Development of a Computational Model for Characterizing Viscoelastic Polymer Solutions
Understanding the stretchy qualities of complex fluids is crucial for industries such as inkjet printing, food manufacturing, fiber spinning, and pharmaceuticals. Special devices called filament and capillary breakup rheometers are often used to study these properties. Despite this, one of the biggest challenges in these industries is accurately measuring the “relaxation times” — a key factor that influences how these fluids behave under stress. This measurement is challenging to standardize and usually needs manual tweaks, which can be inefficient and inconsistent. To tackle this problem, our project is creating an automated toolbox designed to use data from simulations and experiments to figure out these relaxation times more precisely when the fluid is stretched. This toolbox isn’t just about automation; it’s about increasing accuracy by combining simple and advanced models of how the fluid flows and reacts with actual experimental observations. One exciting feature of our toolbox is the use advanced numerical simulations and super-resolution AI techniques. These powerful tools will help us process images from the experiments to observe extremely fine details of how the fluid thins out, down to subpixel levels. This means we can see tiny changes that were previously invisible, improving our understanding and measurement accuracy.
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