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Every technological process developed since the beginning of humanity to the present day always involves some kind of energy use, either mechanical energy of the body or energy from burning fuel or the solar energy obtained from the sun. To manipulate and use that energy, the man always developed resources and equipment to allow it. Among the wide range of equipment, heat exchangers, designed to transfer heat from one fluid to another, will be analyzed in this work. To do this analysis, are used computational fluid dynamics (CFD) techniques to analyze the flow behavior of a compact heat exchanger, of tube and louvered fins type. After this step that aims to pull the parameters of efficiency, optimization features will be used to be able to propose a model for more efficient fin.

A few decades ago, the product development process was just based on a trial and error procedure, and the designer's experience. The need for a new way to design and manufacture more economical and sustainable products corroborates increasingly to a new vision of how to create new products for the benefit of society. Modern numerical tools allow greater knowledge about the physical phenomena involved in engineering problems and enable cost reduction with trials and time of manufacture and projection. Among the equipment that can be mentioned where numerical simulation is used, can be found heat exchangers, which are capable of accomplishing the heat transfer between two fluid medias with different temperatures. Within the range of existing exchangers, this work will address a compact model with louvered fins, widely used in the automotive and aerospace industries, mainly due to their high thermal exchange surface vs occupied volume ratio. The heat exchanger surface is analised using computational fluid dynamics tecniques disposable in the commercial code ANSYS CFX14® to reproduce the flow at service condition. Genetic optimization routines are used to increase the performance of heat exchanger. As a result, a heat transfer surface is obtained with about a 25% better performance according to the selected objective function. The dimensionless factor of the convective heat transfer coefficient (Colburn factor, j) and the friction factor (Fanning factor, f) used in (Wang et al.,1998), are employed for simulation. Experimental data are also used for validation.