Optimal design of smart structures using bonded piezoelectrics for vibration control

Smart material technology has become an area of increasing interest for the development of lighter and stronger structures which are able to incorporate actuator and sensor capabilities for collocated control. In the design of actively controlled structures, the determination of the actuator locations and the controller gains, is a very important issue. For that purpose, smart material modelling, modal analysis methods, control and optimization techniques are the most important ingredients to be taken into account. The optimization problem to be solved in this context presents two interdependent aspects. The first one is related to the discrete optimal actuator location selection problem, which is solved in this paper using genetic algorithms. The second is represented by a continuous variable optimization problem, through which the control gains are determined using classical techniques. A cantilever Euler-Bernoulli beam is used to illustrate the presented methodology.

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.

Multi-choice mixed integer goal programming optimization for real problems in a sugar and ethanol milling company

Goal Programming (GP) is an important analytical approach devised to solve many realworld problems. The first GP model is known as Weighted Goal Programming (WGP). However, Multi-Choice Aspirations Level (MCAL) problems cannot be solved by current GP techniques. In this paper, we propose a Multi-Choice Mixed Integer Goal Programming model (MCMI-GP) for the aggregate production planning of a Brazilian sugar and ethanol milling company. The MC-MIGP model was based on traditional selection and process methods for the design of lots, representing the production system of sugar, alcohol, molasses and derivatives. The research covers decisions on the agricultural and cutting stages, sugarcane loading and transportation by suppliers and, especially, energy cogeneration decisions; that is, the choice of production process, including storage stages and distribution. The MCMIGP allows decision-makers to set multiple aspiration levels for their problems in which the more/higher, the better and the less/lower, the better in the aspiration levels are addressed. An application of the proposed model for real problems in a Brazilian sugar and ethanol mill was conducted; producing interesting results that are herein reported and commented upon. Also, it was made a comparison between MCMI GP and WGP models using these real cases. © 2013 Elsevier Inc.

Lipase production by Botryosphaeria ribis EC-01 on soybean and castorbean meals: Optimization, immobilization, and application for biodiesel production

The effects of soybean and castorbean meals were evaluated separately, and in combinations at different ratios, as substrates for lipase production by Botryosphaeria ribis EC-01 in submerged fermentation using only distilled water. The addition of glycerol analytical grade (AG) and glycerol crude (CG) to soybean and castorbean meals separately and in combination, were also examined for lipase production. Glycerol-AG increased enzyme production, whereas glycerol-CG decreased it. A 24 factorial design was developed to determine the best concentrations of soybean meal, castorbean meal, glycerol-AG, and KH2PO4 to optimize lipase production by B. ribis EC-01. Soybean meal and glycerol-AG had a significant effect on lipase production, whereas castorbean meal did not. A second treatment (22 factorial design central composite) was developed, and optimal lipase production (4,820 U/g of dry solids content (ds)) was obtained when B. ribis EC-01 was grown on 0.5 % (w/v) soybean meal and 5.2 % (v/v) glycerol in distilled water, which was in agreement with the predicted value (4,892 U/g ds) calculated by the model. The unitary cost of lipase production determined under the optimized conditions developed ranged from US$0.42 to 0.44 based on nutrient costs. The fungal lipase was immobilized onto Celite and showed high thermal stability and was used for transesterification of soybean oil in methanol (1:3) resulting in 36 % of fatty acyl alkyl ester content. The apparent K m and V max were determined and were 1.86 mM and 14.29 μmol min -1 mg-1, respectively. © 2013 Springer Science+Business Media New York.

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.

GAIA - Uma proposta de agente inteligente acoplado a algoritmos evolucionários para ajuste dinâmico de parâmetros através de conceitos de design inteligente e lógica fuzzy

