Optimization of the mechanical properties of low-carbon steels by formation of a multiphase microstructure

In this work five methods of heat treatments are investigated in order to obtained convenient volume fractions of ferrite, bainite, martensite and retained austenite, starting with a low carbon steel and seeking the distinction of the phases, through optical microscopy. Specific chemical etching is improved. The results in tensile and fatigue tests were accomplished and the results were related with the microstructural parameters. The results show that the mechanical properties are closely related with the phases, grains size and the phases morphology. Copyright © 2001 Society of Automotive Engineers, Inc.

Tuning of fuzzy inference systems through unconstrained optimization techniques

This paper presents a new methodology for the adjustment of fuzzy inference systems. A novel approach, which uses unconstrained optimization techniques, is developed in order to adjust the free parameters of the fuzzy inference system, such as its intrinsic parameters of the membership function and the weights of the inference rules. This methodology is interesting, not only for the results presented and obtained through computer simulations, but also for its generality concerning to the kind of fuzzy inference system used. Therefore, this methodology is expandable either to the Mandani architecture or also to that suggested by Takagi-Sugeno. The validation of the presented methodology is accomplished through an estimation of time series. More specifically, the Mackey-Glass chaotic time series estimation is used for the validation of the proposed methodology.

Optimization of xylanase biosynthesis by Aspergillus japonicus isolated from a Caatinga area in the Brazilian state of Bahia

The objective of this research was to investigate the potential of xylanase production by Aspergillus japonicus and to determine the effects of cultivation conditions in the process, aiming toward optimization of enzyme production. The best temperature, as well as the best carbon source, for biomass production was determined through an automated turbidimetric method (Bioscreen-C). The enzyme activity of this fungus was separately evaluated in two solid substrates (wheat and soybean bran) and in Vogel medium, adding other carbon sources. Temperature effects, cultivation time, and spore concentrations were also tested. The best temperature for enzyme and biomass production was 25°C; however, the best carbon source for growth (determined by the Bioscreen C) did not turn out to be a good inducer of xylanase production. Maximum xylanase activity was achieved when the fungus was cultivated in wheat bran (without the addition of any other carbon source) using a spore concentration of 1 × 107 spores/mL (25°C, pH 5.0, 120 h). A. japonicus is a good xylanase producer under the conditions presented in these assays. © 2006 Academic Journals.

Applying a genetic neuro-model reference adaptive controller in drilling optimization

Motivated by rising drilling operation costs, the oil industry has shown a trend toward real-time measurements and control. In this scenario, drilling control becomes a challenging problem for the industry, especially due to the difficulty associated with parameters modeling. One of the drillbit performance evaluators, the Rate Of Penetration (ROP), has been used as a drilling control parameter. However, relationships between operational variables affecting the ROP are complex and not easily modeled. This work presents a neuro-genetic adaptive controller to treat this problem. It is based on an auto-regressive with extra input signals, or ARX model and on a Genetic Algorithm (GA) to control the ROP. © [2006] IEEE.

Efficient parametric adjustment of fuzzy inference system using unconstrained optimization

This paper presents a new methodology for the adjustment of fuzzy inference systems, which uses technique based on error back-propagation method. The free parameters of the fuzzy inference system, such as its intrinsic parameters of the membership function and the weights of the inference rules, are automatically adjusted. This methodology is interesting, not only for the results presented and obtained through computer simulations, but also for its generality concerning to the kind of fuzzy inference system used. Therefore, this methodology is expandable either to the Mandani architecture or also to that suggested by Takagi-Sugeno. The validation of the presented methodology is accomplished through estimation of time series and by a mathematical modeling problem. More specifically, the Mackey-Glass chaotic time series is used for the validation of the proposed methodology. © Springer-Verlag Berlin Heidelberg 2007.

Optimization of a novel nitric oxide sensor using a latex rubber matrix

This study present a novel NO sensor made of a spin trap (iron(II)-diethyldithiocarbamate complex, FeDETC) incorporated in a latex rubber matrix and works as a trap for NO, which is detectable by Electron Paramagnetic Resonance (EPR). We explored the optimization of our sensors changing systematically two fabrication parameters: the latex rubber matrix temperature of polymerization and FeDETC concentration inside the matrix. The sensor was prepared in four different temperatures: 4, 10, 20 and 40°C. The FeDETC concentration was also varied from 0.975 to 14.8 mM. We observed a variation of the EPR signals from the sensors prepared at different conditions. We found a high stability of the EPR response from our sensor, 40 days at RT. The best sensor was made with a latex rubber matrix polymerized at 10°C and with a FeDETC concentration of 14.8 mM. In vivo tests show good biocompatibility of our sensor. © 2007 Asian Network for Scientific Information.

