Thermodynamic and Exergoeconomic Analyses of a Novel Combined Cycle Comprised of Vapor-Compression Refrigeration and Organic Rankine Cycles
Bibliographic record
Abstract
In this study, a cooling/power cogeneration cycle consisting of vapor-compression refrigeration and organic Rankine cycles is proposed and investigated. Utilizing geothermal water as a low-temperature heat source, various operating fluids, including R134a, R22, and R143a, are considered for the system to study their effects on cycle performance. The proposed cycle is modeled and evaluated from thermodynamic and thermoeconomic viewpoints by the Engineering Equation Solver (EES) software. Thermodynamic properties as well as exergy cost rates for each stream are found separately. Using R143a as the working fluid, thermal and exergy efficiencies of 27.2% and 57.9%, respectively, are obtained for the cycle. Additionally, the total product unit cost is found to be 60.7 $/GJ. A parametric study is carried out to determine the effects of several parameters, such as turbine inlet pressure, condenser temperature and pressure, boiler inlet air temperature, and pinch-point temperature difference, on the cycle performance. The latter is characterized by such parameters as thermal and exergy efficiencies, refrigeration capacity, produced net power rate, exergy destruction rate, and the production unit cost rates. The results indicate that the system using R134a exhibits the lowest thermal and exergy efficiencies among other working fluids, while the systems using R22 and R143a exhibit the highest energy and exergy efficiencies, respectively. The boiler and turbine contribute the most to the total exergy destruction rate.
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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".