Assessment of body surface temperature in cetaceans: an iterative approach

A transferência de energia térmica da superfície corporal para a água é provavelmente o aspecto mais importante do equilíbrio térmico em mamíferos marinhos, mas os respectivos cálculos dependem do conhecimento da temperatura da superfície, T S, cuja medição direta em animais em liberdade constitui um problema difícil de resolver. Um método iterativo é proposto para a predição de T S de cetáceos em liberdade, a partir da temperatura corporal profunda, da velocidade de deslocamento e da temperatura e propriedades termodinâmicas da água.

On the dissimilarity between the algorithms for computing the symmetric energy-momentum tensor in ordinary field theory and general relativity

The recipe used to compute the symmetric energy-momentum tensor in the framework of ordinary field theory bears little resemblance to that used in the context of general relativity, if any. We show that if one stal ts fi om the field equations instead of the Lagrangian density, one obtains a unified algorithm for computing the symmetric energy-momentum tensor in the sense that it can be used for both usual field theory and general relativity.

ITERATIVE NUMERICAL-SOLUTION OF SCATTERING PROBLEMS

An iterative Neumann series method, employing a real auxiliary scattering integral equation, is used to calculate scattering lengths and phase shifts for the atomic Yukawa and exponential potentials. For these potentials the original Neumann series diverges. The present iterative method yields results that are far better, in convergence, stability and precision, than other momentum space methods. Accurate result is obtained in both cases with an estimated error of about 1 in 10(10) after some 8-10 iterations.

The asynchronous motor one-dimensional analysis

An application of the linear machine one-dimensional analysis method to the modeling of a conventional asynchronous induction motor, considered as a particular case of linear and sectorial machines, is described. A mathematical model for the calculation of the propulsive force developed by this motor, taking into account the transversal edge effect, is derived from the application of the one-dimensional theory and presented in this paper. As an application example, an induction motor is analyzed by means of the one-dimensional theory.

Analysis of heuristic algorithms for the transportation model in static and multistage planning in network expansion systems

The usefulness of the application of heuristic algorithms in the transportation model, first proposed by Garver, is analysed in relation to planning for the expansion of transmission systems. The formulation of the mathematical model and the solution techniques proposed in the specialised literature are analysed in detail. Starting with the constructive heuristic algorithm proposed by Garver, an extension is made to the problem of multistage planning for transmission systems. The quality of the solutions found by heuristic algorithms for the transportation model is analysed, as are applications in problems of planning transmission systems.

A cost optimization-based design of precast concrete floors using genetic algorithms

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Genetic Algorithms (Binary and Real Codes) for the Optimisation of a Fermentation Process for Butanol Production

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

Using traditional heuristic algorithms on an initial genetic algorithm population applied to the transmission expansion planning problem

This paper analyses the impact of choosing good initial populations for genetic algorithms regarding convergence speed and final solution quality. Test problems were taken from complex electricity distribution network expansion planning. Constructive heuristic algorithms were used to generate good initial populations, particularly those used in resolving transmission network expansion planning. The results were compared to those found by a genetic algorithm with random initial populations. The results showed that an efficiently generated initial population led to better solutions being found in less time when applied to low complexity electricity distribution networks and better quality solutions for highly complex networks when compared to a genetic algorithm using random initial populations.

Electric power systems transient stability analysis by neural networks

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Variational iterative method for scattering problems

A parameter-free variational iterative method is proposed for scattering problems. The present method yields results that are far better, in convergence, stability and precision, than any other momentum space method. Accurate result is obtained for the atomic exponential (Yukawa) potential with an estimated error of less than 1 in 1015 (1010) after some 13 (10) iterations.

Algorithms for network piecewise-linear programs: A comparative study

Piecewise-Linear Programming (PLP) is an important area of Mathematical Programming and concerns the minimisation of a convex separable piecewise-linear objective function, subject to linear constraints. In this paper a subarea of PLP called Network Piecewise-Linear Programming (NPLP) is explored. The paper presents four specialised algorithms for NPLP: (Strongly Feasible) Primal Simplex, Dual Method, Out-of-Kilter and (Strongly Polynomial) Cost-Scaling and their relative efficiency is studied. A statistically designed experiment is used to perform a computational comparison of the algorithms. The response variable observed in the experiment is the CPU time to solve randomly generated network piecewise-linear problems classified according to problem class (Transportation, Transshipment and Circulation), problem size, extent of capacitation, and number of breakpoints per arc. Results and conclusions on performance of the algorithms are reported.