Identification of structural damage in flexible structures using system norm and neural networks

Nowadays there is great interest in damage identification using non destructive tests. Predictive maintenance is one of the most important techniques that are based on analysis of vibrations and it consists basically of monitoring the condition of structures or machines. A complete procedure should be able to detect the damage, to foresee the probable time of occurrence and to diagnosis the type of fault in order to plan the maintenance operation in a convenient form and occasion. In practical problems, it is frequent the necessity of getting the solution of non linear equations. These processes have been studied for a long time due to its great utility. Among the methods, there are different approaches, as for instance numerical methods (classic), intelligent methods (artificial neural networks), evolutions methods (genetic algorithms), and others. The characterization of damages, for better agreement, can be classified by levels. A new one uses seven levels of classification: detect the existence of the damage; detect and locate the damage; detect, locate and quantify the damages; predict the equipment's working life; auto-diagnoses; control for auto structural repair; and system of simultaneous control and monitoring. The neural networks are computational models or systems for information processing that, in a general way, can be thought as a device black box that accepts an input and produces an output. Artificial neural nets (ANN) are based on the biological neural nets and possess habilities for identification of functions and classification of standards. In this paper a methodology for structural damages location is presented. This procedure can be divided on two phases. The first one uses norms of systems to localize the damage positions. The second one uses ANN to quantify the severity of the damage. The paper concludes with a numerical application in a beam like structure with five cases of structural damages with different levels of severities. The results show the applicability of the presented methodology. A great advantage is the possibility of to apply this approach for identification of simultaneous damages.

Global optimization for the ℋ∞-norm model reduction problem

A branch and bound algorithm is proposed to solve the [image omitted]-norm model reduction problem for continuous and discrete-time linear systems, with convergence to the global optimum in a finite time. The lower and upper bounds in the optimization procedure are described by linear matrix inequalities (LMI). Also proposed are two methods with which to reduce the convergence time of the branch and bound algorithm: the first one uses the Hankel singular values as a sufficient condition to stop the algorithm, providing to the method a fast convergence to the global optimum. The second one assumes that the reduced model is in the controllable or observable canonical form. The [image omitted]-norm of the error between the original model and the reduced model is considered. Examples illustrate the application of the proposed method.

Triangular arrangement of defects in a mesoscopic superconductor

By solving the time dependent Ginzburg-Landau equations, we investigated the influence of an internal triangular arrangement of point-like defects on the vortex configurations in a thin mesoscopic sample. The effect of the number of internal defects and their nature on the entrance position of the vortex is studied for a very thin circular sample. We found that the interplay between the vortex-vortex repulsion, the vortex-defect interaction and the interaction with the sample border leads to non-commensurate vortex configurations. © 2012 Elsevier B.V. All rights reserved.

Análise teórica de uma nova técnica de processamento de sinais interferométricos baseada na modulação triangular da fase óptica

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Determinação da freqüência de ressonância de antenas tipo microfita triangular e retangular utilizando redes neurais artificiais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Comparative analysis of circular and triangular gold nanodisks for field enhancement applications

ABSTRACT: In this paper, we present a quantitative comparison of circular and triangular gold nanodisks with the same length and thickness. The method of moments is used to solve numerically the scattering problem. With this model, we investigate the spatial near field distribution, spectral response, far field diagrams, and bandwidth wavelength of these particles. Our results show that the resonant wavelength and the near field enhancement and confinement of the triangular particle are larger than those for the circular particle, but the resonance bandwidth and scattering cross section of the triangular particle are smaller.

Resonant properties, of modified triangular plasmonic nanoparticles with higher field concentration

In this paper, we present an analysis of the resonant response of modified triangular metallic nanoparticles with polynomial sides. The particles are illuminated by an incident plane wave and the method of moments is used to solve numerically the electromagnetic scattering problem. We investigate spectral response and near field distribution in function of the length and polynomial order of the nanoparticles. Our results show that in the analyzed wavelength range (0.5-1.8) µm these particles possess smaller number of resonances and their resonant wavelengths, near field enhancement and field confinement are higher than those of the conventional triangular particle with linear sides.

Production lot sizing and scheduling with non-triangular sequence-dependent setup times

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Zero, minimum and maximum relative radial acceleration for planar formation flight dynamics near triangular libration points in the Earth-Moon system

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

Natural formations at the Earth-Moon triangular point in perturbed restricted problems

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

Reaction norm model to describe environmental sensitivity across first lactation in dairy cattle under tropical conditions

Reaction norm models have been widely used to study genotype by environment interaction (G × E) in animal breeding. The objective of this study was to describe environmental sensitivity across first lactation in Brazilian Holstein cows using a reaction norm approach. A total of 50,168 individual monthly test day (TD) milk yields (10 test days) from 7476 complete first lactations of Holstein cattle were analyzed. The statistical models for all traits (10 TDs and for 305-day milk yield) included the fixed effects of contemporary group, age of cow (linear and quadratic effects), and days in milk (linear effect), except for 305-day milk yield. A hierarchical reaction norm model (HRNM) based on the unknown covariate was used. The present study showed the presence of G × E in milk yield across first lactation of Holstein cows. The variation in the heritability estimates implies differences in the response to selection depending on the environment where the animals of this population are evaluated. In the average environment, the heritabilities for all traits were rather similar, in range from 0.02 to 0.63. The scaling effect of G × E predominated throughout most of lactation. Particularly during the first 2 months of lactation, G × E caused reranking of breeding values. It is therefore important to include the environmental sensitivity of animals according to the phase of lactation in the genetic evaluations of Holstein cattle in tropical environments.