Optimization of a synbiotic formulation of soy yoghurt containing yacon extract by response surface methodology

A synbiotic yoghurt based on a combination of soymilk and yacon water extract (from yacon root tubers) was developed as a novel food product fermented with a probiotic culture of Enterococcus faecium CRL 183 and Lactobacillus helveticus ssp jugurti 4l6. Response surface methodology (RSM) was used to optimize the independent variables soymilk protein concentration and percentage of yacon extract in the formulation through a Central Composite Rotatable Design (CCRD), consisting of a 22 factorial design with two levels (-1, +1), two central points (0) and four axial points (± a, 0) (0, ± α). The responses were assessed by consumer acceptance tests. The optimization indicated that a formulation with a soymilk protein concentration of 1.74g/L and 25.86% of yacon extract gave the best average values, 5.91 for the taste and 6.00 for the overall impression responses. The formulation with 40% of yacon extract and the same concentration of soymilk protein achieved similar acceptance values: taste (5.94) and overall impression (5.87), however, with the extra yacon, it probably had a greater content of prebiotic fructooligosaccharides. Consequently, both formulations may give useful functional foods, with sensory properties comparable with those of soy yoghurt (control formulation). Copyright © 2010 by New Century Health Publishers.

Optimization of the surimi production from Mechanically Recovered Fish Meat (MRFM) using response surface methodology

The by-products generated from industrial filleting of tilapia surimi can be used for the manufacture of surimi. The surimi production uses large amounts of water, which generates a wastewater rich in organic compounds (lipids, soluble proteins and blood). Optimizing the number of washing cycles will contribute to a more sustainable production. A mathematical model of mechanically recovered tilapia meat (Oreochromis niloticus) for the processing of surimi (minced fish washing cycles and tapioca starch addition) based on two quality parameters (texture and moisture) was constructed by applying the response surface methodology (RSM). Each factor had an important effect on the moisture and texture of surimi. This study found that the optimal formulation for producing the best surimi using the by-products of tilapia filleting in manufacturing fish burger were the addition of 10% tapioca starch and three minced fish washing cycles. A microstructural evaluation supported the findings of the mathematical model. Practical Applications: The use of mechanically recovered fish meat (MRFM) for the production of surimi enables the utilization of the by-products of filleting fish. However, the inferior quality of the surimi produced from MRFM in relation to that produced with fillets necessitates the addition of starch; secondly, surimi production consumes a large volume of water. RSM provides a valuable means for optimizing the number of washing cycles and starch amounts utilized in fish burger production. Tapioca starch, widely produced in Brazil, has desirable characteristics (surface sheen, smooth texture, neutral taste and clarity in solution) for use in MRFM-produced surimi. © 2013 Wiley Periodicals, Inc.

UV filters in water samples: Experimental design on the SPE optimization followed by GC-MS/MS analysis

Esse estudo descreve o desenvolvimento e otimização de um método de extração em fase solida (SPE) para análise dos filtros ultravioletas (UV): benzofenona-3 (BP-3), etilhexil salicilato (ES), etilhexil metoxinamato (EHMC) e octocrileno (OC) em matrizes ambientais. Um planejamento fatorial fracionário (PFF) 25-1 foi empregado na avaliação das variáveis significativas do método de extração. As condições experimentais otimizadas da avaliação estatística foram: capacidade do cartucho de 500 mL, eluente acetato de etila, metanol como solvente de lavagem (10% em água, v/v) and volume do eluente de 3 × 2 mL e pH 3. Os parâmetros analíticos avaliados foram satisfatõrios, apresentando linearidade de 100 a 4000 ng L -1, recuperaç ões para os quatro níveis de fortificação (Limite de Quantificação do Método, 200, 1000 e 2000 ng L-1) entre 62 e 107% com desvio padrão relativo menor que 14%. Os limites de quantificação foram encontrados na faixa de ng L-1, variando entre 10 e 100 ng L-1. O método proposto foi aplicado para a determinação dos quatro filtros UV em amostras de águas naturais. This study describes the development and optimization of a solid-phase extraction (SPE) method for analysis of ultraviolet (UV) filters, benzophenone-3 (BP-3), ethylhexyl methoxycinnamate (EHMC), ethylhexyl salicylate (ES) and octocrylene (OC), in environmental matrices. A 25-1 fractional factorial design (FFD) was used to evaluate the significant variables for the extraction method. The optimized experimental conditions determined from the statistical evaluation were: breakthrough volume of 500 mL, eluent of ethyl acetate, wash solvent of methanol (10% in water, v/v), eluent volume of 3 × 2 mL and pH 3. The evaluated analytical parameters were satisfactory for the analytes and showed linearity between 100 and 4000 ng L-1, recoveries for four fortification levels (Method Quantification Limit, 200, 1000 and 2000 ng L-1) were between 62 and 107% with relative standard deviations less than 14%. Limits of quantification were in the ng L-1 range and were between 10 and 100 ng L-1. The proposed method was used to analyze four UV filters in natural water samples. ©2013 Sociedade Brasileira de Química.