Há muitos anos, técnicas de Computação Evolucionária vem sendo aplicadas com sucesso na solução dos mais variados tipos de problemas de otimização. Na constante procura pelo ótimo global e por uma melhor exploração da superfície de busca, as escolhas para ajustar estes métodos podem ser exponencialmente complexas e requerem uma grande quantidade de intervenção humana. Estes modelos tradicionais darwinianos apóiam-se fortemente em aleatoriedade e escolhas heurísticas que se mantém fixas durante toda a execução, sem que acompanhem a variabilidade dos indivíduos e as eventuais mudanças necessárias. Dadas estas questões, o trabalho introduz a combinação de aspectos da Teoria do Design Inteligente a uma abordagem hibrida de algoritmo evolucionário, através da implementação de um agente inteligente o qual, utilizando lógica fuzzy, monitora e controla dinamicamente a população e seis parâmetros definidos de uma dada execução, ajustando-os para cada situação encontrada durante a busca. Na avaliação das proposições foi construído um protótipo sobre a implementação de um algoritmo genético para o problema do caixeiro viajante simétrico aplicado ao cenário de distância por estradas entre as capitais brasileiras, o que permitiu realizar 580 testes, simulações e comparações entre diferentes configurações apresentadas e resultados de outras técnicas. A intervenção inteligente entrega resultados que, com sucesso em muitos aspectos, superam as implementações tradicionais e abrem um vasto espaço para novas pesquisas e estudos nos aqui chamados: “Algoritmos Evolucionários Híbridos Auto-Adaptáveis”, ou mesmo, “Algoritmos Evolucionários Não-Darwinianos”.

Optimization of annatto (Bixa orellana L.) drying in fixed bed

ABSTRACT: The drying of annatto seeds (Bixa orellana L.), red piave cultivate, was studied in a fixed bed dryer. The best conditions were estimated to minimize the loss of coloring and to obtain final moisture of the seeds in appropriate levels to its conservation and maintenance of quality. The quantification of the influence of entrance variables in the final contents of bixin and moisture seeds and the identification of the optimal point was performed through the techniques of factorial design, response surfaces methodology, canonical analysis and desirability function. It was verified that the final moisture of the seeds may be estimated by a second-order polynomial model and that the final content of bixin is only significantly influenced by the time of drying being described properly by a linear model, for the seeds used in this study.

Design sistêmico e ecoinovação em APLs: o método F.L.O.R.A como estratégia sustentável aplicada para o polo de confecções de Pernambuco

Pós-graduação em Design - FAAC

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)

Characterization and optimization of levan production by Bacillus subtilis NATTO

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Optimization of Antitrypanosomatid Agents: Identification of Nonmutagenic Drug Candidates with in Vivo Activity

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Discovering promising regions to help global numerical optimization algorithms

We have developed an algorithm using a Design of Experiments technique for reduction of search-space in global optimization problems. Our approach is called Domain Optimization Algorithm. This approach can efficiently eliminate search-space regions with low probability of containing a global optimum. The Domain Optimization Algorithm approach is based on eliminating non-promising search-space regions, which are identifyed using simple models (linear) fitted to the data. Then, we run a global optimization algorithm starting its population inside the promising region. The proposed approach with this heuristic criterion of population initialization has shown relevant results for tests using hard benchmark functions.

Electrochemical oxidation of landfill leachate in a flow reactor: optimization using response surface methodology

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Joint economic design of X̄ and R control charts for processes subject to two independent assignable causes

A model for the joint economic design of X̄ and R control charts is developed. This model assumes that the process is subject to two assignable causes. One assignable cause shifts the process mean; the other shifts the process variance. The occurrence of the assignable cause of one kind does not block the occurrence of the assignable cause of another kind. Consequently, a second process parameter can go out-of-control after the first process parameter has gone out-of-control. A numerical study of the cost surface to the model considered has revealed that it is convex, at least in the interest region.

Efficient Forest Data Structure for Evolutionary Algorithms Applied to Network Design

The design of a network is a solution to several engineering and science problems. Several network design problems are known to be NP-hard, and population-based metaheuristics like evolutionary algorithms (EAs) have been largely investigated for such problems. Such optimization methods simultaneously generate a large number of potential solutions to investigate the search space in breadth and, consequently, to avoid local optima. Obtaining a potential solution usually involves the construction and maintenance of several spanning trees, or more generally, spanning forests. To efficiently explore the search space, special data structures have been developed to provide operations that manipulate a set of spanning trees (population). For a tree with n nodes, the most efficient data structures available in the literature require time O(n) to generate a new spanning tree that modifies an existing one and to store the new solution. We propose a new data structure, called node-depth-degree representation (NDDR), and we demonstrate that using this encoding, generating a new spanning forest requires average time O(root n). Experiments with an EA based on NDDR applied to large-scale instances of the degree-constrained minimum spanning tree problem have shown that the implementation adds small constants and lower order terms to the theoretical bound.