A grey-box modelling methodology for liquid-based building integrated photovoltaic/thermal collectors
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper presents the validation and calibration of a grey-box modelling methodology for a liquid-based PV/T collector. A 1st order simplified thermal network model was developed and calibrated utilizing PV/T experimental testing data from a large-scale solar simulator in Concordia University, Canada. The grey-box model was then evaluated with multiple datasets with varying parameters including solar irradiance, surface wind speed, and mass flow rate in quasi-steady-state conditions. The average overall relative error stayed below 1.69% for all test cases while the maximal relative error between the model and the experimental measurements was 1.52% for the PV/T electrical production and 4.78% for the fluid outlet temperature. The grey-box methodology has shown that a PV/T model can be calibrated utilizing only the electrical production of the PV/T and the inlet/outlet temperatures to achieve high-accuracy prediction of the electrical and thermal performance. The study found that the largest impact on the error between the model and the experimental data was found to be the effect of wind speeds and mass flow rates.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it