109 resultados para Evolutionary algorithm, Parameter identification, rolling element bearings, Genetic algorithm
Resumo:
A fully conserving algorithm is developed in this paper for the integration of the equations of motion in nonlinear rod dynamics. The starting point is a re-parameterization of the rotation field in terms of the so-called Rodrigues rotation vector, which results in an extremely simple update of the rotational variables. The weak form is constructed with a non-orthogonal projection corresponding to the application of the virtual power theorem. Together with an appropriate time-collocation, it ensures exact conservation of momentum and total energy in the absence of external forces. Appealing is the fact that nonlinear hyperelastic materials (and not only materials with quadratic potentials) are permitted without any prejudice on the conservation properties. Spatial discretization is performed via the finite element method and the performance of the scheme is assessed by means of several numerical simulations.
Resumo:
This paper addresses the use of optimization techniques in the design of a steel riser. Two methods are used: the genetic algorithm, which imitates the process of natural selection, and the simulated annealing, which is based on the process of annealing of a metal. Both of them are capable of searching a given solution space for the best feasible riser configuration according to predefined criteria. Optimization issues are discussed, such as problem codification, parameter selection, definition of objective function, and restrictions. A comparison between the results obtained for economic and structural objective functions is made for a case study. Optimization method parallelization is also addressed. [DOI: 10.1115/1.4001955]
Resumo:
This work deals with the problem of minimizing the waste of space that occurs on a rotational placement of a set of irregular bi-dimensional items inside a bi-dimensional container. This problem is approached with a heuristic based on Simulated Annealing (SA) with adaptive neighborhood. The objective function is evaluated in a constructive approach, where the items are placed sequentially. The placement is governed by three different types of parameters: sequence of placement, the rotation angle and the translation. The rotation applied and the translation of the polygon are cyclic continuous parameters, and the sequence of placement defines a combinatorial problem. This way, it is necessary to control cyclic continuous and discrete parameters. The approaches described in the literature deal with only type of parameter (sequence of placement or translation). In the proposed SA algorithm, the sensibility of each continuous parameter is evaluated at each iteration increasing the number of accepted solutions. The sensibility of each parameter is associated to its probability distribution in the definition of the next candidate.
Resumo:
Medium carbon steels are mostly used for simple applications; nevertheless new applications have been developed for which good sheet formability is required. This class of steels has an inherent low formability. A medium carbon hot rolled SAE 1050 steel has been selected for this study. It has been cold rolled with reductions in the 7-80% range. Samples have been used to assess the cold work hardening curve. For samples with a 50 and 80% thickness reduction, an annealing heat treatment has been performed to obtain recrystallization. The material has been characterized in the ""as received"", cold rolled and annealed conditions, using several methods: optical microscopy, X-ray diffraction (texture), Vickers hardness and tensile testing. The 50% cold rolled and recrystallized material has been further studied in terms of sheet metal formability and texture evolution during the actual stamping of a steel toecap that has been used to validate the finite element simulations. (C) 2008 Elsevier B.V. All rights reserved.
Resumo:
In this paper, we propose an approach to the transient and steady-state analysis of the affine combination of one fast and one slow adaptive filters. The theoretical models are based on expressions for the excess mean-square error (EMSE) and cross-EMSE of the component filters, which allows their application to different combinations of algorithms, such as least mean-squares (LMS), normalized LMS (NLMS), and constant modulus algorithm (CMA), considering white or colored inputs and stationary or nonstationary environments. Since the desired universal behavior of the combination depends on the correct estimation of the mixing parameter at every instant, its adaptation is also taken into account in the transient analysis. Furthermore, we propose normalized algorithms for the adaptation of the mixing parameter that exhibit good performance. Good agreement between analysis and simulation results is always observed.
Resumo:
As is well known, Hessian-based adaptive filters (such as the recursive-least squares algorithm (RLS) for supervised adaptive filtering, or the Shalvi-Weinstein algorithm (SWA) for blind equalization) converge much faster than gradient-based algorithms [such as the least-mean-squares algorithm (LMS) or the constant-modulus algorithm (CMA)]. However, when the problem is tracking a time-variant filter, the issue is not so clear-cut: there are environments for which each family presents better performance. Given this, we propose the use of a convex combination of algorithms of different families to obtain an algorithm with superior tracking capability. We show the potential of this combination and provide a unified theoretical model for the steady-state excess mean-square error for convex combinations of gradient- and Hessian-based algorithms, assuming a random-walk model for the parameter variations. The proposed model is valid for algorithms of the same or different families, and for supervised (LMS and RLS) or blind (CMA and SWA) algorithms.
