Assessment of Cavitation Models for Flows in Diesel Injectors With Single- and Two-Fluid Approaches
Bibliographic record
Abstract
Several recent cavitation models for the analysis of two-phase flows in diesel injectors with single- and two-fluid modeling approaches have been evaluated, including the Saha–Abu-Ramandan–Li (SAL), Schnerr–Sauer (SS), and Zwart–Gerber–Belamri (ZGB) models. The SAL model is a single-fluid model, while the other two models have been implemented with both single- and two-fluid approaches. Numerical predictions are compared with experimental results available in literature, qualitatively with experimental images of two-phase flow in an optically accessible nozzle, and quantitatively with measured mass flow rates and velocity profiles. It is found that at low injection pressure differentials there can be considerable discrepancy in the predictions of the vapor distribution from the three models considered. This discrepancy is reduced as the injection pressure differential is increased. Implementation of the SS and ZGB models with single- and two- fluid approaches yields noticeable differences in the results because of the relative velocity between the two phases, with two-fluid approach providing better agreement with experimental results. The performance of the SS and ZGB models implemented with the two-fluid approach is comparable with the SAL single-fluid model, but with significantly more computational time. Overall, the SAL single-fluid model performs comparatively better with respect to the other two models.
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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".