The Influence of Tio2 Nanoparticles and Libr on the Exergy Efficiency of Ammonia Absorption Refrigeration System under Different Working Temperatures
Bibliographic record
Abstract
The addition of TiO 2 nanoparticles and LiBr can increase the coefficient of performance(COP) of the ammonia water absorption, but the exergy efficiency has not been investigated.Therefore, this paper studied the influence of TiO 2 nanoparticles and LiBr on the exergy efficiency under different working temperatures.The results show that the addition of TiO 2 nanoparticles or LiBr can improve the ECOP of the ammonia-water absorption refrigeration system.There is optimal T gen , T eva for the NH 3 -H 2 O-LiBr-TiO 2 working fluid, which is 110℃, -13℃.In comparison, the ECOP decreases with the T cw increases.The maximum value of ECOP in this paper is 0.266 when the T eva , T gen , and T cw are -13℃, 110℃, and 28℃.Generally, applying NH 3 -H 2 O -LiBr -TiO 2 nanofluid working fluid can efficiently improve the ECOP of the absorption refrigeration system.
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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 | 0.000 |
| 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) | 0.001 | 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".