Mathematical Methods for Solar Chimney Analysis
Bibliographic record
Abstract
Solar Chimney Power Plants (SCPP) – also known as Solar Updraft Power Plants – consists in a structure composed by a glass collector, placed in a few meters from the ground, with a chimney in its center, in order to promote a pressure differential and consequently a heated air flow. On the bottom of the chimney, a turbine convert the kinetic energy from the heated airflow in electric power. Many mathematical and numerical methods for predict the performance of this kind of renewable energy plant have been conducted, but always with a divergence among them. The main objective of this work is to compare the mathematical methods of evaluation the overall performance, as well to propose a more accurate mathematical method, comparing all results with Manzanares Plant and other methods in the literature. Two approaches were studied and then modified: one based on continuity and momentum equation and the other based on the sum of all pressure drops along the system. The main reasons of the difference between the models analyzed are highlighted. The results shows that one of the proposed methods leads to a divergence of only 1.3% when compared to Manzanares pilot plant, i.e., with an excellent agreement with experimental data.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".