The Role of Rotated Potential Mixing Protocols on the Behavior of a Conservative Reagent
Bibliographic record
Abstract
Abstract Chaotic advection is defined as the generation of “small‐scale structures” from the repeated stretching and folding of fluid elements in a laminar flow regime that has the potential to enhance mixing and improve treatment effectiveness. Rotated potential mixing (RPM) flow is one configuration used to invoke chaotic advection and involves periodically re‐oriented dipole flow through the transient switching of pressures at a series of radial wells. In this study, we relied on conventional models used by remediation practitioners to represent the expected flow and transport behavior of a conservative reagent subjected to chaotic advection by an RPM flow system, and then explored the impact of engineering controls on reagent mixing behavior. The various lines of evidence demonstrated that this modeling approach captured the key features of the expected transport behavior reported in other studies. Visual observations of the reagent distribution, and quantitative metrics of mixing behavior highlighted the different responses that are possible by the various combinations of RPM flow parameters explored. The results show the importance of combining theoretical considerations with practical limitations when designing an RPM flow system. The flow rate and pumping duration have direct consequences on the degree of reagent spreading and mixing. The use of the same RPM flow protocol in a heterogeneous K field led to a significantly greater degree of reagent mixing than in a homogeneous K system. The results from this investigation have important implications for the design of RPM flow protocols to promote enhanced reagent mixing and thereby improve treatment effectiveness.
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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 | 0.001 | 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".