Thiago N. Rodrigues

Work place: Superior Teaching Institute of Londrina - Educational Faculty of Colombo, ParanĂ¡, Brazil

E-mail: nascimenthiago@gmail.com

Website:

Research Interests: Computer Networks, Network Architecture, Network Security

Biography

Thiago N. Rodrigues has completed his BSc in Computational Mathematics from Federal University of Minas Gerais (UFMG), Brazil. Before his master, he has achieved the specialist's degree in computers network infrastructure for IT business environments from Espírito-Santenses Integrated Faculties (FAESA), Brazil. His MSc in Informatics was obtained from Federal University of Espírito Santo (UFES), Brazil, and it was focused on the parallelization of irregular algorithms for sparse matrices reordering. Through the last decade, he has been acting as a software engineer in large projects of enterprise systems for the Brazilian government. Currently, he is also a professor in a superior teaching institute (INESUL/FAEC) in Brazil.

Author Articles
An Implementation of the Finite Differences Method for the Two-Dimensional Rectangular Cooling Fin Problem

By Thiago N. Rodrigues

DOI: https://doi.org/10.5815/ijitcs.2019.08.01, Pub. Date: 8 Aug. 2019

The transport or advection-diffusion-reaction equation is a well-known partial differential equation employed to model several types of flux problems. The cooling fin problem is a particular case of such an equation. This work presents a straightforward model for the rectangular cooling fin in a problem. The model was based on the finite differences numerical method and an efficient implementation was developed in a high-level mathematical programming language.  The accuracy was evaluated with different granularity levels of meshes, and two distinct boundary conditions are compared. In the first one, only prescribed temperatures are assumed at the four tips of the domain. For the second scenario, it is assumed a heat flux at one tip of a fin with the same geometrical shape. The achieved solutions produced by the algorithm were able to depict the temperature along the whole fin surface accurately. Furthermore, the algorithm reaches relevant performance for meshes up to 4257 points where the CPU time was about 33 seconds.

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