Representing Polydispersed Droplet Behavior in Nucleating Steam Flow With the Quadrature-Method-of-Moments
Bibliographic record
Abstract
This paper applies the Quadrature-Method-of-Moments (QMOM) to the polydispersed droplets spectrum typical in low pressure steam turbines. Various modes of nonequilibrium phase transition are present in steam turbines, starting with primary and secondary homogeneous nucleation as the main source of moisture followed by heterogeneous nucleation and surface entrainment sources. The range of phase transition possibilities leads to a wide range of droplet sizes, which are present under various combinations of inertial and thermal nonequilibrium. Given the extensive prevalence of CFD in turbomachinery design, it is of interest to develop an efficient modeling approach for polydispersed droplet flows that avoids solving an excessive number of equations to represent the droplet size distribution. Methods based on QMOM have shown promise in this regard in other applications areas of two-phase flow, and this paper attempts to quantify its potential for steam turbine applications by applying the method to supersonic nozzle studies with homogeneous and heterogeneous phase transitions.
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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) | 0.002 | 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".