A Numerical Study of a Wavy Fin and Tube CO<sub>2</sub> Evaporator Coil
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Carbon dioxide is among the promising natural refrigerant alternatives to HCFCs and HFCs for refrigeration. In the perspective of this development, a numerical model for dry evaporator coil design and simulation, based on correlations for carbon dioxide, is presented, along with typical cooling coil simulations. The model uses the NIST database for refrigerant properties and provides adequate flexibility for local parameter calculations across the coil. The heat transfer and pressure drop data used to validate this model originate both from a dedicated test bench built in our laboratories and from other sources. These data were predicted satisfactorily over the operating range corresponding to refrigeration applications. Apart from the air side pressure drop, which is predicted with a maximum uncertainty of 25%, a comparison between experiments and calculation are within 1°C for air and CO2 outlet temperatures and within 13.5% for capacity and CO2 pressure drop. Simulations at low and moderate temperatures were performed on coil configurations typically used in supermarket applications. Key parameter distributions, including temperatures, pressures, and relative humidity, were tracked inside and outside the tube coil. Tube relative positions in the coil largely influenced phase repartition and overall operation. The resulting air temperature distribution gradients were also affected.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it