Welcome to our comprehensive guide to topology optimization techniques! Whether you’re a student, a researcher, or a curious individual looking to expand your knowledge, this webpage is designed to be your go-to resource for understanding and implementing these powerful computational methods. Topology optimization is a cutting-edge field at the intersection of mathematics, engineering, and computer science. It involves utilizing advanced algorithms and mathematical optimization to determine the optimal distribution of material within a given design space, with the goal of achieving superior structural performance.
Since our codes are based on GitHub, we advise that the interested party go to our repository (github.com/LTM-Unicamp) and verify which ones are available for viewing or cloning. Written mostly in Matlab and Python, these repositories provide a hands-on approach to learning and implementing a few topology optimization methods. You’ll discover different approaches such as density-based methods and evolutionary algorithms, each offering unique advantages and insights into the optimization process. Besides, we have provided detailed explanations and documentation alongside the codes, that covers mechanics, acoustics, electricity and thermal applications. Since we are constantly expanding it, few free to explore these codes and experiment with different techniques. Examples of what we have so far are:
Sequence of Python programs of increasing complexity for solving density-based Topology Optimization (TO) problems through Sequential Convex Programming (SCP).
Sequence of Python programs of increasing complexity for solving density-based Topology Optimization (TO) problems through Sequential Integer Linear Programming (SILP).
More is coming soon!