shayansss/hml
Implementation of a new hybrid machine learning technique for multi-fidelity surrogates of finite elements models with applications in multi-physics modeling of soft tissues.
This tool helps biomechanical engineers and researchers quickly estimate the behavior of soft tissues under various conditions using finite element models. It takes your existing finite element model data, specifically for soft tissues, and produces highly accurate predictions of tissue responses, significantly faster than traditional simulations. This is ideal for those needing to accelerate their computational biomechanics research.
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Use this if you are a biomechanical engineer or researcher working with finite element simulations of soft tissues and need to drastically reduce the time it takes to get results from complex, high-fidelity models.
Not ideal if you are new to surrogate modeling or Abaqus, as this tool requires familiarity with both to understand and implement the code effectively.
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16
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2
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Jan 21, 2024
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