TRANSIENT RESPONSE OF DIFFERENT REFRIGERANTS USED IN SINGLE-PASS DUAL CHILLER
Bibliographic record
Abstract
A number of process parameters can affect the performance of the district cooling plant, in which the vapor compression refrigeration (VCR) cycle has been widely employed. Two major process disturbances are: the end-user daily varying cooling demand (temperature of the received chilled water) and the seasonal changes in environmental conditions (cooling water temperature). This paper aims to investigate the effect of the selected refrigerants (R134a, R32, R717, R1234yf, R410a) on the transient response of dual chillers. It considers the cooling water temperatures as the process disturbances and disturbance are introduce in two fashion; namely sudden temperature increase and ramp temperature increase. The dynamic behavior of the process dependent variables, namely, the condensing temperature, evaporating temperature, and the coefficient of Performance (COP) are investigated. It is observed that the transient time that is needed for the given refrigerant to reach the new steady-state follows the following rank of refrigerants, starting with the fastest to the slowest: R410a, R32, R134a, R1234yf, and R717. Further, it is observed that the least reduction in COP upon the disturbance occurs in the chillers that run with R717, while the highest is associated with the one that has R134a.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".