Estudo do estado fundamental de aglomerados de silício via redes neurais

We introduce a global optimization method based on the cooperation between an Artificial Neural Net (ANN) and Genetic Algorithm (GA). We have used ANN to select the initial population for the GA. We have tested the new method to predict the ground-state geometry of silicon clusters. We have described the clusters as a piling of plane structures. We have trained three ANN architectures and compared their results with those of pure GA. ANN strongly reduces the total computational time. For Si10, it gained a factor of 5 in search speed. This method can be easily extended to other optimization problems.

Uso de redes neurais recorrentes na determinação das constantes de acidez para a 7-epiclusianona em misturas etanol-água

This work propose a recursive neural network to solve inverse equilibrium problem. The acidity constants of 7-epiclusianone in ethanol-water binary mixtures were determined from multiwavelength spectrophotmetric data. A linear relationship between acidity constants and the %w/v of ethanol in the solvent mixture was observed. The proposed method efficiency is compared with the Simplex method, commonly used in nonlinear optimization techniques. The neural network method is simple, numerically stable and has a broad range of applicability.

Methane combustion kinetic rate constants determination: an ill-posed inverse problem analysis

Methane combustion was studied by the Westbrook and Dryer model. This well-established simplified mechanism is very useful in combustion science, for computational effort can be notably reduced. In the inversion procedure to be studied, rate constants are obtained from [CO] concentration data. However, when inherent experimental errors in chemical concentrations are considered, an ill-conditioned inverse problem must be solved for which appropriate mathematical algorithms are needed. A recurrent neural network was chosen due to its numerical stability and robustness. The proposed methodology was compared against Simplex and Levenberg-Marquardt, the most used methods for optimization problems.

Analysis of the relationship intensity, duration, frequency of disaggregated daily rainfall in southern Rio Grande do Sul, Brazil

The intensity, duration, and frequency relationship (IDF) of rainfall occurrence may be done through continuous records of pluviographs or daily pluviometer values . The objective of this study was to estimate the intensity-duration-frequency relationships of precipitation, using the method of daily rainfall disaggregation, at weather stations located to the southern half of the state of Rio Grande do Sul; comparing them with those obtained by rain gauge records, in places considered homogeneous from the meteorological point of view. The IDF equation parameters were estimated from daily rainfall disaggregation data, using the method of nonlinear optimization. To validate the equations confidence indices and efficiency and the "t" Student test, among maximum intensity values obtained from the disaggregated daily rainfall durations of 10; 30; 60 min and 6; 12 and 24 h and those extracted from existing IDF equations. For all studied stations and return periods, the trust index values were regarded as "optimal", i.e., greater than 0.85. The maximal intensity of rainfall obtained by daily rainfall disaggregation have similarity with those obtained by relations IDF standards. Thus, the method constitutes a feasible alternative in obtaining the IDF relationships.

Simulation of Steady-State Nonlinear Heat Transfer Problems Through the Minimization of Quadratic Functionals

In this work it is presented a systematic procedure for constructing the solution of a large class of nonlinear conduction heat transfer problems through the minimization of quadratic functionals like the ones usually employed for linear descriptions. The proposed procedure gives rise to an efficient and easy way for carrying out numerical simulations of nonlinear heat transfer problems by means of finite elements. To illustrate the procedure a particular problem is simulated by means of a finite element approximation.

Optimization of the use of carbon paste electrodes (CPE) for electrochemical study of the chalcopyrite

The use of carbon paste electrodes (CPE) of mineral sulfides can be useful for electrochemical studies to overcome problems by using massive ones. Using CPE-chalcopyrite some variables were electrochemically evaluated. These variables were: (i) the atmosphere of preparation (air or argon) of CPE and elapsed time till its use; (ii) scan rate for voltammetric measurements and (iii) chalcopyrite concentration in the CPE. Based on cyclic voltammetry, open-circuit potential and electrochemical impedance results the recommendations are: oxygen-free atmosphere to prepare and kept the CPE until around two ours, scan rates from 10 to 40 mV s-1, and chalcopyrite concentrations > 20%.

Retrieval of kinetic rates in reactions with semi batch liquid phase using ill-posed inverse problem theory

A neural network procedure to solve inverse chemical kinetic problems is discussed in this work. Rate constants are calculated from the product concentration of an irreversible consecutive reaction: the hydrogenation of Citral molecule, a process with industrial interest. Simulated and experimental data are considered. Errors in the simulated data, up to 7% in the concentrations, were assumed to investigate the robustness of the inverse procedure. Also, the proposed method is compared with two common methods in nonlinear analysis; the Simplex and Levenberg-Marquardt approaches. In all situations investigated, the neural network approach was numerically stable and robust with respect to deviations in the initial conditions or experimental noises.

Nonlinear dynamics and control of multibody systems

The dynamics of flexible systems, such as robot manipulators , mechanical chains or multibody systems in general, is becoming increasingly important in engineering. This article deals with some nonlinearities that arise in the study of dynamics and control of multibody systems in connection to large rotations. Specifically, a numerical scheme that adresses the conservation of fundamental constants is presented in order to analyse the control-structure interaction problems.

Object-oriented Programming Applied to the Development of Structural Analysis and Optimization Software

This paper presents the development of a two-dimensional interactive software environment for structural analysis and optimization based on object-oriented programming using the C++ language. The main feature of the software is the effective integration of several computational tools into graphical user interfaces implemented in the Windows-98 and Windows-NT operating systems. The interfaces simplify data specification in the simulation and optimization of two-dimensional linear elastic problems. NURBS have been used in the software modules to represent geometric and graphical data. Extensions to the analysis of three-dimensional problems have been implemented and are also discussed in this paper.

Covalidation of Integral Transforms and Method of Lines in Nonlinear Convection-Diffusion with Mathematica

The Mathematica system (version 4.0) is employed in the solution of nonlinear difusion and convection-difusion problems, formulated as transient one-dimensional partial diferential equations with potential dependent equation coefficients. The Generalized Integral Transform Technique (GITT) is first implemented for the hybrid numerical-analytical solution of such classes of problems, through the symbolic integral transformation and elimination of the space variable, followed by the utilization of the built-in Mathematica function NDSolve for handling the resulting transformed ODE system. This approach ofers an error-controlled final numerical solution, through the simultaneous control of local errors in this reliable ODE's solver and of the proposed eigenfunction expansion truncation order. For covalidation purposes, the same built-in function NDSolve is employed in the direct solution of these partial diferential equations, as made possible by the algorithms implemented in Mathematica (versions 3.0 and up), based on application of the method of lines. Various numerical experiments are performed and relative merits of each approach are critically pointed out.