Propaani kiinteäasenteisten yksiosaisten lämpöpumppujen kylmäaineena
Bibliographic record
Abstract
Climate change and the growing concern for energy self-sufficiency are pushing societies to seek more sustainable energy solutions. In Northern Europe, heating accounts for a significant share of total energy consumption, while at the same time, the need for cooling has also increased. Heat pumps offer an excellent technical solution for improving energy efficiency and reducing the emissions from both heating and cooling. The environmental impacts of refrigerants and tightening legislation have become central issues, leading to the adoption of more environmentally friendly alternatives such as propane. The Montreal Protocol governs international refrigerant regulation, and its latest addition, known as the Kigali Amendment, restricts the use of HFC compounds. The European Union has ratified this amendment with its new F-gas regulation, which will completely ban the use of high-GWP compounds by 2050. The most significant restrictions will take effect earlier, in 2027 and 2030, causing a rapid change in the market for new equipment. Alongside the F-gas regulation, which came into force in 2024, the upcoming REACH regulation update restricting PFAS compounds is also steering the market towards natural refrigerants. Hydrocarbons – especially propane – are among the most promising replacements for current refrigerants in heat pump solutions for commercial and residential apartment buildings. The aim of this thesis is to compare the measured COP value of a propane heat pump with the performance values stated by the equipment manufacturer and to examine the additional requirements posed by the flammability of the refrigerant from a project planning perspective. Measurement data for the analysis was collected from a heat pump installed in a commercial building in Satakunta using the building automation system. The objective is to assess the comparability of the results to residential buildings, where there is no high-temperature waste heat source similar to the rejected heat from refrigeration in commercial facilities. Based on the results, propane is technically suitable as a refrigerant, but the challenges include higher costs and lower efficiency compared to the currently used HFC refrigerants.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.087 | 0.033 |
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".