pyRheo: an open-source Python package for complex rheology†

IF 6.2 Q1 CHEMISTRY, MULTIDISCIPLINARY Digital discovery Pub Date : 2025-03-20 DOI:10.1039/D5DD00021A
Isaac Y. Miranda-Valdez, Aaro Niinistö, Tero Mäkinen, Juha Lejon, Juha Koivisto and Mikko J. Alava
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Abstract

Mathematical modeling is a powerful tool in rheology, and we present pyRheo, an open-source package for Python designed to streamline the analysis of creep, stress relaxation, small amplitude oscillatory shear, and steady shear flow tests. pyRheo contains a comprehensive selection of viscoelastic models, including fractional order approaches. It integrates model selection and fitting features and employs machine intelligence to suggest a model to describe a given dataset. The package fits the suggested model or one chosen by the user. An advantage of using pyRheo is that it addresses challenges associated with sensitivity to initial guesses in parameter optimization. It allows the user to iteratively search for the best initial guesses, avoiding convergence to local minima. We discuss the capabilities of pyRheo and compare them to other tools for rheological modeling of soft matter. We demonstrate that pyRheo significantly reduces the computation time required to fit high-performance viscoelastic models.

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pyRheo:一个用于复杂流变学的开源Python包
数学建模是流变学中一个强大的工具,我们提出了pyRheo,一个Python的开源包,旨在简化蠕变,应力松弛,小振幅振荡剪切和稳定剪切流测试的分析。pyRheo包含粘弹性模型的全面选择,包括分数阶方法。它集成了模型选择和拟合特征,并使用机器智能来建议一个模型来描述给定的数据集。该包适合建议的型号或用户选择的型号。使用pyRheo的一个优点是,它解决了与参数优化中初始猜测的敏感性相关的挑战。它允许用户迭代搜索最佳初始猜测,避免收敛到局部最小值。我们讨论了pyRheo的功能,并将它们与软物质流变建模的其他工具进行了比较。我们证明pyRheo显着减少了拟合高性能粘弹性模型所需的计算时间。
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