A modelling framework for jet penetration into soft gels
Bibliographic record
Abstract
Jet penetration into soft gels is essential for optimising fluid delivery in medical therapies, biomedical engineering, and soft robotics. In this work, we visualise the jet flow of a Newtonian fluid into a soft viscoplastic gel using camera imaging and time-resolved tomographic particle image velocimetry (PIV) systems. The flow is primarily governed by the Reynolds number ( $Re = 350-5000$ ) and the effective viscosity ratio ( $m$ up to 22). We observe three flow regimes – mixing, jellyfish, and fingering – with transitions between them quantified in the $Re-m$ plane. An experimentally informed, systematic, practical, semi-analytical modelling framework is developed to estimate jet penetration depth over time, incorporating PIV results and an approximate functional decomposition approach to describe the velocity distribution and Reynolds stress contributions. The model provides reasonable estimations across all three regimes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".