We address a central issue that arises within element-based topology optimization: To achieve a sufficiently well-defined material interface, one requires a highly refined finite element mesh, however, this leads to an increased computational cost due to the solution of the finite element analysis problem. By generating an optimal structure on a coarse mesh and using an artificial neural network to scale up to a larger domain, we can greatly reduce computation time. This approach resulted in time savings of up to 85% for test cases considered. This significant advantage in computation time also preserves the structural integrity when compared to a fine mesh optimization with limited error. Along with the savings in computation time, the boundary edges become more refined during the process, allowing for a sharp transition from solid to void. This improved boundary edge can also be leveraged to improve the manufacturability of the optimized designs.

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