Relationship between the morphology of the maxillary central incisor and horizontal and vertical measurements of the face

Purpose: In order to assist in the selection of artificial teeth for complete dentures, this study aimed to assess the relationship between horizontal and vertical measurements of the face and the morphology of the maxillary central incisor. Materials and Methods: This was a study of 50 plaster casts and 100 teleradiographs - 50 in lateral norm and 50 in frontal norm, belonging to 50 individuals, Caucasian, with a naturally optimal occlusion, matching at least four of the six keys of Andrews. Images of the upper central incisors were obtained by scanning the plaster casts (three-dimensional) and subjectively classified by three examiners as oval, triangular or quadrangular. Facial measures (vertical and horizontal) were defined by means of teleradiographs. In order to check inter-examiner agreement on the classification of central incisor, the Kappa test was used. To verify whether data had normal distribution, the Kolmogorov-Smirnov test was used ( P > 0.2) was used. One-way analysis of variance was employed to assess the association between variables (P > 0.05). Results: When vertical measurements were compared with the three incisor shapes, there was no statistically significant difference (P > 0.05): Triangular (0.54), oval (0.63) and quadrangular (0.51). Similarly, no difference (P > 0.05) was found for facial width (139.08, 143.37, 141.65), maxillary width (76.68, 78.99, 76.91) and mandibular width (103.47, 105.50, 103.11). Conclusions: The majority of cases showed that horizontal and vertical measurements of the face cannot be used as a reference for determining the morphology of the maxillary central incisor crown. It is relevant to analyze and compare other morphological structures to improve the oral health-related quality of life for the conventional denture wearer.

Caminhamento fotogramétrico com arranjo triangular de câmaras fotográficas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A new approach for modeling and control of nonlinear systems via norm-bounded linear differential inclusions

A systematic approach to model nonlinear systems using norm-bounded linear differential inclusions (NLDIs) is proposed in this paper. The resulting NLDI model is suitable for the application of linear control design techniques and, therefore, it is possible to fulfill certain specifications for the underlying nonlinear system, within an operating region of interest in the state-space, using a linear controller designed for this NLDI model. Hence, a procedure to design a dynamic output feedback controller for the NLDI model is also proposed in this paper. One of the main contributions of the proposed modeling and control approach is the use of the mean-value theorem to represent the nonlinear system by a linear parameter-varying model, which is then mapped into a polytopic linear differential inclusion (PLDI) within the region of interest. To avoid the combinatorial problem that is inherent of polytopic models for medium- and large-sized systems, the PLDI is transformed into an NLDI, and the whole process is carried out ensuring that all trajectories of the underlying nonlinear system are also trajectories of the resulting NLDI within the operating region of interest. Furthermore, it is also possible to choose a particular structure for the NLDI parameters to reduce the conservatism in the representation of the nonlinear system by the NLDI model, and this feature is also one important contribution of this paper. Once the NLDI representation of the nonlinear system is obtained, the paper proposes the application of a linear control design method to this representation. The design is based on quadratic Lyapunov functions and formulated as search problem over a set of bilinear matrix inequalities (BMIs), which is solved using a two-step separation procedure that maps the BMIs into a set of corresponding linear matrix inequalities. Two numerical examples are given to demonstrate the effectiveness of the proposed approach.

Matrix-vector multiplication and triangular linear solver using GPGPU for symmetric positive definite matrices derived from elliptic equations

The modern GPUs are well suited for intensive computational tasks and massive parallel computation. Sparse matrix multiplication and linear triangular solver are the most important and heavily used kernels in scientific computation, and several challenges in developing a high performance kernel with the two modules is investigated. The main interest it to solve linear systems derived from the elliptic equations with triangular elements. The resulting linear system has a symmetric positive definite matrix. The sparse matrix is stored in the compressed sparse row (CSR) format. It is proposed a CUDA algorithm to execute the matrix vector multiplication using directly the CSR format. A dependence tree algorithm is used to determine which variables the linear triangular solver can determine in parallel. To increase the number of the parallel threads, a coloring graph algorithm is implemented to reorder the mesh numbering in a pre-processing phase. The proposed method is compared with parallel and serial available libraries. The results show that the proposed method improves the computation cost of the matrix vector multiplication. The pre-processing associated with the triangular solver needs to be executed just once in the proposed method. The conjugate gradient method was implemented and showed similar convergence rate for all the compared methods. The proposed method showed significant smaller execution time.