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<p>Topology optimization typically yields material distributions defined on finite element or isogeometric grids, a discrete format that hinders direct geometry reconstruction, CAD editing, and downstream engineering simulation. To address this interoperability gap, this paper presents a portable MATLAB framework for converting two-dimensional optimization results into trimmed NURBS representations, exported as standardized IGES files. The proposed methodology integrates image-based connected-component analysis for reliable boundary detection, a smoothness-adjustable curve-fitting scheme for precise contour reconstruction, and a compact IGES-writing routine that preserves the parametric structure of the optimized design. The framework is solver-agnostic, accommodating diverse topology optimization data types, including structured meshes, unstructured polygonal meshes, and isogeometric analysis outputs. The MATLAB code is open-source, enabling other researchers to reproduce and extend the proposed workflow. The effectiveness of the method is demonstrated through a series of representative benchmark problems, showing that the generated IGES models support seamless geometric modification and high-fidelity finite element analysis. Overall, this tool provides a practical and portable bridge between numerical topology optimization and downstream CAD/CAE workflows.</p>

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top2iges: A Portable MATLAB Code for Converting Topology Optimization Results into IGES Files with NURBS Representation

  • 期刊论文

  • 发表日期：

    2026年4月30日

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  • Jiayi Li,
  • Mengchan Liu,
  • Shengxue Wang,
  • Xiaoxiao Du,
  • Gang Zhao

摘要

Topology optimization typically yields material distributions defined on finite element or isogeometric grids, a discrete format that hinders direct geometry reconstruction, CAD editing, and downstream engineering simulation. To address this interoperability gap, this paper presents a portable MATLAB framework for converting two-dimensional optimization results into trimmed NURBS representations, exported as standardized IGES files. The proposed methodology integrates image-based connected-component analysis for reliable boundary detection, a smoothness-adjustable curve-fitting scheme for precise contour reconstruction, and a compact IGES-writing routine that preserves the parametric structure of the optimized design. The framework is solver-agnostic, accommodating diverse topology optimization data types, including structured meshes, unstructured polygonal meshes, and isogeometric analysis outputs. The MATLAB code is open-source, enabling other researchers to reproduce and extend the proposed workflow. The effectiveness of the method is demonstrated through a series of representative benchmark problems, showing that the generated IGES models support seamless geometric modification and high-fidelity finite element analysis. Overall, this tool provides a practical and portable bridge between numerical topology optimization and downstream CAD/CAE workflows.