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Summary Much of the cost of manufacturing transformers is related to the complexity in the development of its project, which involves many variables, such as different types of materials, methods, and manufacturing processes. Also, it is notoriously difficult to establish standards that relate the transformer characteristics with these design variables, since each, almost always, variable is calculated empirically. One of the most important design variables is the internal temperature of the transformers, which directly influences the lifetime of such equipments. So, a computational tool is under development whose purpose is to automate the design of cast resin dry‐type transformers and minimize the time taken for its completion, by means of artificial neural networks. In this article, we present some results of this tool, which relate some geometrical parameters of the specific transformer with the temperature of its windings. For this, the winding losses and total losses are also estimated. The training of the neural network was done with the test data of about 300 dry‐type transformers from the same manufacturer, so, with the same constructive features. Nevertheless, our results show that the technique is promising because the neural networks were well fitted and its results present errors lower than 1% when compared with data from tests with real transformers. Evidently, the proposed methodology is dependent on the constructive technique; that is, once trained, the neural network can be used only in the design of dry‐type transformers of the same constructive technique as those whose results of the tests were used to train the network. Nevertheless, even if only used to provide the initial parameters for a more complex design tool, the proposed method is useful since it is rapid and has low computational cost.

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UTFPR-CP). Sob a orientação de um professor supervisor, os alunos realizavam visitas semanais a quatro habitações de baixa renda em aproximadamente dez meses de duração total. Durante as visitas, os alunos aplicaram conceitos de metodologias ativas de ensino, como a aprendizagem baseada em projetos (ABP). A partir dos dados coletados, através da experiência, é possível inferir que as metodologias ativas apresentam resultados importantes. No entanto, o papel do professor é um elemento fundamental para o sucesso da experiência, pois os papéis de professores e alunos precisam ser reconfigurados a partir de uma lógica linear, não hierárquica, permitindo que eles ajam e aprendam juntos.