Design, Fabrication, and Experimental Characterization of a Focusable Solar Simulator for High and Low Flux Solar Thermal Applications
Bibliographic record
Abstract
High-flux solar simulators (HFSS) advance solar thermal research but are traditionally costly and complex, limiting access for smaller institutions. This thesis presents a low-cost, adaptable solar simulator using commercially available xenon arc cinema searchlights and Fresnel lenses for dynamic irradiance control. The system was characterized through direct flux measurements with a pyranometer and indirect flux mapping via a CMOS camera, enabling detailed analysis of irradiance distribution, temporal stability, and efficiency. Experimental results showed an average irradiance of 2819 W/m² over a 12×12-inch area, peak irradiance of 2348 kW/m² with Fresnel lens concentration, and efficiencies up to 22.4% at full intensity. Real-world tests on radiative cooling coatings confirmed the simulator's capability to replicate concentrated solar conditions accurately. This study demonstrates a scalable, practical alternative to traditional HFSS, enhancing accessibility for smaller research facilities and laying a foundation for future multi-lamp and advanced optical configurations.
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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".