Machine learning using the rice quality data obtained from the DS2014PHY samples (IRRI).
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Feb 26, 2019 - Jupyter Notebook
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rheometry
Here are 4 public repositories matching this topic...
Code and synthetic data for “Complementary dissipation potential in pressure-driven flow of shear-thinning and yield-stress fluids” (Y. Wang, Preprints.org, 2026). Reproduces every figure, table and number from fixed seeds.
python reproducible-research inverse-problems rheology non-newtonian-fluids rheometry velocimetry capillary-flow yield-stress-fluids complementary-dissipation-potential legendre-fenchel-transform
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Oct 20, 2026 - TeX
Rheology for engineers in Python: validated methods, an 18-notebook course with worked solutions
python scientific-computing chemical-engineering rheology non-newtonian-fluids rheometry herschel-bulkley-fluids viscoelasticity polymer-melts oscillatory-shear
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Sep 28, 2026 - Jupyter Notebook
Python and browser implementation of the Mullineux (2008) determinant method for fitting the Herschel–Bulkley model to flow-curve data, with goodness-of-fit and nested-model tests
python model-selection curve-fitting goodness-of-fit rheology flow-curves nonlinear-least-squares rheometry herschel-bulkley-fluids yield-stress
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Sep 20, 2026 - HTML
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