A fast tabulated equation of state for CFD simulation of two-phaseflows
Bibliographic record
Abstract
Abstract: One of the challenging aspects when performing CFD of multi-phase flows is the modeling of the fluid equation of state, used to close the system of equations. Firstly, one must define a model to handle the two-phase behavior of the fluid, i.e., under the saturation curve, as it is generally not described by the equation of state itself, that is only valid outside of the saturation dome. Secondly, the related numerical method during the simulation itself should be quite fast as it will be called as many times as there are point/cells in the mesh at each iteration. In this work, a novel tabulated equation of state method is presented, with the intent of performing fast and accurate CFD of flashing nozzles/ejector-type devices. The table is built using the equation of state provided by the REFPROP library and is here applied to two-phase CO2, although the method could be used for any fluid. Likewise, any thermodynamic relation that is implemented in REFPROP can be generated as a tabulated method. A bicubic interpolation scheme is used with local refinement of the meshing in the thermodynamic domain. For the purpose of this work, the tabulated method was coupled to the SU2 density-based solver. Results indicate that the present method is about 10 times faster than previously tabulated methods for CO2, and about 500 times faster than the Span-Wagner equation of state, which is the reference for that fluid.
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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".