Fast and accurate inclusion of steam properties in two- and three-dimensional steam turbine flow calculations
Bibliographic record
Abstract
The Denton time-marching method for turbomachinery flow calculation has been modified for rapid and accurate access to the properties of steam in equilibrium dry and wet states and in the metastable dry region. Transition between metastable dry and equilibrium wet states is accomplished either at the stable equilibrium boundary or by allowing metastable equilibrium expansion followed by a condensation shock whose location depends on the local degree of subcooling of the metastable vapour and the local expansion rate. Steam properties and their derivatives are obtained from a wide-ranging Helmholtz representation of equilibrium (stable and metastable) thermodynamic properties and stored for use in an accurate Taylor series representation. Comparisons have been made of flow development in a low-pressure steam turbine blade row for three expansion assumptions: equilibrium stable and metastable dry, stable equilibrium, dry and wet, and dry expansion prior to a condensation ‘shock’ which is followed by equilibrium wet expansion. Inclusion of real steam properties extends calculation time for one iteration cycle by about 5 per cent and has little effect on the number of cycles required for convergence in the absence of a condensation shock; however, inclusion of the shock may double the time required for convergence.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".