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The usual approach to engineering education, though appropriate for some students, in general lacks adaptability for different learning needs. Game-based learning is an attempt to provide adaptable learner-centered education. This paper presents a review of the published works on game-based applications for Mechanical Engineering teaching and learning from the past five decades. A comprehensive review was performed, and more than 200 papers were screened, evaluating the gamification approach, educational objectives, and Mechanical Engineering curriculum. Bloom’s taxonomy was used to identify cognitive learning outcomes for each of the games studied. There was also an attempt to establish Mechanical Engineering topics for an efficient curriculum and a correspondence of each game analyzed with the specific topic. The references found are presented according to Mechanical Engineering knowledge topic and cognitive learning outcome. Suggestions for further research on the field are made. The main ones include the need to formalize the educational objectives and development goals of the games, since most of the games studied did no such formalization, as well as the development and design strategies adopted to achieve such goals, a recently growing field of study.

Seeking to define more robust and executable structures, this article presents a computational framework for the optimal design of steel truss frames, which integrates two software of great prominence in structural engineering, MATLAB and ANSYS. Computational interfaces were created to enable the automation of the iterative optimization process. The optimization algorithm and computational interfaces were developed on the MATLAB platform, while structural analyses were performed with the ANSYS Mechanical APDL platform. Some details of the computational implementation are presented herein. The objective is to minimize the cost of structures by determining the optimal positioning of nodal coordinates and the optimal choice of commercially available structural profiles -shape and size optimization, respectively. For shape optimization, a computational model was defined to automatically generate the geometry of the structure, maintaining some intrinsic relations of symmetry and collinearity between elements. The design constraints are critical nodal displacements, stresses, and slenderness of elements, following the requirements of ABNT NBR 8800:2008. To exemplify the application of the proposed methodology, this article presents the optimal design of trusses for roofs of industrial sheds, considering its non-linear geometric behavior, typical of this type of structure.

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