Data supporting the publication: Vision-Informed Short-Horizon Prediction for the Squeeze Flow of Soft Materials
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This dataset supports the paper "Vision-Informed Short-Horizon Prediction for the Squeeze Flow of Soft Materials." It contains the experimental data, simulation data and results used to evaluate a vision-informed framework for parameter estimation and short-horizon prediction of the squeeze flow of soft specimens. The dataset includes: Physical experiment data - RGB video recordings from five repeated squeeze flow trials of a playdough specimen compressed under a constant load, along with the extracted 2D border observations and ArUco-marker-based height measurements used as ground truth. Synthetic experiment data - Ground-truth simulation data for all 17 synthetic scenarios (A.I–A.VI, B.I–B.VI, C.I, D.I–D.III and E.I). These cover constant homogeneous, time-varying homogeneous and time-varying heterogeneous (Carreau) viscosity materials, cylindrical and cuboidal specimens, constant and time-varying loading, and a range of slip conditions. This includes:- Directly projected FE border sequences (simulated borders) used to isolate the estimation components from perception uncertainties- Photorealistic video renderings generated in Blender used to exercise the full …
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