Exergy Efficiency and COP Improvement of a CO2 Transcritical Heat Pump System by Replacing an Expansion Valve with a Tesla Turbine
Bibliographic record
Abstract
The heat pump system has been widely used in residential and commercial applications due to its attractive advantages of high energy efficiency, reliability, and environmental impact. The massive exergy loss during the isenthalpic process in the expansion valve is a major drawback of the heat pump system. Therefore, the Tesla turbine exergy analysis in terms of transiting exergy efficiency is investigated and integrated with the transcritical heat pump system. The aim is to investigate the factors that reduce exergy losses and increase the coefficient of performance and exergy efficiency. The contribution of this paper is twofold. First, a three-dimensional numerical analysis of the supercritical CO2 flow simulation in the Tesla turbine in three different geometries is carried out. Second, the effect of the Tesla turbine on the coefficient of performance and exergy efficiency of the heat pump system is investigated. The effect of the rotor speed and disk spacing on the Tesla turbine power, exergy loss, and transiting exergy efficiency is investigated. The results showed that at a lower disk spacing, the turbine produces higher specific power and transiting exergy efficiency. In addition, the coefficient of performance (COP) and exergy efficiency improvement in the heat pump system combined with the Tesla turbine are 9.8% and 28.9% higher than in the conventional transcritical heat pump system, respectively.
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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".