7 resultados para Isolated bound-state solution


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The aim of this contribution is to extend the techniques of composite materials design to non-linear material behaviour and apply it for design of new materials for passive vibration control. As a first step a computational tool allowing determination of macroscopic optimized one-dimensional isolator behaviour was developed. Voigt, Maxwell, standard and more complex material models can be implemented. Objective function considers minimization of the initial reaction and/or displacement peak as well as minimization of the steady-state amplitude of reaction and/or displacement. The complex stiffness approach is used to formulate the governing equations in an efficient way. Material stiffness parameters are assumed as non-linear functions of the displacement. The numerical solution is performed in the complex space. The steady-state solution in the complex space is obtained by an iterative process based on the shooting method which imposes the conditions of periodicity with respect to the known value of the period. Extension of the shooting method to the complex space is presented and verified. Non-linear behaviour of material parameters is then optimized by generic probabilistic meta-algorithm, simulated annealing. Dependence of the global optimum on several combinations of leading parameters of the simulated annealing procedure, like neighbourhood definition and annealing schedule, is also studied and analyzed. Procedure is programmed in MATLAB environment.

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Inorganica Chimica Acta 356 (2003) 215-221

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Thesis submitted to the Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia for the degree of Doctor of Philosophy in Environmental Sciences

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African Studies Review, Volume 52, Number 2, pp. 35–

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J Biol Inorg Chem (2008) 13:1321–1333 DOI 10.1007/s00775-008-0416-1

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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics

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This study analyses financial data using the result characterization of a self-organized neural network model. The goal was prototyping a tool that may help an economist or a market analyst to analyse stock market series. To reach this goal, the tool shows economic dependencies and statistics measures over stock market series. The neural network SOM (self-organizing maps) model was used to ex-tract behavioural patterns of the data analysed. Based on this model, it was de-veloped an application to analyse financial data. This application uses a portfo-lio of correlated markets or inverse-correlated markets as input. After the anal-ysis with SOM, the result is represented by micro clusters that are organized by its behaviour tendency. During the study appeared the need of a better analysis for SOM algo-rithm results. This problem was solved with a cluster solution technique, which groups the micro clusters from SOM U-Matrix analyses. The study showed that the correlation and inverse-correlation markets projects multiple clusters of data. These clusters represent multiple trend states that may be useful for technical professionals.