3 resultados para Time-Fractional Diffusion-Wave Problem

em Universidade Federal do Rio Grande do Norte(UFRN)


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The present work investigates some consequences that arise from the use of a modifed lagrangean for the eletromagnetic feld in two diferent contexts: a spatially homogeneous and isotropic universe whose dynamics is driven by a magnetic feld plus a cosmological parameter A, and the problem of a static and charged point mass (charged black hole). In the cosmological case, three diferent general solutions were derived. The first, with a null cosmological parameter A, generalizes a particular solution obtained by Novello et al [gr-qc/9806076]. The second one admits a constant A and the third one allows A to be a time-dependent parameter that sustains a constant magnetic feld. The first two solutions are non-singular and exhibit in ationary periods. The third case studied shows an in ationary dynamics except for a short period of time. As for the problem of a charged point mass, the solutions of the Einstein-Maxwell equations are obtained and compared with the standard Reissner-Nordstrom solution. Contrary to what happens in the cosmological case, the physical singularity is not removed

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We investigate several diffusion equations which extend the usual one by considering the presence of nonlinear terms or a memory effect on the diffusive term. We also considered a spatial time dependent diffusion coefficient. For these equations we have obtained a new classes of solutions and studied the connection of them with the anomalous diffusion process. We start by considering a nonlinear diffusion equation with a spatial time dependent diffusion coefficient. The solutions obtained for this case generalize the usual one and can be expressed in terms of the q-exponential and q-logarithm functions present in the generalized thermostatistics context (Tsallis formalism). After, a nonlinear external force is considered. For this case the solutions can be also expressed in terms of the q-exponential and q-logarithm functions. However, by a suitable choice of the nonlinear external force, we may have an exponential behavior, suggesting a connection with standard thermostatistics. This fact reveals that these solutions may present an anomalous relaxation process and then, reach an equilibrium state of the kind Boltzmann- Gibbs. Next, we investigate a nonmarkovian linear diffusion equation that presents a kernel leading to the anomalous diffusive process. Particularly, our first choice leads to both a the usual behavior and anomalous behavior obtained through a fractionalderivative equation. The results obtained, within this context, correspond to a change in the waiting-time distribution for jumps in the formalism of random walks. These modifications had direct influence in the solutions, that turned out to be expressed in terms of the Mittag-Leffler or H of Fox functions. In this way, the second moment associated to these distributions led to an anomalous spread of the distribution, in contrast to the usual situation where one finds a linear increase with time

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The Multiobjective Spanning Tree is a NP-hard Combinatorial Optimization problem whose application arises in several areas, especially networks design. In this work, we propose a solution to the biobjective version of the problem through a Transgenetic Algorithm named ATIS-NP. The Computational Transgenetic is a metaheuristic technique from Evolutionary Computation whose inspiration relies in the conception of cooperation (and not competition) as the factor of main influence to evolution. The algorithm outlined is the evolution of a work that has already yielded two other transgenetic algorithms. In this sense, the algorithms previously developed are also presented. This research also comprises an experimental analysis with the aim of obtaining information related to the performance of ATIS-NP when compared to other approaches. Thus, ATIS-NP is compared to the algorithms previously implemented and to other transgenetic already presented for the problem under consideration. The computational experiments also address the comparison to two recent approaches from literature that present good results, a GRASP and a genetic algorithms. The efficiency of the method described is evaluated with basis in metrics of solution quality and computational time spent. Considering the problem is within the context of Multiobjective Optimization, quality indicators are adopted to infer the criteria of solution quality. Statistical tests evaluate the significance of results obtained from computational experiments