Bibliographic record
Abstract
The main goal of this study is to perform simulations of droplet dynamics using Truchas, a LANL-developed computational fluid dynamics (CFD) software, and compare them to a computational study of Hysing et al.[IJNMF, 2009, 60:1259]. Understanding droplet dynamics is of fundamental importance in liquid-liquid extraction, a process used in the nuclear fuel cycle to separate various components. Simulations of a single droplet rising by buoyancy are conducted in two-dimensions. Multiple parametric studies are carried out to ensure the problem set-up is optimized. An Interface Smoothing Length (ISL) study and mesh resolution study are performed to verify convergence of the calculations. ISL is a parameter for the interface curvature calculation. Further, wall effects are investigated and checked against existing correlations. The ISL study found that the optimal ISL value is 2.5{Delta}x, with {Delta}x being the mesh cell spacing. The mesh resolution study found that the optimal mesh resolution is d/h=40, for d=drop diameter and h={Delta}x. In order for wall effects on terminal velocity to be insignificant, a conservative wall width of 9d or a nonconservative wall width of 7d can be used. The percentage difference between Hysing et al.[IJNMF, 2009, 60:1259] and Truchas for the velocity profiles vary from 7.9% to 9.9%. The computed droplet velocity and interface profiles are found in agreement with the study. The CFD calculations are performed on multiple cores, using LANL's Institutional High Performance Computing.
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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".