Investigation of mechanical heat pump systems for heat upgrading applications
Bibliographic record
Abstract
Three high temperature heat pump systems based on vapor compression cycles are introduced and examined. Four fluids (water, cyclohexane, biphenyl and mercury) are selected and analysed thermodynamically as prospective working fluids for the high temperature heat pumps. These working fluids are used in cascaded cycles to upgrade the heat to a temperature of 600 ??C. The equations of state used in performance analysis are Peng???Robinson, NRTL and IAPWS-95. A parametric analysis is carried out to study the effects of isentropic efficiency, sink temperature, source temperature, and ambient temperature on the system performance. Energetic and exergetic COPs of the overall and individual cycles are determined. The COP values obtained are found to range from 2.08 to 4.86, depending upon the cycle and temperature levels. The System 2 (energetic and exergetic COPs are 3.8 and 1.9 respectively) outperforms System 1 (energetic and exergetic COPs are 2.2 and 1.0 respectively) both energetically and exergetically, while operating under same conditions of source temperature 81??C and sink temperature 600 ??C. The System 3 achieves maximum cycle temperature of 792 ??C while operating under moderate pressure ratios. The high COP values in some instances make these systems promising alternatives to fossil fuel and electrical heating. As a possible sustainable scenario, these pumps can utilise low grade heat from geothermal, nuclear or thermal power plants and derive work from clean energy sources (solar, wind, nuclear) to deliver high grade heat. The high delivery temperatures make these heat pumps suitable for processes with corresponding needs, like high temperature endothermic reactions, metallurgical processes, distillation, and thermochemical water splitting.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".