Reginaldo A. Zara

Solução computacional do problema da cavidade cúbica através das equações de Navier-Stokes tridimensionais

This paper presents an approach to solving problems of three-dimensional fluid flow with application to the problem cubic cavity with sliding covering. The fluid flow is modeled by the Navier-Stokes equations which are discretized using the finite difference method. The solution to the problem was obtained using the SOR method (Successive Over Relaxation) to solve the Poisson equation for pressure for each time step. The results of numerical simulations are presented as graphs of velocity, pressure and surface current. It is observed the formation of tridimensional vortices rising from the corners of the cavity near the covering. The results generalize the solution of the two-dimensional case and show the numerical-computational strategies employed are appropriated and exhibit good numerical quality.

Transições ele fase em um modelo de crescimento interagente semiflexível

The Interacting Growth Walk (IGW) is a kinect growing model that could be especially useful to investigate polymer systems at low temperature regimes. It may generate self-avoiding chains to be used in investigation of physical and geometrial properties of polymer chains at different temperatures. In this work we introduce stiffness effects in the standard Narasimhan IGW model aiming to investigate a single strand semiflexible polymer by adding an energy penalty (χ) for each change in the growth direction of the chain. We found that, depending on stiffness strength, the chain can be considered flexible (for χ = 0) or rigid (in the limit χ → ∞)). For intermediate values of χ the IGW model generates semiflexible chains. The resulting model called as semiflexible interacting growth model was investigated by means of Monte Carlo simulations and the properties of the chains obtained were analyzed. It is observed phase transitions between three different conformational arrangements: an extended phase, a compact isotropic phase and a compact anisotropic phase. Similar final conformations as well as phase transitions are known from self-avoiding walk models.

Computational Agents Applied to Dengue Fever Simulation

This paper summarizes the three main modules of a computing system whose goal is to automate specific actions aiming to provide combat and control of dengue. The module I is an information system on Dengue. Modules II and III perform simulations on dengue using computational agents.

Simulação de Monte Carlo do modelo de crescimento cinético interagente

The interacting growth model (IGW) belongs to a class of growth models used to simulate polymerization processes. In this work it was investigated by means of Monte Carlo simulations and a statistical analysis of the properties of the self avoiding configurations was made. We evaluated the distributions of growths frustrated by self trapping for growths carried out under different temperatures. The IGW model generates long chains at low temperatures and its efficiency is improved when the temperature is lowered. This fact contrasts with the usual methods of generating self avoiding chain based on models of self avoinding walks (SAW). Using the distributions of the configurations generated and the fractions and successful growth we evaluated the mean lengths of growths and the distribution of contacts as a function of the temperature. The results confirm the findings of Narasimhan et al. that there is a transition Θ equivalent to that observed in SAW models and complements the analysis of the model defined on square networks.

Dynamic modeling of overload in scale free networks

We introduce a simple dynamic model to investigate the fragmentation of transport networks. The transport properties like as the size of largest connected cluster, the length of the minimum paths and the optimal paths between a pair of nodes of the network were evaluated upon continuously increasing the load on the system. We use two load insertion strategies: an uniform random distribution of loads and a Cohen-like immunization strategy (one node is selected with a uniform probability p and one of its first neighbours, randomly selected, receives the load). Both strategies may be classified as local strategies but the resulting effects are qualitatively different. Evaluating the physical quantities as a function of time we observe that for the random distribution strategy there is a crossover from a fully connected cluster to a non-connected state in the sense that all links become unavailable. On the other hand, following the Cohen-like strategy we found a sudden change in transport properties which is may be interpreted as a percolation-like transition induced by the cumulative process of load.