Chemometric optimization of solid-liquid extraction with low-temperature partition (SLE-LTP) for determination of persistent organic pollutants in Caiman yacare eggs

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Harmony Search applied for Support Vector Machines Training Optimization

Since the beginning, some pattern recognition techniques have faced the problem of high computational burden for dataset learning. Among the most widely used techniques, we may highlight Support Vector Machines (SVM), which have obtained very promising results for data classification. However, this classifier requires an expensive training phase, which is dominated by a parameter optimization that aims to make SVM less prone to errors over the training set. In this paper, we model the problem of finding such parameters as a metaheuristic-based optimization task, which is performed through Harmony Search (HS) and some of its variants. The experimental results have showen the robustness of HS-based approaches for such task in comparison against with an exhaustive (grid) search, and also a Particle Swarm Optimization-based implementation.

Sucrose utilization by Zymomonas mobilis: Levan production optimization using submerged fermentation

Levan is an extracellular polysaccharide (EPS), constituted by linked fructose units β (2,6), obtained by transfructosilation reaction during fermentation of microorganisms in a sucrose rich culture medium. The bacterial levan production is a good alternative of fructose source, besides having certain functional characteristics in the human body, such as a hypocholesterolemic and an anticarcinogenic agent. In the food industry, the levan can be used to fix colors and flavors, as well as to thickening and stabilizing agent in foods. This work aimed to analyze the kinetic parameters for levan production by Zymomonas mobilis CCT 4494, using submerged fermentation. The response surface methodology (RSM), was utilized to predict the optimization of medium for exopolymer production and the independent variables studied were: initial pH, incubation temperature, sucrose, KCl, K2SO4, MgSO4 and CaCl2. It was observed that the bacterium Z. mobilis CCT 4494 well adapted in medium containing high concentrations of sucrose.

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.

Quality and dose optimization in hand computed radiography

The objective of the present study was to optimize a radiographic technique for hand examinations using a computed radiography (CR) system and demonstrate the potential for dose reductions compared with clinically established technique. An exposure index was generated from the optimized technique to guide operators when imaging hands. Homogeneous and anthropomorphic phantoms that simulated a patient's hand were imaged using a CR system at various tube voltages and current settings (40-55 kVp, 1.25-2.8 mAs), including those used in clinical routines (50 kVp, 2.0 mAs) to obtain an optimized chart. The homogeneous phantom was used to assess objective parameters that are associated with image quality, including the signal difference-to-noise ratio (SdNR), which is used to define a figure of merit (FOM) in the optimization process. The anthropomorphic phantom was used to subjectively evaluate image quality using Visual Grading Analysis (VGA) that was performed by three experienced radiologists. The technique that had the best VGA score and highest FOM was considered the gold standard (GS) in the present study. Image quality, dose and the exposure index that are currently used in the clinical routine for hand examinations in our institution were compared with the GS technique. The effective dose reduction was 67.0%. Good image quality was obtained for both techniques, although the exposure indices were 1.60 and 2.39 for the GS and clinical routine, respectively.

Net power optimization of an irreversible Otto cycle using ECOP and ecological function

This paper presents an analysis of an irreversible Otto cycle aiming to optimize the net power through ECOP and ecological function. The studied cycle operates between two thermal reservoirs of infinite thermal capacity, with internal irreversibilities derived from non-isentropic behavior of compression and expansion processes, irreversibilities from thermal resistance in heat exchangers and heat leakage from the high temperature reservoir to the low temperature reservoir. Analytical expressions are applied for the power outputs optimized by the ECOP, by the ecological function and by the maximum power criteria, in conjunction with a graphic analysis, in which some cycle operation parameters are analyzed for an increased comprehension of the effects of the irreversibilities in the optimized power.