This work integrates the use of Python in the approach and solution of electrical circuits exercises using nodal analysis. The didactic unit is composed of three modules that are closely linked and gradually introduce the nodal analysis starting with the analysis of resistive circuits with DC excitations, passing through a brief introduction to the frequency analysis using phasors and ending with an exercise more complete analysis in frequency with controlled sources.The unit is intended to accompany the student of computational engineering or related in an introductory course to the analysis of electrical circuits serving as an organizing and guiding element of the different activities that involve the development of this type of exercises: identification of node voltages, presentation of the control variables in terms of node voltages, identification of possible supernodes, statement of the circuit equations in their matrix form and their numerical solution.It is an original material arising from work experience during the development of the subject. All four team members participated in the design, writing, and development of the examples listed here. Erick Mauricio initially proposed the material for the first module on a complete nodal analysis exercise on a resistive circuit (first module); Carlos D. and Nicoll Natalia in turn proposed to extend this analysis to the case of frequency analysis using phasors (third module), finding that, for a full understanding of the subject, an additional component on the concept of "phasor" was necessary. , which motivated the development of the second module by Aleyda.comments on OER:i) the quality of the content,The content of this unit is above all practical; part of typical exercises of the analysis of electrical circuits to guide the student in the different stages of its solution.ii) ease of use,In the modules that are delivered, an attempt has been made to manage a perspective of simplicity with the Python code as progress is made in the approach and solution of the exercises: readability, elegance and simplicity are characteristics of Python.iii) the effectiveness of teaching and / or learning,Based on our experience, thinking about the problem and programming its solution using Python allowed us to strengthen logical and algorithmic thinking as well as consolidate our knowledge in the field.iv) the overall potential impact of OER on Computer Science or Information Technology academic programs;The integration of programming tools in the introductory courses of electrical circuits has shown not only a high impact on the training of the student but also alters to a certain extent the dynamics of class work by allowing the integration of numerical simulation tools as a link. between theory - circuit analysis - and practice - laboratory work.
COMPSAC OER COMPETITION
