How much exergy one can obtain from incident solar radiation?
Bibliographic record
Abstract
A thermodynamic model is proposed to study the exergetic content of incident solar radiation reaching on the Earth’s surface which can be used to produce work through a dually cascaded thermodynamic cycle. The “topping” cycle is an ad hoc engine created by nature that connects the outer shell of the terrestrial atmosphere (which is in equilibrium with the extraterrestrial solar radiation) to the collector of a solar heat engine operating on the Earth’s surface. The work produced by the topping cycle is dissipated in form of scattering, absorption, heat, movement of air masses (wind), etc. The “bottoming” cycle is a heat engine operating between the collector and surrounding temperatures, and delivers useful work. It is shown that the maximum work extractable from this system as exergy is obtained when both cycles operate reversibly. An expression for this maximum work, which represents the exergy of incident solar radiation on the Earth’s surface, is proposed. The application of the present model is illustrated and validated by calculating the exergy of solar radiation based on some measurements. The results obtained by the present model are compared to the ones obtained through other models available in the open literature.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".