Resumo:
Among several process variability sources, valve friction and inadequate controller tuning are supposed to be two of the most prevalent. Friction quantification methods can be applied to the development of model-based compensators or to diagnose valves that need repair, whereas accurate process models can be used in controller retuning. This paper extends existing methods that jointly estimate the friction and process parameters, so that a nonlinear structure is adopted to represent the process model. The developed estimation algorithm is tested with three different data sources: a simulated first order plus dead time process, a hybrid setup (composed of a real valve and a simulated pH neutralization process) and from three industrial datasets corresponding to real control loops. The results demonstrate that the friction is accurately quantified, as well as ""good"" process models are estimated in several situations. Furthermore, when a nonlinear process model is considered, the proposed extension presents significant advantages: (i) greater accuracy for friction quantification and (ii) reasonable estimates of the nonlinear steady-state characteristics of the process. (C) 2010 Elsevier Ltd. All rights reserved.
Resumo:
This work deals with a procedure for model re-identification of a process in closed loop with ail already existing commercial MPC. The controller considered here has a two-layer structure where the upper layer performs a target calculation based on a simplified steady-state optimization of the process. Here, it is proposed a methodology where a test signal is introduced in a tuning parameter of the target calculation layer. When the outputs are controlled by zones instead of at fixed set points, the approach allows the continuous operation of the process without an excessive disruption of the operating objectives as process constraints and product specifications remain satisfied during the identification test. The application of the method is illustrated through the simulation of two processes of the oil refining industry. (c) 2008 Elsevier Ltd. All rights reserved.
Resumo:
This article documents the addition of 229 microsatellite marker loci to the Molecular Ecology Resources Database. Loci were developed for the following species: Acacia auriculiformis x Acacia mangium hybrid, Alabama argillacea, Anoplopoma fimbria, Aplochiton zebra, Brevicoryne brassicae, Bruguiera gymnorhiza, Bucorvus leadbeateri, Delphacodes detecta, Tumidagena minuta, Dictyostelium giganteum, Echinogammarus berilloni, Epimedium sagittatum, Fraxinus excelsior, Labeo chrysophekadion, Oncorhynchus clarki lewisi, Paratrechina longicornis, Phaeocystis antarctica, Pinus roxburghii and Potamilus capax. These loci were cross-tested on the following species: Acacia peregrinalis, Acacia crassicarpa, Bruguiera cylindrica, Delphacodes detecta, Tumidagena minuta, Dictyostelium macrocephalum, Dictyostelium discoideum, Dictyostelium purpureum, Dictyostelium mucoroides, Dictyostelium rosarium, Polysphondylium pallidum, Epimedium brevicornum, Epimedium koreanum, Epimedium pubescens, Epimedium wushanese and Fraxinus angustifolia.
Resumo:
Symptoms resembling giant calyx, a graft-transmissible disease, were observed on 1-5% of eggplant (aubergine; Solanum melongena L.) plants in production fields in Sao Paulo state, Brazil. Phytoplasmas were detected in 1 2 of 1 2 samples from symptomatic plants that were analysed by a nested PCR assay employing 16S rRNA gene primers R16mF2/R16mR1 followed by R16F2n/R16R2. RFLP analysis of the resulting rRNA gene products (1.2 kb) indicated that all plants contained similar phytoplasmas, each closely resembling strains previously classified as members of RFLP group 16SrIII (X-disease group). Virtual RFLP and phylogenetic analyses of sequences derived from PCR products identified phytoplasmas infecting eggplant crops grown in Piracicaba as a lineage of the subgroup 16SrIII-J, whereas phytoplasmas detected in plants grown in Braganca Paulista were tentatively classified as members of a novel subgroup 16SrIII-U. These findings confirm eggplant as a new host of group 16SrIII-J phytoplasmas and extend the known diversity of strains belonging to this group in Brazil.
Resumo:
The genetic linkage map for the common bean (Phaseolus vulgaris L.) is a valuable tool for breeding programs. Breeders provide new cultivars that meet the requirements of farmers and consumers, such as seed color, seed size, maturity, and growth habit. A genetic study was conducted to examine the genetics behind certain qualitative traits. Growth habit is usually described as a recessive trait inherited by a single gene, and there is no consensus about the position of the locus. The aim of this study was to develop a new genetic linkage map using genic and genomic microsatellite markers and three morphological traits: growth habit, flower color, and pod tip shape. A mapping population consisting of 380 recombinant F10 lines was generated from IAC-UNA x CAL143. A total of 871 microsatellites were screened for polymorphisms among the parents, and a linkage map was obtained with 198 mapped microsatellites. The total map length was 1865.9 cM, and the average distance between markers was 9.4 cM. Flower color and pod tip shape were mapped and segregated at Mendelian ratios, as expected. The segregation ratio and linkage data analyses indicated that the determinacy growth habit was inherited as two independent and dominant genes, and a genetic model is proposed for this trait.
