PyTopo3D: A Python Framework for 3D SIMP-based Topology Optimization
It provides an incremental software solution for engineers, students, and researchers to more easily apply 3D topology optimization in Python-based environments.
The paper tackles the lack of readily usable, open-source 3D topology optimization tools in Python by introducing PyTopo3D, a framework that implements the SIMP method with enhanced features like STL import/export and accelerated filtering, resulting in an accessible tool for engineering workflows.
Three-dimensional topology optimization (TO) is a powerful technique in engineering design, but readily usable, open-source implementations remain limited within the popular Python scientific environment. This paper introduces PyTopo3D, a software framework developed to address this gap. PyTopo3D provides a feature-rich tool for 3D TO by implementing the well-established Solid Isotropic Material with Penalization (SIMP) method and an Optimality Criteria (OC) update scheme, adapted and significantly enhanced from the efficient MATLAB code by Liu and Tovar (2014). While building on proven methodology, PyTopo3D's primary contribution is its integration and extension within Python, leveraging sparse matrix operations, optional parallel solvers, and accelerated KD-Tree sensitivity filtering for performance. Crucially, it incorporates functionalities vital for practical engineering workflows, including the direct import of complex design domains and non-design obstacles via STL files, integrated 3D visualization of the optimization process, and direct STL export of optimized geometries for manufacturing or further analysis. PyTopo3D is presented as an accessible, performance-aware tool and citable reference designed to empower engineers, students, and researchers to more easily utilize 3D TO within their existing Python-based workflows.