Comparative efficiency assessment of a multi-flash integrated system based on three efficiency definitions
Bibliographic record
Abstract
This paper deals with energy and exergy analyses of a multi-flash integrated system and studies three efficiency definitions for system assessment. In this regard, a comparative performance evaluation is conducted to investigate the effects of using these energy and exergy efficiencies on the assessment of a triple-flash integrated system with an electrolyzer. Parametric studies are conducted to investigate the effect of rise in the ambient temperature and geothermal source temperature on these energy and exergy efficiencies. The results show that the efficiency definition plays a critical role as the efficiency value differs from one definition to another. Increasing the ambient temperature decreases both energy and exergy efficiencies based on the first definition, but increases them based on the second and third definitions. An increase in the geothermal source temperature reduces both energy and exergy efficiencies based on the first definition, but increases them based on the second and third definitions of efficiencies. The energy and exergy efficiencies of the overall system based on the third definition are found to be increasing from 0.6 to 2.2% and 6.5 to 47.29%, respectively.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".