Resumo:
The weed, known commonly as vassourinha de botao (buttonweed), is present in several crops in northern and north-eastern Brazil. Its occurrence is common in sugarcane and soybean crops in the states of Goias, Tocantins, and Maranhao. However, there is no published information in the literature about its taxonomic classification. Thus, this research aimed to classify taxonomically this species in order to develop a classification key based on the morphological characteristics among varieties of Borreria densiflora DC., as well as to illustrate it and provide a palynological basis to classify this species as a new variety For the classification process, data from the literature, morphological characteristics, and palynological evidence were considered. In this article, we describe a new variety, B. densiflora DC. var. latifolia E.L. Cabral & Martins. The new variety possesses a terrestrial habitat and it is a simple perennial weed species. These results show the importance of an accurate identification, as well as an understanding of the evolutionary changes inherent to weeds (like intraspecific variability), breeding system, genetic potential, and ecological studies. Those factors are essential to the beginning of a long-term weed management strategy.
Resumo:
A total of 152,145 weekly test-day milk yield records from 7317 first lactations of Holstein cows distributed in 93 herds in southeastern Brazil were analyzed. Test-day milk yields were classified into 44 weekly classes of DIM. The contemporary groups were defined as herd-year-week of test-day. The model included direct additive genetic, permanent environmental and residual effects as random and fixed effects of contemporary group and age of cow at calving as covariable, linear and quadratic effects. Mean trends were modeled by a cubic regression on orthogonal polynomials of DIM. Additive genetic and permanent environmental random effects were estimated by random regression on orthogonal Legendre polynomials. Residual variances were modeled using third to seventh-order variance functions or a step function with 1, 6,13,17 and 44 variance classes. Results from Akaike`s and Schwarz`s Bayesian information criterion suggested that a model considering a 7th-order Legendre polynomial for additive effect, a 12th-order polynomial for permanent environment effect and a step function with 6 classes for residual variances, fitted best. However, a parsimonious model, with a 6th-order Legendre polynomial for additive effects and a 7th-order polynomial for permanent environmental effects, yielded very similar genetic parameter estimates. (C) 2008 Elsevier B.V. All rights reserved.
Resumo:
Lactic acid bacteria ( LAB) are currently used by food industries because of their ability to produce metabolites with antimicrobial activity against gram-positive pathogens and spoilage microorganisms. The objectives of this study were to identify naturally occurring bacteriocinogenic or bacteriocinogenic-like LAB in raw milk and soft cheese and to detect the presence of nisin-coding genes in cultures identified as Lactococcus lactis. Lactic acid bacteria cultures were isolated from 389 raw milk and soft cheese samples and were later characterized for the production of antimicrobial substances against Listeria monocytogenes. Of these, 58 (14.9%) LAB cultures were identified as antagonistic; the nature of this antagonistic activity was then characterized via enzymatic tests to confirm the proteinaceous nature of the antimicrobial substances. In addition, 20 of these antagonistic cultures were selected and submitted to genetic sequencing; they were identified as Lactobacillus plantarum (n = 2) and Lactococcus lactis ssp. lactis (n = 18). Nisin genes were identified by polymerase chain reaction in 7 of these cultures. The identified bacteriocinogenic and bacteriocinogenic-like cultures were highly variable concerning the production and activity of antimicrobial substances, even when they were genetically similar. The obtained results indicated the need for molecular and phenotypic methodologies to properly characterize bacteriocinogenic LAB, as well as the potential use of these cultures as tools to provide food safety.
Resumo:
Lychnophora ericoides Mart. (Asteraceae, Vernonieae) is a plant, endemic to Brazil, with occurrence restricted to the ""cerrado"" biome. Traditional medicine employs alcoholic and aqueous-alcoholic preparations of leaves from this species for the treatment of wounds, inflammation, and pain. Furthermore, leaves of L. ericoides are also widely used as flavorings for the Brazilian traditional spirit ""cachaca"". A method has been developed for the extraction and HPLC-DAD analysis of the secondary metabolites of L. ericoides leaves. This analytical method was validated with 11 secondary metabolites chosen to represent the different classes and polarities of secondary metabolites occurring in L. ericoides leaves, and good responses were obtained for each validation parameter analyzed. The same HPLC analytical method was also employed for online secondary metabolite identification by HPLC-DAD-MS and HPLC-DAD-MS/MS, leading to the identification of di-C-glucosylflavones, coumaroylglucosylflavonols, flavone, flavanones, flavonols, chalcones, goyazensolide, and eremantholide-type sesquiterpene lactones and positional isomeric series of chlorogenic acids possessing caffeic and/or ferulic moieties. Among the 52 chromatographic peaks observed, 36 were fully identified and 8 were attributed to compounds belonging to series of caffeoylferuloylquinic and diferuloylquinic acids that could not be individualized from each other.