Application of ultrasound Doppler technique for in‐line rheological characterization and flow visualization of concentrated suspensions
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Bibliographic record
Abstract
Abstract Ultrasonic velocity profiling (UVP) is a technique that can measure an instantaneous one‐dimensional velocity profile in a fluid containing particles across the ultrasonic beam axis or measurement line. A method for in‐line rheometry combining the UVP technique with pressure difference (PD) measurements (UVP + PD), was developed and improved at SP − Technical Research Institute of Sweden and the Cape Peninsula University of Technology, South Africa. The UVP + PD methodology allows measurements that are not possible with common rheometers such as radial velocity profiles and yield stress directly in‐line and under true dynamic process conditions. Furthermore, it has advantages over commercially available process rheometers and offline instruments in being non‐invasive, applicable to opaque and concentrated suspensions, and having small sensor dimensions. It has been evaluated for several potential industrial applications including paper pulp, foods, transient flows, and model mineral suspensions. Similarly, the UVP technique can be applied to an open‐channel flow by combining flow depth measurements to obtain rheological properties in‐line. Industrial fluids, such as thickened pastes, commonly found in tailings transportation exhibit wide particle size distributions, large particle sizes, and very high viscosities. These industrial fluids cause strong attenuation of the ultrasound energy, which can significantly distort velocity profiles measured with the UVP technique or even make it impossible to conduct flow measurements. Initial results obtained in concentrated cement pastes and grouts (bentonite and kaolin clay) showed that UVP is a feasible and promising technique for flow characterization in viscous fluids.
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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 it