to identify the numerical flow of stresses generated in the structure, setting out in more technical and rational members of strut-and-tie, and to quantify their value for future structural design. This paper presents an index performance based on the evolutionary topology optimization method for automatically generating optimal strut-and-tie models in reinforced concrete structures with stress constraints. In the proposed approach, the element with the lowest Von Mises stress is calculated for element removal, while a performance index is used to monitor the evolutionary optimization process. Thus, a comparative analysis of the strut-and-tie models for beams is proposed with the presentation of examples from the literature that demonstrates the efficiency of this formulation. © 2013 Elsevier Ltd.

Técnicas estendidas na performance e no ensino do contrabaixo acústico no Brasil

Pós-graduação em Música - IA

Global optimization using a genetic algorithm with hierarchically structured population

This paper applies a genetic algorithm with hierarchically structured population to solve unconstrained optimization problems. The population has individuals distributed in several overlapping clusters, each one with a leader and a variable number of support individuals. The hierarchy establishes that leaders must be fitter than its supporters with the topological organization of the clusters following a tree. Computational tests evaluate different population structures, population sizes and crossover operators for better algorithm performance. A set of known benchmark test problems is solved and the results found are compared with those obtained from other methods described in the literature, namely, two genetic algorithms, a simulated annealing, a differential evolution and a particle swarm optimization. The results indicate that the method employed is capable of achieving better performance than the previous approaches in regard as the two criteria usually employed for comparisons: the number of function evaluations and rate of success. The method also has a superior performance if the number of problems solved is taken into account. (C) 2013 Elsevier B.V. All rights reserved.

Thermoplastic polyesters and Co-polyesters derived from vegetable oil: synthesis and optimization of melt polycondensation for medium and long chain poly(omega-hydroxyfatty acid)s and their ester derivatives

The synthesis of a series of omega-hydroxyfatty acid (omega-OHFA) monomers and their methyl ester derivatives (Me-omega-OHFA) from mono-unsaturated fatty acids and alcohols via ozonolysis-reduction/crossmetathesis reactions is described. Melt polycondensation of the monomers yielded thermoplastic poly(omega-hydroxyfatty acid)s [-(CH2)(n)-COO-](x) with medium (n = 8 and 12) and long (n = 17) repeating monomer units. The omega-OHFAs and Me-omega-OHFAs were all obtained in good yield (>= 80%) and purity (>= 97%) as established by H-1 NMR, Fourier Transform infra-red spectroscopy (FT-IR), mass spectroscopy (ESI-MS) and high performance liquid chromatography (HPLC) analyses. The average molecular size (M-n) and distribution (PDI) of the poly(omega-hydroxyfatty acid)s (P(omega-OHFA)s) and poly(omega-hydroxyfatty ester) s (P(Me-omega-OHFA) s) as determined by GPC varied with organo-metallic Ti(IV) isopropoxide [Ti(OiPr)(4)] polycondensation catalyst amount, reaction time and temperature. An optimization of the polymerization process provided P(omega-OHFA) s and P(Me-omega-OHFA) s with M-n and PDI values desirable for high end applications. Co-polymerization of the long chain (n = 12) and medium chain (n = 8) Me-omega-OHFAs by melt polycondensation yielded poly(omega-hydroxy tridecanoate/omega-hydroxy nonanoate) random co-polyesters (M-n = 11000- 18500 g mol(-1)) with varying molar compositions.

Bio-Optical Properties of the Inner Continental Shelf off Santos Estuarine System, Southeastern Brazil, and their Implications for Ocean Color Algorithm Performance

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Development of a comprehensive method for analyzing clerodane-type diterpenes and phenolic compounds from Casearia sylvestris Swartz (Salicaceae) based on ultra high performance liquid chromatography combined with chemometric tools

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Evolutionary optimization applied for fine-tuning parameter estimation in optical flow-based environments

Optical flow methods are accurate algorithms for estimating the displacement and velocity fields of objects in a wide variety of applications, being their performance dependent on the configuration of a set of parameters. Since there is a lack of research that aims to automatically tune such parameters, in this work we have proposed an evolutionary-based framework for such task, thus introducing three techniques for such purpose: Particle Swarm Optimization, Harmony Search and Social-Spider Optimization. The proposed framework has been compared against with the well-known Large Displacement Optical Flow approach, obtaining the best results in three out eight image sequences provided by a public dataset. Additionally, the proposed framework can be used with any other optimization technique.

A preparação para performance musical de quarteto de violões

Pós-graduação em Música - IA