Bibliographic record
Abstract
The chilling output of the chiller fluctuated according to the chilling load. When it dropped down below a certain value, the temperature of the supply chilled water flowing out of the chiller would drop down too much. And this would result the chiller being shut down abnormally, because of its low temperature protection. Any this shutdown of the chiller endangered the production continuity and security, and caused a certain economic losses. A bypass, which was from the outlet of the chiller’s condenser to the chilled water filter inlet, was added to the chilling system. Through this bypass, some cooling water was introduced from the cooling water circulation into the chilled water circulation. Then the temperature of the supply chilled water flowing out of the chiller was promoted. With experiments, and by the aid of thermodynamics analysis, the amount of introduced cooling water, which could be introduced to promote the supply chilled water temperature for maintaining the chiller running normally, was researched. Ultimately, a certain amount of introduced cooling water, at which the chiller would no longer stop abnormally at any chilling load, was determined. And the energy lose caused by the introduced cooling water was less than 5 percent the rated output of the chiller. Compared with the chiller rated output, this energy lose was so small that it could be neglected.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".