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.

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.

Termodinâmica estatística de líquidos com o método de Monte Carlo. I. Metodologia

Statistical mechanics Monte Carlo simulation is reviewed as a formalism to study thermodynamic properties of liquids. Considering the importance of free energy changes in chemical processes, the thermodynamic perturbation theory implemented in the Monte Carlo method is discussed. The representation of molecular interaction by the Lennard-Jones and Coulomb potential functions is also discussed. Charges derived from quantum molecular electrostatic potential are also discussed as an useful methodology to generate an adequate set of partial charges to be used in liquid simulation.

Vibrational contribution to dipole polarizability and first hyperpolarizability of LiH

The role played by electron correlation and vibrational correction on the polarizability of the LiH molecule is demonstrated. We present results for the dipole moment, polarizability and first hyperpolarizability of the LiH molecule obtained through many-body perturbation-theory, coupled-cluster and quadratic configuration interaction methods. Our best result for the dipole polarizability, obtained using the QCISD(T) scheme, indicates that the vibrational contribution is appreciable, amounting to ca. 10% of the total polarizability. Regarding the first hyperpolarizability, the vibrational contribution is even more important and has opposite sign in comparison with the electronic contribution.

Heat Source Estimation with the Conjugate Gradient Method in Inverse Linear Diffusive Problems

In this work, we present the solution of a class of linear inverse heat conduction problems for the estimation of unknown heat source terms, with no prior information of the functional forms of timewise and spatial dependence of the source strength, using the conjugate gradient method with an adjoint problem. After describing the mathematical formulation of a general direct problem and the procedure for the solution of the inverse problem, we show applications to three transient heat transfer problems: a one-dimensional cylindrical problem; a two-dimensional cylindrical problem; and a one-dimensional problem with two plates.

On-site calibration of a phase fraction meter by an inverse technique

The formal calibration procedure of a phase fraction meter is based on registering the outputs resulting from imposed phase fractions at known flow regimes. This can be straightforwardly done in laboratory conditions, but is rarely the case in industrial conditions, and particularly for on-site applications. Thus, there is a clear need for less restrictive calibration methods regarding to the prior knowledge of the complete set of inlet conditions. A new procedure is proposed in this work for the on-site construction of the calibration curve from total flown mass values of the homogeneous dispersed phase. The solution is obtained by minimizing a convenient error functional, assembled with data from redundant tests to handle the intrinsic ill-conditioned nature of the problem. Numerical simulations performed for increasing error levels demonstrate that acceptable calibration curves can be reconstructed, even from total mass measured within a precision of up to 2%. Consequently, the method can readily be applied, especially in on-site calibration problems in which classical procedures fail due to the impossibility of having a strict control of all the input/output parameters.

A structural bridge between alternant and non-alternant hydrocarbons

A simple set of trimethylene-substituted even, fully-pi-bonded, non-alternant monocycles is shown to have several key features in common with acyclic, even alternant polyenes at the Hückel level. These non-alternant molecules provide a bridge between alternant and non-alternant hydrocarbons. This topic might serve as a useful addition to Hückel theory courses targeted at senior undergraduate students.

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.

Proposal of methodology for the modeling and control of manipulators

Industrial applications demand that robots operate in agreement with the position and orientation of their end effector. It is necessary to solve the kinematics inverse problem. This allows the displacement of the joints of the manipulator to be determined, to accomplish a given objective. Complete studies of dynamical control of joint robotics are also necessary. Initially, this article focuses on the implementation of numerical algorithms for the solution of the kinematics inverse problem and the modeling and simulation of dynamic systems. This is done using real time implementation. The modeling and simulation of dynamic systems are performed emphasizing off-line programming. In sequence, a complete study of the control strategies is carried out through the study of several elements of a robotic joint, such as: DC motor, inertia, and gearbox. Finally a trajectory generator, used as input for a generic group of joints, is developed and a proposal of the controller's implementation of joints, using EPLD development system, is presented.

As fases históricas do debate sobre a transformação dos valores em preços de produção

The historical phases of the debate on the transformation of values into production prices. Even though the transformation problem in general does not have a widen accepted solution, it is possible to recognize scientific progress when the historical phases of the debate are put side by side in order to complement each other. Therefore, the debate originated from the challenge of the conciliation of the law of value with an equal average rate of profit, though sometimes said to be unfruitful by economists, shows evolution in the long run because it forces non-marxist economic schools to confront concretely the quality side of value in theory and to develop abstract models of planned economy in practice.