Impacts of Ground Slope on Main Performance Figures of Solar Chimney Power Plants: A Comprehensive CFD Research with Experimental Validation
Bibliographic record
Abstract
Geometric parameters in solar chimney power plants are numerically optimised for the purpose of better power output figures. Several parameters have been investigated in the pilot plant such as chimney height and diameter, collector diameter and slope, and slenderness. However, ground slope has not been studied to date despite its perspicuous impact on turbulent flow. In this study, the impacts of the different slope angles of the ground, where the solar radiation is absorbed through the collector, on the main performance parameters of the system are numerically analysed through a reliable CFD software ANSYS FLUENT. By considering the actual geometric figures of the pilot plant, a 3D model is constructed through DO (discrete ordinates) solar ray tracing algorithm and RNG k-ε turbulence model. For the solar intensity of 1000 W/m2, the maximum velocity inside the system is found to be 14.2 m/s, which is in good accordance with the experimental data of 15.0 m/s. Starting from 5 m inside the collector, the chimney inlet heights are reconfigured 0.209, 0.419, 0.625, 0.838, and 1.04 m, respectively, and when the ground slope is 0.1, 0.2, 0.3, 0.4, and 0.5°, the changes in the performance output of the system are investigated. For the reference case which refers to the horizontal ground, the maximum air velocity is determined to be 14.2 m/s and the power output is 54.3 kW. However, when the ground slope is made 0.5°, it is observed that the maximum velocity increases by 37% to 19.51 m/s, and the power output is enhanced to 63.95 kW with a rise of 17.7%. Sloping ground is found a key solution to improve the turbulent effects inside the plant, thus to enhance the electrical power output.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".