Experimental proof-of-principle of heat recovery and recirculation in a reciprocating steam engine. Applicability of the technology to present electricity generating power plants and estimation of the yearly world energy saving and reduction of greenhouse gas emission
Bibliographic record
Abstract
The motivation for the present study is energy production from thermonuclear fusion, as discussed in recent works [Panarella, Phys. Essays 33 , 283 (2020); 34 , 256 (2021); Peretti et al ., Phys. Essays 34 , 596 (2021)]. The direction of research for the attainment of the milestone of fusion energy breakeven was analyzed in depth in those works. The path of increasing the efficiency of the energy input deposition was found to be favorable relative to the alternative path of increasing the fusion energy output in ever bigger machines, as pursued for the past seven decades by all major research programs. The input for the fusion machines is electrical energy, which is generated from conventional engines that convert heat to work. In a simulation study, it was found that the efficiency of these engines could be improved through heat recovery and recirculation without violating the second law of thermodynamics. However, an experimental proof-of-principle was required to conclusively prove what the simulation indicated to be possible. The present study reports on such an experimental confirmation. It demonstrates experimentally a novel thermodynamic cycle where heat is re-used and re-circulated in a reciprocating steam engine. An advanced study of the second law of thermodynamics is provided that justifies this experimental result, as well as its historical interpretation. Re-use and recirculation of heat in engines used in power plants all over the world leads to global energy savings, as well as to significant reductions of global greenhouse gas emissions. These are estimated on a yearly time-scale with the most recent data available. Their significance regarding mitigation of climate change is highlighted.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".