Experimental performance of a seasonally adaptive asymmetric compoundparabolic concentrator
Bibliographic record
Abstract
While tracking solar concentrators are a useful technology for high temperature applications including concentrating solar power (CSP), their tracking systems make them complex and expensive when implemented for lower temperature applications, including process and space heating. By removing the need for tracking, stationary solar concentrators are a promising low-cost technology to meet the demand for such low to medium temperature applications. The implementation of stationary concentrators at high latitudes, where acceptance angles are not symmetrical, favours the use of Asymmetric Compound Parabolic Concentrators (ACPCs). But, when year-round concentration is desired, stationary concentrators face a difficult challenge due to the inverse relationship between the maximum geometric concentration (Cg,max) and the acceptance angle. To address this, we developed an innovative reconfigurable stationary ACPC. The design features two configurations, one for winter and one for summer, which are interchanged by a simple switching movement of one of the mirror walls. This reconfigurable ACPC allows for year-round performance with a concentration surpassing the theoretical limit for a standard non-reconfigurable design. A prototype was developed for Toronto's latitude (43.7 North) and was designed to have at least 6 hours of useful collection time year-round. The resulting design has an acceptance halfangle of i = 45, and can reach average concentrations of up to 2, which notably surpasses the theoretical maximum concentration of Cg,max,2D = 1/sini =1.41. The prototype design was evaluated using both Monte Carlo Ray Tracing (MCRT) simulations and outdoor flux mapping experiments. The MCRT simulations have been found to line up well with both theory and experimental results. The outdoor experiments were performed at the rooftop of the Bergeron Center in York University, Toronto (43.772 North, 79.507 West) utilizing an innovative flux-mapping procedure. Experiments were performed near Summer Solstice, September Equinox and Winter Solstice, demonstrating good real-world performance at different solar altitudes. The results obtained show that the reconfigurable ACPC is a low-cost alternative to meet low to medium temperature heating demands sustainably at high latitudes.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".