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Python is a low-cost and open-source substitute for the MATLAB programming language. This paper presents “PyTOPress”, a compact Python code meant for pedagogical purposes of topology optimization for structures subjected to design-dependent fluidic pressure loads. PyTOPress, based on the “TOPress” MATLAB code (Struct Multi Optim 66(4):97 [1]), is built using the NumPy and SciPy libraries. The applied pressure load is modeled using the Darcy law with an additional drainage term. From the obtained pressure field, the constant nodal loads are determined. The employed method makes it easier to compute the load sensitivity using the adjoint-variable method at a low cost. The topology optimization problems are solved herein by minimizing the compliance of the structure with a constraint on material volume. The method of moving asymptotes is employed to update the design variables. The effectiveness and success of PyTOPress code are demonstrated by optimizing a few design-dependent pressure loadbearing problems. The code is freely available at https://github.com/PrabhatIn/PyTOPress .

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PyTOPress: Python Code for Topology Optimization with Design-Dependent Pressure Loads

  • 会议论文

  • 发表日期：

    2026年

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  • Shivajay Saxena,
  • Swagatam Islam Sarkar,
  • Prabhat Kumar

摘要

Python is a low-cost and open-source substitute for the MATLAB programming language. This paper presents “PyTOPress”, a compact Python code meant for pedagogical purposes of topology optimization for structures subjected to design-dependent fluidic pressure loads. PyTOPress, based on the “TOPress” MATLAB code (Struct Multi Optim 66(4):97 [1]), is built using the NumPy and SciPy libraries. The applied pressure load is modeled using the Darcy law with an additional drainage term. From the obtained pressure field, the constant nodal loads are determined. The employed method makes it easier to compute the load sensitivity using the adjoint-variable method at a low cost. The topology optimization problems are solved herein by minimizing the compliance of the structure with a constraint on material volume. The method of moving asymptotes is employed to update the design variables. The effectiveness and success of PyTOPress code are demonstrated by optimizing a few design-dependent pressure loadbearing problems. The code is freely available at https://github.com/PrabhatIn/PyTOPress .