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Constructal Theory has been applied to evaluate system performance in several engineering areas like solid mechanics, refrigeration, heat exchangers, etc. It states that finite flow systems performance can be optimized by minimizing the resistances. It is usually formulated by the definition of geometric constraints and an optimization method like exhaustive search or Genetic Algorithm. In present work, Constructal Theory is used in its most fundamental sense, i.e., the geometric forms should evolve (grow) from a fundamental shape, named here as Elemental Constructal (EC), instead of by the application of an optimization method to a predefined geometry. In order to test the proposed algorithm, the isotherm cavity intruded into a heat generating solid body problem is solved with proposed algorithm and solution is compared with literature solutions obtained for several pre-defined shapes (I, T, Y, X and others). If a sufficient small EC were used to define the building blocks of the cavity, thermal performance obtained with current method is comparable with performance of the best shapes found in literature. Main goal is not to find best possible geometry for the cavity, but to understand how cavity form should grow in order to reduce the temperature in solid domain. Moreover, the cavity optimization problem has only been used as an application example of a much more general methodology used to predict how shape and structure may evolve in different flow problems.

Heavy steel industries are constantly distressed with improving quality, reliability, and robustness of their product. Nevertheless, they are also concerned with reducing welding processes cost, men-power, and material waste. This leads to an interest in control techniques, automation, and robotization. Monitoring the welding process of continuously fed melting wire electrode is still an open problem, due to the instability caused by the electrical variables. We identify expressive gaps in the understanding of stability and quality of welding deposition. In this work, we introduce a low-cost system that monitors the stability of the weld bead and the transfer mode of the MIG/MAG welding process. We propose a non-intrusive solution that uses the sound signal produced by the electric arc to monitor and analyze the process in real-time. In this sense, we propose an Artificial Neural Network (ANN) based methodology to identify some types of discontinuities in the welding process. To support and foster the development of sound signal based neural network, we produce a sound signal dataset based on the experiments which recreate real situations in the welding industry. Processes with adequate conditions and welds with two types of discontinuities were executed to validate the methodology. The model performance is evaluated using both classification accuracy and confusion matrix. Results show to be possible to identify discontinuities in the welding process by looking only at the sound generated by the electric arc.

Fruit flies affect direct and indirect the fruit production, causing damage and losses in a worldwide scale. The control of fruit flies is usually done in an unregulated way, using insecticides in the form of bait-toxic, without knowledge of the infecting species. This work presents the development of an embedded system based on optoeletronic sensor to be used in an McPhail intelligent trap, sending remotely the data related to the fruit flies through a wireless protocol with low power consumption and wide range.

The Simulated Annealing is a widely used metaheuristic to combinatorial and optimization problems studied since 1983, when it was first proposed. This algorithm has a particular parameter, the cooling schedule (specifically the decrease of temperature) which is still defined for each problem empirically. This study has the aim to find the best cooling schedule(s) for geometric optimization of a heat transfer problem. More specifically it is performed the geometrical evaluation of an isothermal Y-shaped cavity intruded into conducting solid wall with internal heat generation. In this research, Constructal Design is employed to determine the constraints and objectives for geometric evaluation of this problem. The cooling schedule(s) recommended here will contribute for future applications of Simulated Annealing heuristic in association with Constructal Design to seek for the optimal shapes of complex geometries in heat transfer problems, as well as, evaluate the influence of geometric parameters over thermal performance of the problem. Six different methods of decrease of temperature are evaluated in twenty samples of thirty simulations for each cooling schedule. From these simulations, it was extracted the percentage of convergence to the global optimal point. Results showed that the Fast cooling schedule led to the worst performance in the seek for the global optimal shapes, while the three hybrid cooling schedules proposed here are the most recommended to find the optimal geometrical configurations in heat transfer problems in association with Constructal Design ( BoltzExp , ConstExp1 and ConstExp2 )

This work relies on constructal design to perform the geometric optimization of the V-shaped pathways of highly conductive materials (inserts) that remove a constant heat generation rate from a body and deliver it to isothermal heat sinks. It is shown numerically that the global thermal resistance of the V-shaped pathway can be minimized by geometric optimization subject to total volume and V-shaped pathways material constraints. Constructal design and genetic algorithm (GA) optimization showed the emergence of an optimal architecture that minimizes the global thermal resistance: an optimal external shape for the assembly of pathways and optimal geometry features for the V-shaped pathway. Parametric study was performed to show the behavior of the minimized global thermal resistance as function of the volume fraction of the V-shaped pathways. First achieved results for ϕ = 0.3 indicated that when freedom is given to the geometry, the thermal performance is improved. Afterward, the employment of GA with constructal design allowed the achievement of the optimal shapes of V-shaped pathways for different volume fractions (0.2 ≤ ϕ ≤ 0.4). It was not realized the occurrence of one universal optimal shape for the several values of ϕ investigated, i.e., the optimal design was dependent on the degrees of freedom and the parameter ϕ and it is reached according to constructal principle of optimal distribution of imperfections.

This work proposes an architecture of an inspection robot's navigation system, aiming at monitoring of power cables in underground distribution lines. This architecture is composed of two modules: i. feature extraction from environment, ii navigation approach. The feature extraction module is based on the use of the edge detector by Canny algorithm and Hough transform for identification of lines from images of environment to monitoring. The lines identified correspond to cable conformation inside the duct. This information will serve to help the navigation system. For the implementation of the navigation system two approaches were proposed: navigation based on artificial neural network and navigation based on PID control. The navigation architecture can be used in real or simulated scenarios, and it was tested in a simulated environment.