EFFICIENCY ASSESSMENT OF GLYCOL COLD THERMAL ENERGY STORAGE AND EFFECT OF VARYING ENVIRONMENT TEMPERATURE
Bibliographic record
Abstract
The effect of varying environment temperature on the efficiency of glycol cold thermal energy storage (CTES) is investigated. Several thermodynamic system parameters are analyzed, such as change in storage temperature, storage heat load, energy and exergy efficiencies and exergy destruction. Glycol CTES is treated as a potential application of sensible heat storage systems. A storage tank with a capacity of 150,000 kg is considered with an ethylene glycol- based water solution storage medium. Exergy analysis is used, which provides more useful information than energy analysis about energy quality, efficiency, losses and irreversibilities. Modelling results indicate that the system exergy efficiency is 46% less than energy efficiency. The system exergy efficiencies are 40% and 20% at 50°C and 10°C ambient temperatures, respectively. The results imply that cold energy is more efficient at higher ambient temperatures, storage heat loss depends weakly on ambient temperature, and the reference-environment temperature affects significantly exergy destruction and efficiency.
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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".