Simulação da transferência de calor em amostras aquecidas por plasma

The processing of materials through plasma has been growing enough in the last times in several technological applications, more specifically in surfaces treatment. That growth is due, mainly, to the great applicability of plasmas as energy source, where it assumes behavior thermal, chemical and/or physical. On the other hand, the multiplicity of simultaneous physical effects (thermal, chemical and physical interactions) present in plasmas increases the complexity for understanding their interaction with solids. In that sense, as an initial step for the development of that subject, the present work treats of the computational simulation of the heating and cooling processes of steel and copper samples immersed in a plasma atmosphere, by considering two experimental geometric configurations: hollow and plane cathode. In order to reach such goal, three computational models were developed in Fortran 90 language: an one-dimensional transient model (1D, t), a two-dimensional transient model (2D, t) and a two-dimensional transient model (2D, t) which take into account the presence of a sample holder in the experimental assembly. The models were developed based on the finite volume method and, for the two-dimensional configurations, the effect of hollow cathode on the sample was considered as a lateral external heat source. The main results obtained with the three computational models, as temperature distribution and thermal gradients in the samples and in the holder, were compared with those developed by the Laboratory of Plasma, LabPlasma/UFRN, and with experiments available in the literature. The behavior showed indicates the validity of the developed codes and illustrate the need of the use of such computational tool in that process type, due to the great easiness of obtaining thermal information of interest

Conexão entre as redes complexas e estatística de Kaniadakis e busca eficiente das propriedades críticas do processo epidêmico difusivo 1D

In this work we study a connection between a non-Gaussian statistics, the Kaniadakis statistics, and Complex Networks. We show that the degree distribution P(k)of a scale free-network, can be calculated using a maximization of information entropy in the context of non-gaussian statistics. As an example, a numerical analysis based on the preferential attachment growth model is discussed, as well as a numerical behavior of the Kaniadakis and Tsallis degree distribution is compared. We also analyze the diffusive epidemic process (DEP) on a regular lattice one-dimensional. The model is composed of A (healthy) and B (sick) species that independently diffusive on lattice with diffusion rates DA and DB for which the probabilistic dynamical rule A + B → 2B and B → A. This model belongs to the category of non-equilibrium systems with an absorbing state and a phase transition between active an inactive states. We investigate the critical behavior of the DEP using an auto-adaptive algorithm to find critical points: the method of automatic searching for critical points (MASCP). We compare our results with the literature and we find that the MASCP successfully finds the critical exponents 1/ѵ and 1/zѵ in all the cases DA =DB, DA DB. The simulations show that the DEP has the same critical exponents as are expected from field-theoretical arguments. Moreover, we find that, contrary to a renormalization group prediction, the system does not show a discontinuous phase transition in the regime o DA >DB.