Determining the flow transition from laminar to turbulence using simple spin-echo magnetic resonance techniques
Bibliographic record
Abstract
We have recently introduced a methodology to determine the average velocity and flow behavior index of laminar pipe flow of a power-law fluid using simple magnetic resonance (MR) techniques. In general, MR techniques are noninvasive and capable of working on optically opaque fluids. Knowledge of the average velocity and flow behavior index provides the information needed to reconstruct the flow velocity profile. However, as the flow velocity increases, the flow will begin to develop turbulence. For pipe flow of a particular fluid, the velocity profile is flatter in the center of the pipe at turbulent flow rates compared with laminar flow. An effective flow behavior index can approximate the time-averaged velocity profile, as the Reynolds number increases, as a fluid transitions from laminar to turbulent flow. Here, we show the results of testing the utility of such a simplification in monitoring that transition. For the present study, Reynolds numbers ranged from approximately 490 to 6800, which corresponds to flow rates of 200 to 2750 ml/min and average velocity of 5 to 80 cm/s. We found that visual inspection of the data would be sufficient to determine the state of the flow. With some external knowledge of the flow rate, the shape of the time-averaged velocity profile and eddy diffusivity can be estimated (and potentially also an average fluid particle acceleration).
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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".