Development of a Python library for finite element analysis of truss systems with energy minimization

In the field of structural engineering, the analysis and understanding of truss systems hold great significance. These systems are constructed using bars that connect nodal points and find applications in various fields such as construction, aviation, and mechanical engineering. As the demand for optimized and efficient structural designs increases, there is a growing need for powerful computational tools capable of accurately modeling and analyzing truss systems. The Finite Element Method (FEM) emerges as a prominent computational tool used to comprehend and predict the behavior of complex systems. FEM enables engineers to analyze the response of a system under different loads and boundary conditions by breaking down structures into smaller and manageable elements. However, FEM falls short in completing the analysis in cases of missing support reactions (external instability) within the structural system. Innovative energy minimization methods are employed to address such issues. This method is grounded in the principle of minimum energy in nature, seeking the position where the system possesses minimum energy. For systems lacking classical mechanical stability, the energy minimization method aims to determine the position that yields the minimum energy. This master's thesis introduces a new Python library that integrates Finite Element Analysis with energy minimization techniques for truss systems. The proposed library not only provides engineers with an accessible and versatile tool but also incorporates energy minimization principles for optimizing the design and performance of truss structures. Additionally, it includes a brief introduction to both metaheuristic and non-metaheuristic algorithms, fostering discussions on selecting the appropriate method for analysis.